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Full text of "American Society of Sugar Cane Technologists Journal, 2002-2003"

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Digitized by the Internet Archive 

in 2013 



http://archive.org/details/americansocietyo2223amer 



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JOURNAL 



American Society 

of 

Sugar Cane Technologists 



Volume 22 

Florida and Louisiana Divisions 

June, 2002 



ASSCT 



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22 
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2001 JOINT EXECUTIVE COMMITTEE 
AMERICAN SOCIETY OF SUGAR CANE TECHNOLOGISTS 



General Secretary-Treasurer 

Denver T. Loupe 



Florida Division 



Office 



Louisiana Division 



David G. Hall 
John A. Fanjul 
James M. Shine 
John Dunckelman 
Michael Damms 
Tere Johnson 
Carmen Baez-Smith 
Thomas Schueneman 



President 

First Vice-President 

Second Vice-President 

Chairman, Agricultural Section 

Chairman, Manufacturing Section 

Chairman at Large 

Past President 
S ecretary-Treasurer 



Will Legendre 

Chris Mattingly 

Tony Parris 

Keith Bischoff 

Juan Navarro 

Benjamin Legendre 

Bill White 

Denver T. Loupe 



EDITORS 

Journal American Society of Sugar Cane Technologists 
Volume 22 
June, 2002 

Managing Editor 

Ron DeStefano 

Agricultural Editor 

Nael El-Hout 

Manufacturing Editor 

Manolo Garcia 



PROGRAM CHAIRMAN 

31st Annual Joint Meeting 

American Society of Sugar Cane Technologists 
T. E. Reagan 



Honorary membership shall be conferred on any individual who has distinguished himself 
or herself in the sugar industry, and has been elected by a majority vote of the Joint Executive 
Committee. Honorary membership shall be exempt from dues and entitled to all the privileges of 
active membership. Each Division may have up to 1 5 living Honorary Members. In addition, there 
may be up to 5 living Honorary members assigned to the two Divisions jointly. (Article JJI, Section 
4 of the Constitution of the American Society of Sugar Cane Technologists). 



As of May 2001, the following is the list of the living Honorary members of the American 
Society of Sugar Cane Technologists for Florida and Louisiana Divisions: 



Florida Division 


Joint Division 


Guillermo Aleman 


Jack L. Dean 


Henry J. Andrei s 


Preston H. Dunckelman 


Pedro Arellano 


Lloyd L. Lauden 


Enrique Arias 


Denver T. Loupe 


Antonio Arvesu 


Harold A. Willett 


John B. Boy 




David G. Holder 
Arthur Kirstein III 




Jimmy D. Miller 


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Joseph Orsenigo 


t-?s 


Ed Rice 


fySLH 


Bias Rodrigues 




George H. Wedgworth 


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Louisiana Division 

Felix "Gus" Blanchard 

Richard Breaux 

P.J. "Pete" deGravelles 

Gilbert Durbin 

Minus Granger 

Sess D. Hensley 

James E. Irvine 

Dalton P. Landry 

Lowell L. McCormick 

Joe Polack 

Charles Savoie 



2001 OUTSTANDING PRESENTATION AWARDS 

Gregg Nuessly. Feeding Effects of Yellow Sugarcane Aphid on Sugarcane. 

Victoria Singleton. A New Polarimetric Method for the Analysis of Dextran and Sucrose. 

Michael E. Selassi. Economically Optimal Crop Cycle for Major Sugarcane Varieties in 
Louisiana. 

Nell Swift. Heat Transfer Devices. 



li 



. 



TABLE OF CONTENTS 

President's Message - Florida Division 

David G. Hall 1 

President's Message - Louisiana Division 

Will E. Legendre 5 

PEER REFEREED JOURNAL ARTICLES Agricultural Section 8 

Effect of Silicon-Rich Slag and Lime on Phosphorus Leaching in Sandy Soils 9 

V. V. Matichenkov, B. Ande, P. Ande, D. V. Calvert, and E. A. Bocharnikova 

Silicon as a Beneficial Element for Sugarcane 21 

V. V. Matichenkov and D. V. Calvert 

Maximizing Economic Returns from Sugarcane Production through 

Optimal Harvest Scheduling 30 

Michael E. Selassi, Lonnie P. Champagne, and Benjamin L. LeGendre 

Cultivar and Crop Effects of Sugarcane Bull Shoots on Sugarcane 

Yields in Louisiana 42 

Kenneth A. Gravois, Benjamin L. LeGendre, and Keith P. Biscoff 

Economically Optimal Crop Cycle Length for Major Sugarcane 

Varieties in Louisiana 53 

Michael E. Selassi and Janis Breaux 

Seasonally Maintained Shallow Water Tables Improve Sustainability of 

Histosols Planted to Sugarcane 62 

Brandon C. Grigg, George H. Snyder, and Jimmy D. Miller 

Sugarcane Genotype Repeatability in Replicated Selection Stages 

and Commercial Adoption 73 

Barry Glaz, Jimmy Miller, Christopher Derren, Manjit S. Kang, 

Paul M. Lyrene, and Bikram S. Gill 

PEER REFEREED JOURNAL ARTICLES Manufacturing Section 89 

Comparing the Effects of Sulphur Dioxide on Model Sucrose 

and Cane Juice Systems 90 

L. S. Andrews and M. A. Godshall 

The Effects of Two Louisiana Soils on Cane Juice Quality 101 

Mary An Godshall, Scott K. Spear, and Richard M. Johnson 



in 



A New Polarimetric Method for the Analysis of Dextran and Sucrose 112 

Victoria Singleton, Jennifer Horn, Chris Bucke, and Max Adlard 

AGRICULTURAL ABSTRACTS 120 

The Louisiana Basic Breeding Program-Past, Present, and Future 120 

Thomas L. Tew 

Assessment of Stalk Cold Tolerance of Louisiana Varieties 

During the 2000-2001 Crop Year 120 

Benjamin L. LeGendre, Harold Birkett, and Jeanie Stein 

Post-Freeze Performance of 16 Sugarcane Cultivars Following the 

December 31, 2000 Freeze Event in Florida 122 

J. M. Shine, R. A. Gilbert, and J. D. Miller 

Sugarcane Tissue Phosphorus Concentration as Affected by P Rates 

Applied to a Florida Histosol 122 

Y. Luo and Rosa M. Muchovej 

Sugarcane Root and Soil Microbial Responses to Intermittent Flooding 123 

D. R. Morris, B. Glaz, and S. Daroub 

Effect of Nitrogen Fertilizer Rates on Producer Economic Returns of 

Variety LCP 85-384 on a Heavy-Textured Soil in Louisiana 124 

W. B. Hallmark, G. J. Williams, G. L. Hawkins, and M. E. Selassi 

Production Trends of the Major Cane Sugar Producing Countries in the World 125 

Chen-Jian Hou 

Potential Effect of Yellow Leaf Syndrome on the Louisiana Sugarcane Industry 125 

M. P. Grisham, Y. B. Pan, W. H. White, 

M. A. Godshall, B. L. LeGendre, and J. C. Comstock 

Feeding Effects of Yellow Sugarcane Aphid on Sugarcane 126 

Gregg Nuessly and Matthew Hentz 

Relative Abundance and Diversity of Aphid Species Collected in Traps 

Adjacent to Sugarcane Fields in Florida 127 

R. N. Raid, G. S. Nuessly, and R. H. Cherry 

Fifteen Years of Recurrent Selection for Sugarcane Borer Resistance 128 

W. H. White, T. L. Tew, and J. D. Miller 



IV 



. 



Mexican Rice Borer on Sugarcane and Rice: 

Significance to Louisiana and Texas Industries 128 

M. O. Way, T. E. Reagan, and F. R. Posey 

Economically Optimal Crop Cycle Length for Major Sugarcane 

Varieties in Louisiana 129 

Michael E. Selassi and Janis Breaux 

Optimal Maturity of CP sugarcane Clones for Harvest Scheduling in Florida 130 

R. A. Gilbert, J. M. Shine, and J. D. Miller 

Protox Inhibitor Herbicide Effects on Pythium and Root Rot of Sugarcane 131 

J. H. Daugrois, J. W. Hoy, and J. L. Griffin 

Irrigation of Sugarcane on Clay in a High-Rainfall Environment 132 

Howard P. Viator 

Effect of Tissue Culture Method on Sugarcane Yield Components 132 

J. W. Hoy, K. P. Bischoff, K. A. Gravois, and S. B. Milligan 

Genes Expressed During Regeneration in Tissue Culture 133 

Robin Rowe, Candace Timple, and Sarah Lingle 

A Technique to Breed for Ratoon Stunting Disease in Sugarcane 134 

J. D. Miller, J. C. Comstock, P. Y. P. Tai, and B. Glaz 

Progress in the Development of Transgenic Disease-Resistant Sugarcane 134 

Z. Ying and M. J. Davis 

Potential Impact of DNA Marker Technology on Sugarcane Breeding 135 

Yong-Bao Pan 

In Vivo Viability of Sugarcane Pollen Stored at Ultra Low Temperature 

Following Preservation Treatments 135 

P. Y. P. Tai and J. D. Miller 

MANUFACTURING ABSTRACTS 137 

The Freeze of 2001-A "New Book is Written" 137 

John A. Fanjul 

The Breakage in Sugarcane Mill Rolls 137 

Jorge Okhuysen 

Material Balance and Equipment Requirements of a Typical Sugar Mill 137 

Eduardo Samour and William Easdale 



v 



Reducing Equipment Cost / Best Equipment management Practices 138 

Neal Hahn 

What You Should Learn from Your Chemical Supplier 138 

Stephen J. Clarke 

The Effect of Two Louisiana Soils on Cane Juice Quality 139 

Mary An Godshall, Scott S. Spear, and Richard M. Johnson 

Mill House Operation: Composition of Juice from Individual Mills 139 

Khalid Iqbal, Mary An Godshall, and Linda Andrews 

A New Polarimetric Method for the Analysis of Dextran and Sucrose 140 

Victoria Singleton 

Comparative Performance of Hot, Cold, and Intermediate Lime Clarification 

at Cora Texas Factory 140 

Gillian Eggleston, Blaine E. Ogier, and Adrian Monge 

Advance Report on the Use of Lime Saccharate in the Alcalinization 

of Sugarcane Juice 141 

Miguel Lama, Jr. and Raul O. Rodriguez 

The Re-Introduction of Formal Sugar Engineering Courses at LSU 141 

Peter W. Rein 

SAT Process for Production of White Sugar from Sugar Mills 142 

Chung Chi Chou 

The Biorefinery Concept 142 

Willem H. Kampen and Henry Njapau 

Evaporator Scale-Minimization with Electro-Coagulation 

and Improved Cleaning with Chelates 143 

Henry Njapau and Willem H. Kampen 

Evaporator Performance During Crop 2000-2001 at Cajun Sugar Factory 143 

Walter Hauck 

Mixed Juice Clarifier Distribution at Clewiston 144 

Mike Damms and Carlos Bernhardt 

Goats, Mice, and Dextran, The Road to a Monoclonal Antibody Test Kit 144 

Don F. Day, D. Sarkar, and J. Rauh 



VI 



. 



Comparing the Effects of Sulphur Dioxide on Model Sucrose 

and Cane Juice Systems 144 

L. S. Andrews and M. A. Godshall 

Advances in Technology of Boiler Water Treatment in 

Louisiana Sugarcane Mills 145 

Brent Weber, Brian Cochran, and Brian Kitchen 

Heat Transfer Devices 1 46 

Nell Swift 

IN MEMORIAM 147 

Enrique R. Arias 148 

S. J. P. Chilton 150 

Jack Dean 151 



vn 



Editorial Policy 152 

Rules for Preparing Papers to be Printed in the Journal of the 

American Society of Sugar Cane Technologists 154 

Guidelines for Preparing Papers for Journal of ASSCT 156 

Constitution of the American Society of Sugar Cane Technologists 157 

Author Index 164 



To order an extra copy of this volume, or a previous journal of American Society of Sugar Cane 
Technologists, write to: 

General Secretary-Treasurer 

American Society of Sugar Cane Technologists 

P.O. Box 25100 

Baton Rouge, LA 70894-5100 

Copies shipped within the USA are $10.00 (postage included) 

Copies shipped outside the USA are $10.00 (postage not included) 
Please add shipping costs as follows: 

Select method of delivery: 

surface mail (4-6 week delivery): add $5.00 per item 

air mail (7-10 day delivery): add $10 per item 



vni 



PRESIDENT'S MESSAGE 
FLORIDA DIVISION 

David G. Hall, Ph.D. 

Research Department 

United States Sugar Corporation 

P.O. Drawer 1207 

Clewiston, FL 33440 

On behalf of the Florida Division of the American Society of Sugar Cane Technologists, 
I bring the Louisiana Division greetings and thanks for hosting this year's annual joint meeting. 
To my Florida colleagues, I thank you for giving me the opportunity to serve as your president 
this year. It has been a privilege and an honor. 

Following our Society's tradition, I offer the following summary of the harvest season 
just completed in Florida. A total of 445,202 acres of cane was grown in Florida this past 
season, of which 427,156 acres were harvested for sugar. The first mill to begin grinding started 
on October 12, 2000, and the last mill to complete its crop finished on April 7, 2001. The 2000- 
2001 harvest season therefore spanned 177 days. On an individual mill basis, the shortest 
grinding season was 125 days and the longest was 172 days, with an average of 153 days across 
Florida's six mills. Two back-to-back hard freezes occurred during early January 2001, about 
mid-way through our harvest season. These freezes forced growers and mills to quickly 
prioritize the order in which to harvest the remaining fields. 

The 2000-2001 harvest season was our second largest over the last 20 years with respect 
to raw sugar produced (Figure 1). According to records compiled by the Florida Sugar Cane 
League for the 2000-2001 harvest season, Florida sugarcane growers and mills produced 
2,057,000 short tons raw value basis sugar and 106,500,000 gallons of 79.5° final molasses from 
17,320,000 gross tons of cane. The average sugar recovery per net ton of cane was 251.7 
pounds. The average cane yield for the harvest season was 40.6 gross tons of cane per acre with 
an average yield of 9,435 pounds of 96° sugar per acre. The January freezes reduced overall 
yield during the 2000-2001 harvest season and have hurt the yield potential of cane being grown 
for the 2001-2002 harvest season. 

As every ASSCT member knows, the price of raw sugar took a dive early during 2000, 
dropping to a record low of 16 cents per pound of raw sugar. Although prices have improved 
somewhat, economists forecast that we may never again see raw sugar above 20 cents per pound. 
A permanent, large drop in value may occur if the sugar policy in the Farm Bill is not revamped, 
if the North American Free Trade Agreement (NAFTA) problems with Mexico are not resolved, 
and if the importation of molasses stuffed with sucrose from Canada continues. 






Figure 1 . Some harvest figures for the Florida sugar industry 
(source: Florida Sugar Cane League). 



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If sugarcane growers in the United States find themselves living with a permanently 
depressed sugar market, we will have to scramble to find ways to enhance productivity and 
reduce production costs. In this event, a number of avenues could be explored for both the 
milling and agricultural sides of our industry. These avenues include increased automation and 
mechanization; decision-making computer models; modified agronomic systems; biotechnology; 
and enhanced biological systems. In the face of these challenges (and because I am an 
entomologist), I would like to share with you a few thoughts about pest control. An underlying 
stimulus for my comments was the following question: If sugar prices drop, how can we reduce 
losses to pests and simultaneously reduce our expenditures on pest control without sacrificing 
productivity? 

Pest problems in our sugarcane fields fluctuate from year-to-year and from decade-to- 
decade. This is true with respect to the specific pest species, the intensity of their damage, and 



. 



the regional spread of their infestations. Each of us knows the particular complex of pest species 
we need to be concerned about. Just because 1999 or 2000 was a light year with respect to 
infestations and damage by these pests does not mean they have gone away. 

Wireworms are currently the most important insect pests of sugarcane in Florida. 
Fortunately, chemical control tactics for wireworms are effective. Two granular 
organophosphates are labeled for wireworm control: ethoprop (Mocap) and phorate (Thimet). 
Unfortunately, due to factors such as the Food Quality Protection Act passed by Congress and 
supported by our industry, the sugarcane labels for these two pesticides could soon be in 
jeopardy, perhaps as early as this year. Our industry therefore needs to be searching for 
alternatives. I call upon our universities, the United States Department of Agriculture and our 
friends in the chemical industry to assist us with this. 

Florida sugarcane growers usually apply a pesticide for wireworm control once every 
three to five years when they plant a field unless they are planting after rice. The extent to which 
these insecticide applications are needed remains unclear. Growers would like to reduce their 
dependency and expenditures on insecticides for wireworm control in Florida, but they need help 
from scientists to do this. 

The lesser cornstalk borer continues annually to be a common pest in some Florida 
sugarcane fields. Management guidelines and emergency control tactics are currently not 
available for this pest in sugarcane. We could use help from our universities, the USDA and the 
chemical industry in coming up with an effective, affordable management program for the lesser 
cornstalk borer. 

The sugarcane borer is recognized as being a more important economic pest in Louisiana 
than in Florida. However, growers need to remember that the borer does cause economic losses 
in Florida sugarcane. Granted, the borer causes larger economic losses during some years than 
others, and outbreaks are more likely to occur in some areas than others. Some Florida growers 
lose money to the sugarcane borer, but they don't know it because they don't scout. While 
emergency control tactics are available for the borer, the cost of these in conjunction with the 
cost of a traditional scouting program may not be profitable during some years except in 
localized areas. Monitoring methods less expensive than traditional scouting might help with 
this problem. 

This is the new millennium, the age of new and constantly changing technologies, 
computers and computer modeling. Researchers working in sugarcane pest control should take 
greater advantage of these technologies. It is possible that growers and scouting companies 
could reduce pest management costs and achieve satisfactory levels of pest control using 
technologies such as remote sensing and computer modeling to predict pest outbreaks in 
conjunction with either traditional scouting methods or new, nontraditional monitoring methods. 

We have a good handle on control thresholds for two insects, the sugarcane borer and the 
sugarcane wireworm. We could use similar information for other insects pests such as the lesser 
cornstalk borer. Regardless of the particular insect pest, control thresholds need to be based not 
only on the value of pest damage but also on the costs of control and scouting. As the sugar 



price decreases, the economic thresholds for pests increase. At or below some market value of 
sugar, pests may no longer cause economic losses large enough to justify expenditures on 
frequent scouting and emergency control, particularly if the cost of scouting and control increase. 
This would elevate the need for less expensive approaches to detecting and managing losses to 
pests. The development and implementation of low-cost, low-input management strategies such 
as pest-resistant clones and biological control could become critical. 

Providing growers with sugarcane clones resistant to pests has been and will continue to 
be one of our most important strategies for pest control. This tactic could become essential for 
insect control if the market value of sugar drops. Louisiana has capitalized on plant resistance to 
the sugarcane borer, at least in the past. Economic damage by other pests—including the yellow 
sugarcane aphid and the lesser cornstalk borer—might be significantly reduced by growing 
varieties with even modest levels of pest resistance. Compromises may be necessary between 
yield and pest resistance. Conventional plant breeding programs need to be continued with 
increased emphasis on pest control. Although we do not know if or when we might be willing to 
market sugar from a genetically modified sugarcane, I believe we need to be developing 
transgenic clones with pest resistance and be prepared to implement them commercially. 

Finally, the importance continues in intercepting sugarcane pests new to the United 
States. Four pests new to Florida sugarcane have been found over the past 25 years: the 
sugarcane aphid Melanaphis sacchari; the sugarcane delphacid Perkinsiella saccharicida, the 
sugarcane lacebug Leptodictya tabida, and the weevil Metamasius hemipterus. I commend 
Federal and State agencies for their daily efforts to catch exotic pests being imported into 
Florida, though increased resources are needed for these agencies to accomplish the job. This 
critical function is becoming harder and harder as foreign travel increases and more airports and 
marine ports accept foreign travel. Quarantining foreign plant material imported for scientific 
reasons remains critical. Ornamental and horticultural plants being brought into the United 
States must be screened for sugarcane pests. We need to support continued funding of 
quarantine facilities such as the APHIS Federal quarantine center in Beltsville and ensure they 
use the most modern methods available to protect our industry. With respect to sugarcane pests 
already present in some areas of the United States, let's guard against spreading them to other 
areas. 

In summary, certain sugarcane pests continue to reduce the profitability of growing 
sugarcane in Florida and will continue doing so if management tactics are not fully developed 
and used. Non-chemical control methods are needed for sugarcane wireworms in Florida but, 
until these are available, we need to ensure chemical control methods remain available. If the 
market value of sugar decreases, expenditures on pest control will need to be reduced without 
decreasing productivity in order to maintain profits. This can only be accomplished through the 
development of new low cost, low input management tactics. The members of this society have 
the expertise to address these issues. In the meantime, let's hope no new insect pests of 
sugarcane find their way into the continental United States. 

I thank you for your attention and hope that this 31st Annual Meeting of the American Society of 
Sugar Cane Technologists is one of our most fruitful. 



- 



PRESIDENT'S MESSAGE 
LOUISIANA DIVISION 

Will E. LeGendre 

Jeanerette Sugar Co., Inc. 

P.O. Box 648 

Jeanerette, LA 70544 

On behalf of the members of the Louisiana Division of the American Society of Sugar Cane 
Technologists, I would like to express my most sincere welcome to the Florida division of the 
Society to the Thirty-First Annual Joint Meeting at New Orleans, Louisiana. I would also like to 
welcome all of the friends and family members of the Society and give thanks for their enduring 
support to what I consider the sweetest industry in the world. I will say with the highest degree of 
confidence that this year's meeting will engage prolific ideas and technology exchange to continually 
advance the U.S. Mainland sugarcane industry. 

In reading the production report for the year 2000 in Louisiana, an anticipated record year 
turned into only a good year even though the Louisiana industry produced the second largest crop 
in the state's history. Eighteen factories producing 1 ,565,848 tons of sugar, raw value, ground a total 
of 15,497,457 tons of cane. This is about 100,000 tons of sugar less than 1999 record production 
with sugar recovery also dropping from 1 0.40% in 1 999 to 1 0. 1 0% in 2000. Approximately 460,000 
acres of cane, a new state record, were harvested yielding a cane production of 33.7 tons per acre, 
down from 37 tons per acre the previous year. 

The decline in production from the previous year can be summed up into one word, 
DROUGHT. The winter months of 1 999 and 2000 were relatively dry and mild. This was ideal 
weather for the harvest season for 1999. Lay-by at the beginning of 2000 went very smoothly due 
to the dry conditions. With a record amount of acreage in cane and a mild winter behind them, the 
Louisiana sugarcane farmer was anxiously awaiting a record-shattering crop. The only two 
ingredients needed were rain and sunshine. The scorching sunshine did its job enthusiastically, while 
the timely rains took a long summer vacation. Drought conditions had carried over from 1 999 and 
put a choke hold on South Louisiana in 2000. For some areas, 30-inch deficits were noted by 
September. The cane was stressed and below the average height nearing the end of the growing 
season. The new prediction for the 2000 harvest was as much as 20% below the earlier estimates. 
Finally, the rains did come but in September, which brought about an abnormally late growth period. 
Tonnage looked as though it would recover but sucrose content was sacrificed because of the late 
growth spurt. Natural ripening was delayed and the response to the chemical ripener, glyphosate 
(Polado) was reduced especially during the early weeks of the harvest. Sucrose content made a 
valiant, come- from- behind charge to present a respectable yield of 10.10% by the end of the crop; 
however, sucrose levels took a nose dive following a killing freeze on December 20. There were 
small areas in the state that received some timely rainfall and benefitted from early applications of 
Polado, which in turn increased sucrose yield from the start of the crop and continued through the 
end. 

What's in the crystal ball for the Louisiana sugar industry? We must address the issues that 
are of major importance in the United States and in the world today. Look up the spot price on sugar 



today and it is virtually unchanged from twenty years ago. Who among us would not love to go out 
and buy a new F-150 for ten thousand dollars or experience unchanged grocery prices over the last 
two decades. Reflect back a mere five years ago and track the retail prices of food that contain 
substantial amounts of sugar. Breakfast cereal prices are up 4%, candies, cakes and cookies up 8%; 
and ice cream up 14%. Sadly, we are all well aware of the stagnant price of sugar during the same 
time period. The food manufacturers have the audacity to cry to the legislature that the price of sugar 
is hampering their profits. There are a number of factors that deter us from true economic supply 
and demand. The current U.S. trade agreements that allow importation of up to 1.5 million tons of 
sugar from forty-one countries can easily exceed the demand, thus suppress prices. In addition, the 
United States quota system never envisioned sugar being smuggled into the country by way of 
"stuffed molasses" or other desugarization products. It will be a tough battle, but it appears our 
friends in Washington can potentially resolve these and other issues to bring a stable and fair market 
value to the sugar we produce, especially if we resolve to add our voices to their efforts. 

What can be done here at home? Over the past ten years, our number one priority as 
producers was to increase volume. Put as much cane through our mills as possible and try to keep 
losses in sucrose to an acceptable Louisiana level. Various alterations were utilized to achieve 
record volumes, for instance, starting the harvest season earlier and finishing later, and acquiring 
larger process machinery. We were aware that these early starts could result in immature cane, low 
sugar content, and problems in the factory with starches and other impurities. But, with proper 
applications of chemical ripeners, we were able to bring this window forward to a degree. In 
addition, hardier varieties developed by the Louisiana Agricultural Experiment Station, USDA-ARS 
and the American Sugar Cane League, working cooperatively, were less vulnerable to marginal 
freezes over a short period of time, providing some peace of mind on the backside of harvest. 
During the 2000 harvest season, Mother Nature brought an early freeze in November that caused 
moderate damage to the northern parishes of the state, but surprisingly, spared most of the cane in 
the south. However, on December 20 the entire sugarcane belt experienced a killing freeze that 
ultimately, with subsequent freezes the first week of January, caused a dramatic reduction in 
recoverable sugar by the end of the harvest. It appears that we are willing to accept this inherent risk 
in an attempt to achieve higher volumes. Processing records tons of cane per day in an attempt to 
achieve over one million tones per season became the goal of many mills. 

In today's market, we must not lose sight of the potential degree of greater sugar loss when 
production is increased. Keeping our focus on efficiencies as well as higher volume is imperative. 
In 2000 we saw sugar prices plummet to a 30 year low while watching natural gas prices skyrocket. 
How can an industry thrive with its product price so low and fuel costs exorbitantly high? 
Fortunately, as we reach mid-2001, sugar prices have rebounded some and natural gas prices have 
dropped slightly. Nonetheless, our priority remains yielding the most sugar with a low operating cost 
and minimal losses. Research is an invaluable tool that can heighten our abilities and thus keep us 
competitive in the domestic market as well as globally. Scientists with the Louisiana Agricultural 
Experiment Station, USDA-ARA and the American Sugarcane League, working cooperatively, have 
in recent years developed outstanding, high-yielding varieties such as LC 85-384 and HoCP 85-845, 
which now occupy over 85 percent of our planted acreage. These new varieties, especially LCP 85- 
384, led to the industry switching from whole-stalk to combine harvesting; this revolutionized our 
harvesting methods and minimized field losses while increasing sugar per acre. Ongoing research 
in processing is needed now more than ever to develop new technology and improve old technology. 



Reducing labor requirements by implementing automation in various processes has been and will 
continue to be a positive result of ongoing research. 

The Louisiana sugar industry with its uniquely short grinding season can ill afford to 
experiment with pioneering, unproven, process equipment. Theoretically, this new equipment could 
improve efficiencies, but losses could be significant if the equipment fails and processing stops. 
There are high expectations for the resurgence of Audubon Sugar Institute to provide new product 
research and practical solutions. With our assistance and cooperation, Audubon is positioning itself 
once again to be the premier sugar institute in the world. Through its highly qualified staff, training 
and educating factory personnel is an integral part of ASI's commitment to the sugar industry and 
its future success. 

The time has come for the United States sugar industry to acknowledge that we can no longer 
survive on a razor thin profit margin. Increasing bureaucratic regulation, increased operational costs, 
decreasing qualified personnel, should motivate us as an industry to define and implement a course 
of action to move forward and create successes. Education, communication, cooperation, and 
motivation are key elements for any successful businesses facing future challenges. Throughout the 
history of the sugar industry challenges and obstacles have plagued us in one form or another but we 
have always persevered, overcome, and ultimately thrived. The resolution of problematic obstacles 
is relative to its place in history. No era exists in this industry that was without its tribulations. The 
technology and resources of these eras have historically resolved the problems of a particular time 
and more significantly forged the industry ahead to a higher level. 

Meetings such as this, where all facets of the industry come together and share ideas, studies, 
experiences, and technology is an integral part of the future success of our beloved industry. Sugar 
has been in the Legendre family for four generations; therefore, one could surmise that it is in my 
blood to have chosen such a profession. That may have some validity, although a deeper bond 
comes from the character of its associates. The willingness to help out a colleague with technical 
information, lend equipment and assistance to get neighboring factories back on line, is a unique 
quality found in no other industry. This fraternal relationship generates a passion within our industry 
that can only result in future prosperity for generations come. 






PEER 

REFEREED 

JOURNAL 

ARTICLES 



AGRICULTURAL 
SECTION 



.. 



Journal American Society of Sugarcane Technonogists, Vol. 22, 2002 

EFFECT OF SILICON-RICH SLAG AND LIME ON PHOSPHORUS LEACHING IN 

SANDY SOILS 



V.V. Matichenkov ***, B. Ande **, P. Ande **, D.V. Calvert * and 

E.A. Bocharnikova *** 
*Indian River Res. and Edu. Center, Fort Pierce, FL 34945-3 138; **Pro-Chem Chemical Company 
1000 S. Olive Avenue, West Palm Beach, FL 33401; ***Institute of Chemical, Physical and 
Biological Problems of Soil Science, Russian Academy of Sciences, Pushchino, Russia, 142292. 



ABSTRACT 

Phosphorus (P) contamination of natural surface and subsurface waters draining from 
agricultural soils is a persistent environmental and economic problem in Florida. A silicon (Si) soil 
amendment (Si-rich slag) and lime (CaC0 3 ) were compared to determine their effects on P leaching 
from cultivated Spodosols, Entisols, and Alfisols in soil columns and in greenhouse experiments 
with Bahiagrass (Paspalum notatum Fluigge) grown under various levels of P fertilization. The Si 
slag reduced P leaching considerably more than lime in all soils investigated. Lime transformed 
plant-available P into plant-unavailable forms, while Si slag maintained P in a plant-available form. 
In greenhouse experiments, plant growth responses were greater from Si slag-treated soil than from 
P fertilization. The Si slag improved P availability and had a positive effect on the development of 
the Bahiagrass root system. Application of Si slag to sandy soils could help reduce P leaching and 
the potential pollution of natural waters. 

INTRODUCTION 

The lack of soil nitrogen (N), phosphrous (P) and potassium (K) is a major factor limiting 
plant growth on native sandy soils in Florida. Commercial fertilizers containing these elements plus 
other macro- and microelements are used to overcome this limitation. 

Sandy soils often have low P retention due to: (1) the essential lack of alumino-silicates and 
metal-oxide clays in the albic E horizon (Harris, et. al, 1996), and (2) the presence of a seasonal 
shallow water table promoting lateral P transport within the E horizon (Mansell, et al., 1991). 
Frequent, heavy rainfall and widespread use of irrigation and drainage may lead to leaching of 20 
to 80% of added P (Campbell, et al., 1985; Sims, et al., 1998). This problem has ecological, 
economic and animal health consequences. Leached P promotes eutrophication of natural waters and 
P deficiency in plants (Richardson and Vaithiyanathan, 1995). Nutrient leaching can cause soil 
nutrient deficiencies, giving rise to the need for additional fertilization. The present method for 
reducing P leaching from sandy soils is through the use of limestone (Sims, et al., 1998). 
Unfortunately, lime transforms plant-available P into plant-unavailable forms (Lindsay, 1 979), which 
increases the need for P fertilization. 

Silicon-rich biogeochemically active substances (Si soil amendments) usually exhibit 
a high adsorption capacity for anions (Rochev, et al., 1980). They can adsorb mobile P and render 
it in a plant-available form (Matichenkov, et al., 1 997). Preliminary column experiments showed that 



Matichenkov et al.: Effect of Silica-rich Slag and Lime on P Leaching in Sandy Soils 

the application of various Si-rich materials reduced P leaching by 30 to 90% (Matichenkov et al., 
2000). 

The objective of this study was to compare the effect of Si slag (a finely processed calcium 
magnesium silica slag, PRO-CHEM Chemical Company, FL) with lime on P leaching from soils 
classified as cultivated Spodosols, Entisols, and Alfisols in column and greenhouse experiments. 

MATERIALS AND METHODS 

Soil samples representing two soil orders were collected at the University of Florida, Indian 
River Research and Education Center in Fort Pierce, FL. Soil samples were selected at the depth of 
0-20 cm from a cultivated Alfisol (Winder series, fine-loamy, siliceous, hyperthermic Typic 
Grossaqualfs) and a cultivated Spodosol (Ankona series, sandy, siliceous, hyperthermic, orstein 
Arenic Haplaquods). Sampling sites for the Alfisol and the Spodosol were under citrus groves. Soil 
samples representing a third soil order - a cultivated Entisol (Margate series, sandy, siliceous, 
hyperthermic Mollic Psammaquents) were collected in Hendry county in a commercial sugarcane 
field at the depth of 0-20 cm. 

The study involved both column and greenhouse experiments. The column experiment was 
used to model P leaching using Si slag and lime at 1 1 ha" 1 mixed with the different soils. The plastic 
column had a volume of 60 cm 3 and a diameter of 2.5 cm. Distilled water or a P-bearing solution 
(prepared from dissolving KH 2 P0 4 , 10 mg P L" 1 ) was added to the column at 6-8 mL h" 1 using a 
peristaltic pump. The percolate was collected in 20 mL intervals. Collected solutions were placed 
in a refrigerator at 4°C after adding a drop of chloroform for reduction of microbial activity. A total 
of 300 mL of solution was applied to each column. Each column was replicated three times and 
triplicate analyses were made on each liquid sample. After the leaching experiment was completed, 
the soils were dried at 65°C and passed through a 1-mm sieve. Triplicate soil and sand samples were 
analyzed for water-extractable and acid -extractable (0.1 M HC1) P. Phosphorus concentration was 
determined according to the method of Walsh and Beaton (1973). 

The greenhouse experiment was conducted with a cultivated Entisol. The soil was mixed 
with Si-rich slag or lime at the rates of and 10 1 ha" 1 . The P fertilizer (ground superphosphate) was 
applied at the rates of 0, 50 and 100 kg P ha" 1 . One kg of treated soil was then placed into plastic 
pots. Bahiagrass was used as a test plant (120 seeds per pot). Each variant had 2 replications. 
Irrigation was conducted with distilled water. After seeding and once a week thereafter, percolate 
samples were collected from the bottom of each pot and analyzed. The percolates and water and acid 
extracts of the soil were analyzed colorimetrically for P using a spectrophotometer at a wave length 
of 880 nm (Eaton, et. al., 1995). 

All data were subjected to a statistical analysis based on comparative methods using the 
P<0.05 value obtained from a multiple comparison test of variance and Duncan's coefficients (Pari, 
1967). 

RESULTS AND DISCUSSION 

Irrigation with distilled water in the column experiment was intended to represent the 
percolation of heavy rainfall (150-mm cm" 2 ). In the Entisol, the concentration of P in the percolate 

10 



Journal American Society of Sugarcane Technonogists, Vol. 22, 2002 

gradually decreased from 5.2 to 1.6 mg P L" 1 in the control, from 4.8 to 1.2 mg P L" 1 in the lime- 
treated soil, and from 1.5 to 0.5 mg P L" 1 in the Si-slag-treated soil (Figure 1). Irrigation with the P- 
bearing solution represented both heavy rainfall and P fertilization. The Entisol soil was gradually 
saturated with P (Figure 2). The concentration of P in the percolate solution increased from 4.5 to 
8.7 mg P L" 1 in the control, from 2.0 to 6.6 mg P L" 1 in the lime-treated soil and from 0.4 to 0.7 mg 
P L" 1 in the Si-slag-treated soil (Figure 2). 

In the Spodosol treated with Si slag or lime, the P concentration in the percolate was 
relatively stable under irrigation with distilled water (Figure 3), while that for the control sharply 
increased and then decreased. In the Spodosol irrigated with the P-bearing solution, the P in the 
percolate sharply increased both in the control and in the lime-treated soil, while the soil treated with 
Si slag showed only a small amount of P leaching (Figure 4). 

Phosphorus concentration in the percolate from the Alfisol under distilled water irrigation 
sharply increased from 0.5 to 0.9 mg P L" 1 in the control and from 0.3 to 0.6 mg P L" 1 in the lime- 
treated soil, but stayed relatively stable (from 0.3 to 0.4 mg P L" 1 ) in the Si-slag-treated soil (Figure 
5). Under irrigation with the P-bearing solution, P in the percolate gradually increased from 0.8 to 
9.7 mg P L" 1 in the control and from 0.7 to 4.5 mg P L" 1 in the lime-treated soil, but remained stable 
(from 0.6 to 0.7 mg P L" 1 ) for the Si-slag-treated soil (Figure 6). 

The column experiment demonstrated that Si slag adsorbed mobile P considerably better than 
lime and had appreciably less P leaching than the lime treatment in all soils investigated (Figures 1- 
6). This effect may have been caused by the action of several mechanisms. For example, Si slag 
contains Si, Al and Fe compounds and it is possible that both chemical and physical P adsorption 
mechanisms by Si slag were involved. 

Application of lime or Si slag along with P fertilizer (Figure 7, 8 and 9) influenced P leaching 
from the Entisol soil in the greenhouse experiment. Lime by itself slightly increased P leaching from 
the Entisol without P fertilization (Figure 7). Lime had its greatest effect in reducing P leaching from 
the Entisol treated with 50 kg P ha" 1 (Figure 8). However, Si slag showed a greater reduction in P 
leaching than lime at all treatment levels of P fertilization (Figure 7, 8 and 9). These data support the 
results of the column experiment (Figures 1-6) in that Si slag adsorbs considerably greater 
concentrations of mobile P than limestone. 

Addition of either P or Si slag to the soil increased the mass of shoots and roots of Bahiagrass 
(Table 1), whereas the lime treatment either had a negative or neutral effect on grass growth. A 
reduction of P concentration was shown in plants receiving the Si slag treatment (Table 2). For 
example, P concentration in Bahiagrass shoots decreased from 404 to 309 mg P lOOg" 1 , from 422 to 
239 mg P lOOg- 1 , and from 481 to 339 mg P lOOg' 1 in the treatments with 0, 50 and 100 kg P ha' 1 , 
respectively. Considering the significant effects of Si slag on the Bahiagrass mass (Table 1), the 
decreased plant P concentration may have been a dilution effect. The content of P in the shoots and 
the roots after 3 months of growth were examined to see if Si slag had increased P availability to the 
plants. Data on total P content per 100 plants confirmed this hypothesis (Table 3). The Si slag 
treatment increased the total amount of P in the shoots (except at 50 kg P ha" 1 ) and roots of 
Bahiagrass. Conversely, lime had the opposite effect on the shoots, but not roots of Bahiagrass. 



11 



Matichenkov et al.: Effect of Silica-rich Slag and Lime on P Leaching in Sandy Soils 

The concentration of P in Bahiagrass was higher with the control and lime treatments than 
with the Si slag treatment (Table 2). However, the content of P in both the shoots and roots was 
greater with the Si slag treatment than with the control or the lime treatment (Table 3). These data 
can be explained by considering the magnitude of increase in the biomass of Bahiagrass (Table 1). 
When compared with the control and lime treatments, Si slag application essentially doubled the 
biomass of shoots and increased the biomass of roots approximately 7 times. Although Si slag 
application resulted in a P dilution effect in the shoots and roots, the Bahiagrass absorbed more P 
with the Si slag treatment than with the control or the lime treatment. 

Data on water-extractable and acid-extractable P in the soil after the greenhouse experiment 
showed that the application of Si slag allowed P to remain in a plant-available form (Table 4). 
Liming resulted in a reduction in P leaching (Figure 8 and 9), but mobile P apparently was 
transformed into plant-unavailable P. Si slag also reduced mobile P leaching, probably by adsorption 
on the surface, but kept P in a plant-available form. Therefore, there appears to be a strong possibility 
that the application of Si slag to sandy soils could preserve natural waters from P contamination and 
improve P plant nutrition more efficiently than lime applications. 

ACNOWLEDGEMENTS 

This research was supported by a grant from the South Florida Water Management District 
and RECMLX PA Co. 



REFERENCES 

1. Campbell, K.L., J.S. Rogers, and D.R. Hensel. 1985. Drainage water quality from potato 
production. Trans. ASAE, 28:1798-1801. 

2. Eaton, A.D., L.S. Clesceri, and A.E. Greenberg (Ed). 1995. Standard Methods for 
Examination of Water and Wastewater, Am. Publ. Health As. 

3. Harris, W.G., R.D. Rhue, G. Kidder, R.B. Brown, and R. Littell. 1 996. Phosphorus retention 
as related to morphology of sandy coastal plain soil materials. Soil Sci. Soc. Am. J. 60: 1 5 1 3- 

1521 

4. Lindsay, W.L. 1979. Chemical Equilibria in Soil. John Wiley & Sons, New York. 
Mansell, R.S., S.A. Bloom, and B. Burgoa. 1991. Phosphorus transport with water flow in 
an acid, sandy soil. In Jacob B., and M.Y. Corapcioglu (Ed). Transport process in porous 
media. Kulwer Acad. Publ., Dorchester, the Netherlands, p.271-314. 

5. Mansell, R. S., S. A. Bloom, and B. Burqua. 1991 . Phosphorus transport with water flow in 
an acid , sandy soil. In Jacob, B. and M. Y. Corapcioglu (eds.). Transport process in porous 
media. Kulwer Acad. Publ., Dorchester, the Netherlands, pp. 271-314. 

6. Matichenkov, V.V., V.M. Dyakov, and E.A. Bocharnikova. 1997. The complex silicon- 
phosphate fertilizer. Russian patent, registration No. 97121 543. 

12 






> 



Journal American Society of Sugarcane Technonogists, Vol. 22, 2002 

7. Matichenkov, V.V., D.V. Calvert, G.H. Snyder, B. Whalen, and Y. Wan. 2000. Nutrients 
leaching reduction by Si-rich substances in the model experiments. In Proc. 7 th Inter. Conf. 
Wetland systems for water pollution control, Lake Buena Vista, Florida, Nov. 11-16, 2000, 
583-592. 

8. Pari, B. 1967. Basic Statistics. Doubleday & Co., Inc., Garden City, N.Y. p. 364. 

9. Richardson, C.J., and P. Vaithiyanathan. 1995. Phosphorus sorption characteristics of 
Everglades soils along a eutrophication gradient. Soil Sci. Soc. Am. J. 59:1782-1788. 

1 0. Rochev, V. A, R. V. Shveikina, G. A. Barsukova, and N.N. Popova. 1980. The effect of silica- 
gel on agrochemical soil properties and crop of agricultural plants. In Plant Nutrition and 
Programming of Agricultural Plants. Proceed. Sverdlovsky ACI, Perm, 60:61-68. 

11. Sims, J. T., Simard R.R., and B.C. Joern. 1998. Phosphorus loss in agricultural drainage: 
historical perspective and current research. J. Environ. Qual., 27:277-293. 

12. Walsh, L.M., and J.D. Beaton 1973. Soil testing and plant analysis. Soil Sci. Soc. Am. Inc., 
Madison, Wisconsin, USA. 



13 



Matichenkov et al.: Effect of Silica-rich Slag and Lime on P Leaching in Sandy Soils 

Table 1. The weight of fresh shoots and roots of Bahiagrass after growing 3 months in a 
greenhouse. 



Variant 


Without P Fertilizers 


50 kg P ha 1 as 
superphosphate 


100 kg P ha 1 as 
superphosphate 


Shoots 


Roots 


Shoots 


Roots 


Shoots 


Roots 






rage weight (g) for 1 plants 






Control 


0.57b 


0.17b 


0.84b 


0.29b 


0.89b 


0.37b 


Lime 


0.47c 


0.14b 


0.59c 


0.31b 


0.92b 


0.38b 


Si Slag 


1.12a 


0.97a 


1.14a 


1.14a 


1.48a 


1.37a 



Using Duncan's multiple range test, values within a column followed by the same letter are not 
statistically different (P<0.05). 



Table 2. The concentration of P in shoots and roots of Bahiagrass after growing 3 months in a 
greenhouse. 



Variant 


Without P Fertilizers 


50 kg P ha 1 as 
superphosphate 


100 kg P ha 1 as 
superphosphate 


Shoots 


Roots 


Shoots 


Roots 


Shoots 


Roots 








ma P 100 o- 1 












Control 


404a 


346b 


422a 


306b 


481a 


388a 


Lime 


418a 


450a 


360b 


362a 


432b 


378a 


Si Slag 


309b 


246c 


239c 


211c 


339c 


239b 



Using Duncan's multiple range test, values within a column followed by the same letter are not 
statistically different (PO.05). 



14 



Journal American Society of Sugarcane Technonogists, Vol. 22, 2002 

Table 3. Total content of P in shoots and roots of Bahiagrass after growing 3 months in a 
greenhouse. 



Variant 


Without P Fertilizers 


50 kg P ha 1 as 
superphosphate 


100 kg P ha 1 as 
superphosphate 


Shoots 


Roots 


Shoots 


Roots 


Shoots 


Roots 




moP 1 fM"> "lotito- 1 








Control 


2.30b 


0.59b 


3.57a 


0.91b 


4.28b 


1.43b 


Lime 


1.97c 


0.63b 


2.12c 


1.15b 


3.98c 


1.43b 


Si Slag 


3.48a 


2.40a 


2.73b 


2.41a 


5.03a 


3.27a 



Using Duncan's multiple range test, values within a column followed by the same letter are not 
statistically different (P<0.05). 



Table 4. The concentration of water- and acid-extractable P in Entisol after growing 
greenhouse study. 


Bahiagrass in 


Variant 


Without P Fertilizers 


50 kg P ha 1 as 
superphosphate 


100 kg P ha' 1 as 
superphosphate 


Water- 
Extractable 


Acid- 
Extractable 


Water- 
Extractable 


Acid- 
Extractable 


Water- 
Extractable 


Acid- 
Extractable 








.__ mcr P V 


g" 1 of soil 










nig r js. 


Original 
soil 


6.9a 


106a 


- 


- 


- 


- 


Control 


2.8b 


63b 


7.1b 


95b 


14.8a 


123a 


Lime 


3.6b 


51c 


7.8b 


85b 


13.5b 


114a 


Si Slag 


6.8a 


64b 


12.9a 


115a 


14.8a 


128a 



Using Duncan's multiple range test, values within a column followed by the same letter are not 
statistically different (P<0.05). 



15 



Matichenkov et al.: Effect of Silica-rich Slag and Lime on P Leaching in Sandy Soils 

Figure 1 . Effect of irrigation with distilled water on phosphorus concentration in a percolate solution 
from an Entisol treated with Si slag or limestone. Error bars indicate standard errors of the mean. 



6 

Oh •> 

B 4 



"o 
o 

PL-. 



3 
2 
1 












Control - - ■ Lime Si slag 






1^ 












* - ' ^^^^^^^^"5E""^^^^M^™ 




x> 






r i i i i i 







50 



100 



150 



200 



250 



300 



350 



Volume of water (mL/cm ) 



Figure 2. Effect of irrigation with a P-bearing solution on phosphorus concentration in a percolate 
solution from an Entisol treated with Si slag or limestone. Error bars indicate standard errors of the 



mean. 



12 

I 8 
s 6 

<D 
■»— > . 

J2 4 
"o 

^ 2 

CD Z. 

Oh 









_| Control - - - Lime Si slag 












S^^L^ ^ - " " " 






^ ...*-'• 


• 






1 1 1 1 I 



50 



100 



150 



200 



250 



300 



350 



Volume of solution (mL/cm ) 



16 



. 



Journal American Society of Sugarcane Technonogists, Vol. 22, 2002 



Figure 3 . Effect of irrigation with distilled water on phosphorus concentration in a percolate solution 
from a Spodosol treated with Si slag or limestone. Error bars indicate standard errors of the mean. 



0.8 

50.7 



§0.2 
I 0.1 







Control 



Lime Si slag 




J, -i. . 



- 1 



■ - - -I 







50 



100 



150 



200 



250 



300 



350 



Volume of water (mL/cm ) 



Figure 4. Effect of irrigation with a P-bearing solution on phosphorus concentration in a percolate 
solution from a Spodosol treated with Si slag or limestone. Error bars indicate standard errors of the 
mean. 








Control 



Lime Si slag 



50 



100 



150 



200 



250 



300 



350 



Volume of solution (mL/cm ) 



17 



Matichenkov et al.: Effect of Silica-rich Slag and Lime on P Leaching in Sandy Soils 

Figure 5. Effect of irrigation with distilled water on phosphorus concentration in a percolate from 
an Alfisol treated with Si slag or limestone. Error bars indicate standard error of the mean. 



1.2 

% 0.8 






0.6 



£ 0.4 



P 0.2 










Control ■ ■ ■ Lime 


Si slag 




"W^T T 




/ * — ^ T ^ 


/ 


!,■■■< ::r: 






"* ^ ^ 






B"^ 








— 1 I - ■ 1 _..-.... . . _ "■■ 1 



50 



100 



150 



200 



250 



300 



350 



Volume of water (mlVcm ) 



Figure 6. Effect of irrigation with a P-bearing solution on phosphorus concentration in a percolate 
solution from an Alfisol treated with Si slag or limestone. Error bars indicate standard errors of the 
mean. 



12 

as 



T3 ~ 

J3 4 
"o 

2 2 









Control - ■ ■ Lime Si slag 




_^-— —■ — "^ 


^^-^ 


/* 


/ ,..--••"" 


1 1 - ■ 1 1 1 







50 



100 



150 



200 



250 



300 



350 



Volume of solution (mL/cm ) 



18 



Journal American Society of Sugarcane Technonogists, Vol. 22, 2002 

Figure 7. Phosphorus concentration in a percolate solution from the greenhouse experiment with 
an Entisol. Error bars indicate standard errors of the mean. 



2.5 



a 



Oh 

"o 
o 

J-c 



1.5 



0.5 




fc-* .-... 


Control ■ ■ ■ Lime Si slag 




r M. \ ^ 






■*■, x - - *■ 






*•■. o . . - - ■ * „ .- i 


■"I i i 




i i i 







6 8 

Weeks 



10 



12 



14 



Figure 8. Phosphorus concentration in a percolate solution from the greenhouse experiment with 
an Entisol treated with P fertilizer (50 kg P/ha). Error bars indicate standard errors of the mean. 







Control + P 50 kg/ha 
Lime + P 50 kg/ha 
Sislag + P 50 kg/ha 



6 



8 



10 



12 



Weeks 




14 



19 






Matichenkov et al.: Effect of Silica-rich Slag and Lime on P Leaching in Sandy Soils 

Figure 9. Phosphorus concentration in a percolate solution from the greenhouse experiment with 
an Entisol treated with P fertilizer (100 kg/ha). Error bars indicate standard errors of the mean. 



^35 

Ph 

^25 
U 15 

lio 

o 

(D 5 










Control + P 100 kg/ha 
Lime + P 100 kg/ha 
Si slag + P 100 kg/ha 



4 



6 8 

Weeks 



■ ■ tm ■ I * 

10 



12 



14 



20 



. 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

SILICON AS A BENEFICIAL ELEMENT FOR SUGARCANE 

V.V. Matichenkov and D.V. Calvert 

Indian River Res. and Edu. Center, Fort Pierce, FL 34945-3138 

ABSTRACT 

A number of field and greenhouse studies have demonstrated that silicon (Si) is an important 
beneficial element for sugarcane (Saccharum officinarum L.). Effective management practices utilize 
Si fertilization on soils deficient in plant-available Si. Thus far, knowledge of the direct effects of 
Si fertilizers on sugarcane has not advanced as rapidly as for rice. Silica concentration in cultivated 
plants ranges from 0.3 to 8.4 %. A range of 210-224 million tons of Si or 70-800 kg ha" 1 of plant- 
available Si is harvested with the sugarcane crop from arable soils annually. Crop removal of Si by 
sugarcane exceeds those of the macronutrients N, P, and K. Usually the concentration of Si in 
sugarcane leaves varies from 0.1 to 3.2%. Higher yield of sugarcane is associated with higher 
concentration of Si in the leaves. Field and greenhouse experiments conducted in the USA (Florida 
and Hawaii) and Mauritius demonstrated that application of Si fertilizers had a positive effect on the 
disease-, pest- and frost-resistance of sugarcane. It was shown that sugarcane productivity increased 
from 17 to 30 %, whereas production of sugar rose from 23 to 58% with increasing Si fertilization. 
One of the most important functions of Si was the stimulation of the plant's defense abilities against 
abiotic and biotic stresses. Literature data demonstrated that improved sugarcane nutrition brought 
about by fertilization with Si was shown to reinforce the plant's protection properties against leaf 
freckle, sugarcane rust, and sugarcane ringspot. In addition, Si fertilization has a more positive effect 
than liming on the chemical and physical properties of the soil. 

INTRODUCTION 

Beginning in 1840, numerous laboratory, greenhouse and field experiments showed 
sustainable benefits of Si fertilization for rice (Otyza sativa L.), barley {Hordeum vulgare L.), wheat 
(Triticum vulgare Vil), corn (Zea mays L.), sugarcane, cucumber (Cucumus sativa L), tomato 
(Lycopersicon esculentum Mill), citrus {Citrus taitentis Risso) and other crops (Epstein, 1999; 
Liebig, 1840; Matichenkov et al., 1999; Savant et al., 1997). Unfortunately, the present opinion 
about Si being an inert element is prevalent in plant physiology and agriculture despite the fact that 
Si is a biogeochemically active element and that Si fertilization has significant effects on crop 
production, soil fertility, and environmental quality (Epstein, 1 999; Matichenkov and Bocharnikova, 
2000; Voronkov et al., 1978). 

RESULTS AND DISCUSSION 

Silicon in the Soil-Plant System. 

Silicon is the most abundant element in the earth's crust after oxygen: 200 to 350 g Si kg" 1 
in clay soils and 450 to 480 g Si kg" 1 in sandy soils (Kovda, 1973). It is the current opinion that Si 
is an inert element and cannot play an important role in the biological and chemical processes. 
However many Si compounds are not inert. Silicon can form numerous compounds with high 

21 



Matichenkov and Calvert: Silicon as a Beneficial Element for Sugarcane 

chemical and biochemical activities. Four elements, carbon (C), aluminum (Al), phosphorus (P), and 
germanium (Ge) surround Si in the Periodic Table of Elements. The properties of Si are somewhat 
similar to those of the surrounding elements. Only Si can form stable polymers similar to C (Her, 
1979). Silicon is similar to Al in that it can act similarly in formatting minerals (Sokolova, 1985). 
Silicon can replace P in DNA (Voronkov et al., 1 978). Also, Si has similar metallic properties to Ge 
(Her, 1979). Usually plants absorb Si more than other elements (Savant et al., 1997). These 
properties in turn determine silicon's effect on soil fertility and plants. 

Soils generally contain from 5 to 40% Si (Kovda, 1973). The main portions of soil Si-rich 
compounds are represented by quartz or crystalline silicates, which are inert. In many respects, these 
silicates form the skeleton of the soil. The physically and chemically active Si substances in the soil 
are represented by soluble and weakly adsorbed monosilicic acids, polysilicic acids, and 
organosilicon compounds (Matichenkov and Ammosova, 1996). These forms are interchangeable 
with each other as well as with other crystalline minerals and living organisms (soil microorganisms 
and plants). Monosilicic acid is the center of these interactions and transformations. Monosilicic acid 
is a product of Si-rich mineral dissolution (Lindsay, 1979). The soluble and weakly adsorbed 
monosilicic acids are absorbed by plants and microorganisms (Yoshida, 1 975). They also control soil 
chemical and biological properties (P, Al, Fe, Mn and heavy metal mobility, microbial activity, 
stability of soil organic matter) and the formation of polysilicic acids and secondary minerals in the 
soil (Matichenkov et al., 1995; Sokolova, 1985). Plants and microorganisms can absorb only 
monosilicic acid (Yoshida, 1975). Polysilicic acid has a significant effect on soil texture, water 
holding capacity, adsorption capacity, and soil erosion stability (Matichenkov et al., 1995). 

Using data from the literature on Si removal by different cultivated plants (Reimers, 1 990; 
Bazilevish et. al., 1975) and from the FAO database on world crop production (FAO Internet 
Database, 1998), it was calculated that 210-224 million tons of plant-available Si is removed from 
arable soils annually. Harvesting cultivated plants usually results in Si removal from the soil. In most 
cases much more Si is removed than other elements (Savant et al., 1997). For example, potatoes 
remove 50 to 70 kg Si ha" 1 . Various cereals remove 100 to 300 kg Si ha" 1 (Bazilevich et al, 1975). 
Sugarcane removes more Si than other cultivated plants. Sugarcane removes 500 to 700 kg Si ha" 1 
(Anderson, 1991). At the same time sugarcane absorbs 40 to 80 kg P ha" 1 , 100 to 300 kg K ha" 1 , and 
50 to 500 kg N ha" 1 (Anderson, 1991). 

Studies have shown that while other plant-available elements were restored by fertilization, 
Si was not. Soil fertility degradation started because the reduction of monosilicic acid concentration 
in the soil initiated decomposition of secondary minerals that control numerous soil properties 
(Karmin, 1986; Marsan and Torrent, 1989). A second negative effect of reduced monosilicic acid 
concentration in the soil is decreased plant disease and pest resistance (Epstein, 1999; Matichenkov 
et al., 1999; Savant et al., 1997). 

In recent years we tested the concentration of monosilicic acid, polysilicic acids, and acid- 
extractable Si in Florida and Louisiana soils (Matichenkov and Snyder, 1996; Matichenkov et al., 
1997; Matichenkov et al., 2000). The concentration of monosilicic and polysilicic acids in the soil 
can be analyzed only from fresh soil samples (Matichenkov et al., 1997). The concentration of acid- 



22 



-> 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

extractable Si is positively correlated with biochemically active Si or sources of plant-available Si 
in the soil (Barsykova and Rochev, 1979). 

Selected data on the concentration of monosilicic acid, polysilicic acid, and acid-extractable 
Si in Histosols, Spodosols, Entisols and Mollisols are presented in Table 1. The lowest 
concentrations of soluble and biochemically active Si substances are found in the sandy soil (Table 
1). Cultivation can increase the concentration of monosilicic acids, probably because plant residuals 
(especially burned sugarcane leaves) are not removed from the soil. Even so, the concentration of 
soluble and biochemically active Si-rich compounds remains critically low. 

The concentration of monosilicic acid in a native Histosol is usually characterized as being 
medium to high. The sources of plant-available Si are extremely critical (Table 1), and cultivation 
results in sharply reduced monosilicic acid levels in the soil. In commercial rice and sugarcane 
production in the Everglades Agricultural Area, growers usually use Si soil amendments for 
increased crop production and quality (Datnoff et al., 1997, Savant et al., 1997). Sugarcane usually 
is grown after rice. The application of Si fertilizer has beneficial effects on both rice and sugarcane 
(Savant et al., 1999). The concentration of monosilicic acid, polysilicic acid, and acid-extractable 
Si increased with cultivation (Table 1). The most dramatic increase was observed for acid-extractable 
Si. This parameter determines the amount of biogeochemically active Si and is a potential source for 
plant-available Si (Barsykova and Rochev 1979). Native Histosols have extremely low levels of 
biogeochemically active or plant-available Si. On the other hand cultivated Histosols have medium 
to high level of monosilicic acid or plant-available Si (Table 1). 

The native soils from Louisiana were characterized by a high concentration of soluble and 
biochemically active Si (Table 1). High levels of biogeochemically active Si were found in 
accumulative alluvial soils (Kovda, 1973). Louisiana soils were collected in the Mississippi delta 
and were formed under alluvial accumulative processes. The long period of cultivation of these soils 
resulted in the decrease of monosilicic acid and acid-extractable Si (Table 1). Most likely this is a 
result of monosilicic acid absorption by cultivated plants rather than leaching, because monosilicic 
acid is characterized by a low capacity to move down the soil profile (Matichenkov and Snyder, 
1996). However, the content of polysilicic acids increased, which is probably associated with 
degradation of soil minerals (Matichenkov et al., 1995; Her, 1979). The decrease of acid-extractable 
Si supports this conclusion. As a result of agricultural activity, the concentration of plant-available 
Si was decreased and soil fertility was degraded. 

These data demonstrate that Si fertilization is needed for all four soils under investigation 
to assure adequate Si nutrition of sugarcane and to optimize the fertility of these soils. 

Effect of Si on Sugarcane 

Silicon fertilizers influence plants in two ways: (1) the indirect influence on soil fertility, and 
(2) the direct effect on the plant. Most investigations of monosilicic acid effects on soil properties 

23 



Matichenkov and Calvert: Silicon as a Beneficial Element for Sugarcane 

concern their interaction with soil phosphates (Matichenkov and Ammosova, 1 996). Silicon fertilizer 
applied into the soil initiates two processes. The first process involves increases in the concentration 
of monosilicic acids resulting in the transformation of slightly soluble phosphates into plant- 
available phosphates (Lindsay, 1979; Matichenkov, 1990). The equations for these reactions are as 
follows: 

CaHP0 4 + Si(OH) 4 = CaSi0 3 + H 2 + H 3 P0 4 
2A1(H 2 P0 4 ) 3 + 2Si(OH) 4 + 5H + = Al 2 Si 2 5 + 5H 3 P0 4 + 5H 2 
2FeP0 4 + Si(OH) 4 + 2H + = Fe 2 Si0 4 + 2H 3 P0 4 

Secondly, Si fertilizer adsorbs P, thereby decreasing P leaching by 40-90 % (Matichenkov et al., 
2000). It is noteworthy that adsorbed P is kept in a plant-available form. 

Silicon fertilizers are usually neutral to slightly alkaline (Lindsay, 1 979). Soluble Si reduces 
Al toxicity because monosilicic acid reacts with mobile Al and forms slightly soluble 
aluminosilicates (Lumsdon and Farmer, 1995). This means that Si amendments may be used for 
improving the chemical properties of acid soils. Numerous field experiments have demonstrated that 
Si fertilization has more influence on plant growth on acid soils than liming (Ayres, 1 966; Fox et al., 
1967). Silicon fertilizer can increase plant resistance to heavy metals (Epstein 1999) and toxic 
hydrocarbons (Bocharnikova et al., 1999). Both effects of Si fertilizer appear to occur through 
optimization of soil properties and the direct effect on soil microorganisms. Our earlier investigation 
demonstrated that soil treatment with Si-rich materials increased both water-holding capacity and 
soil adsorption capacity for ions (Matichenkov and Bocharnikova, 2000). 

The direct effect of Si fertilizer on plants is primarily manifested in increasing disease and 
pest resistance. Data in the literature showed that Si fertilization increased the resistance of 
sugarcane to sugarcane rust (Dean and Todd, 1979), leaf freckle (Fox et al., 1967), sugarcane 
ringspot (Raid et al., 1991), leaf disorder (Clements, 1965), and stalk and stem borers (Edward et 
al., 1985; Meyer and Keeping, 1999). Except for biotic stresses such as pests and plant diseases, Si 
fertilization increased sugarcane resistance to abiotic stresses such as soil water shortage, cold 
temperature, UV-B radiation, and for Fe, Al and Mn toxicities (Savant et al., 1999). 

The field experiments in Hawaii, Mauritius and Florida demonstrated high response of 
sugarcane to Si fertilizer (Table 2). It is important to note that Si fertilizer increased not only the 
productivity of cane but also the concentration of sugar in the plants as well (Table 2). It is probable 
that Si has a direct effect on biochemical processes in sugarcane that are similar to responses 
observed for sugar beet (Liebig, 1840). 

CONCLUSIONS 

Soils used for sugarcane in Florida and Louisiana usually have low concentrations of plant- 
available Si and biogeochemically active Si. The removal of Si by sugarcane initiated soil fertility 

24 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

degradation. Cultivated plants tend to have Si deficiency. The application of Si in soil amendments 
is needed for both optimized soil fertility and improved plant nutrition. The field experiments in 
Florida, Hawaii, and Mauritius demonstrated the highly beneficial effects of Si fertilizers. 

REFERENCES 

1. Anderson, D.L.. 1991. Soil and leaf nutrient interactions following application of calcium 
silicate slag to sugarcane. Fertilizer Research 30:9-18. 

2. Ayres, A.S.. 1966. Calcium silicate slag as a growth stimulator for sugarcane on low silicon 
soils. Soil Sci. 101(3):216-227. 

3. Barsykova, A.G., and V.A. Rochev. 1979. The influence of silica-gel-rich fertilizers on 
mobile silicic acid in the soil and on available Si for plants. In The control and management 
of the content of the macro- and the microelements in media. Ural region, Proceedings of 
Sverdlovsky ACI 54:84-88. 

4. Bazilevich, N.I., L.E. Rodin, and N.N Rozov. 1975. The biological productivity and cycle 
of chemical elements in plant associations. In: Bazilevich N.I. (Ed) Biosphere Resource, 
ser.l., Leningrad, pp.5-33. 

5. Bocharnikova,E.A., V.V.MatichenkovandG.H. Snyder. 1999. A technology for restoration 
of hydrocarbon polluted soils. Proceed. 31 st Mid- Atlantic Industrial and Hazardous Waste 
Conference, June, 1999:166-174. 

6. Clements, H.F. 1965. Effects of silicate on the growth and freckle of sugarcane in Hawaii. 
Proc. Int. Soc. Sugar Cane Technol. 12:197-215. 

7. Datnoff, E.L., C.W. Deren, and G.H. Snyder. 1997. Silicon fertilization for disease 
management of rice in Florida. Crop Protection 16(6):525-531. 

8. Dean, J.L., and E.H. Todd. 1979. Sugarcane rust in Florida. Sugar Journal 42:10. 

9. Edward, S.H., L.H. Allen, and G.J. Gascho. 1985. Influence of UV-B radiation and soluble 
silicates on the growth and nutrient concentration of sugarcane. Soil Crop Sci. Soc. Fla. 
44:134-141. 

10. Epstein, E. 1999. The discovery of the essential elements. Discoveries in plant biology, v. 3. 
S.D.Kung and S.F. Yang (ed), World Scientific Publishing, Singapore. 

1 1 . FAO. 1 998. World Agricultural Center, FAOSTAT agricultural statistic data-base gateway. 



25 



Matichenkov and Calvert: Silicon as a Beneficial Element for Sugarcane 

12. Fox, R.L., J.A. Silva, O.R. Younge, D.L. Plucknett, and G.D. Sherman. 1967. Soil and plant 
silicon and silicate response by sugar cane. Soil Sci. Soc. Amer. 31 :775-779. 

13. Her, R.K. 1979. The chemistry of silica. Wiley, New York. 

14. Karmin, Z. 1986. Formation of ferrihydrite by inhibition of grim rust structures in the 
presence of silicon. Soil Sci. Soc. Amer. J., 50(l):247-254. 

15. Kovda, V.A. 1973. The bases of learning about soils. Moscow: Nayka, 2 v. 



16. Liebig, J. Von. 1840. Organic chemistry in its application to agriculture and physiology. 
Ed. from the manuscript of the author by Lyon Playfair. Taylor and Walton, London. 

17. Lindsay, W.L. 1979. Chemical equilibria in soil. John Wiley & Sons, New York 

18. Lumsdon, D.G., and V.C. Farmer. 1995. Solubility characteristics of proto-imogolite sols: 
how silicic acid can detoxify aluminium solutions. European Soil Sci., 46:179-186. 

19. Marsan, F. A., and J. Torrent. 1 989. Fragipan bonding by silica and iron oxides in a soil from 
northwestren Italy. Soil Sci. Soc. Amer. J., 53(4): 1140-1 145. 

20. Matichenkov, V.V. 1990. Amorphous oxide of silicon in soddy podzolic soil and its 
influence on plants. Author reference of Can. Diss., Moscow State University. 

21. Matichenkov, V.V., D.L. Pinsky, and E.A. Bocharnikova. 1995. Influence of mechanical 
compaction of soils on the state and form of available silicon. Eurasian Soil Science 
27(12):58-67. 

22. Matichenkov, V. V., and J.M. Ammosova. 1 996. Effect of amorphous silica on soil properties 
of a sod-podzolic soil. Eurasian Soil Science 28(10):87-99. 

23. Matichenkov, V.V. and G.H. Snyder. 1996. The mobile silicon compounds in some South 
Florida soils. Eurasian Soil Science 12:1165-1173. 

24. Matichenkov, V.V., Ya. M. Ammosova, and E.A. Bocharnikova. 1997. The method for 
determination of plant available silica in soil. Agrochemistry 1:76-84. 

25. Matichenkov, V.V., D.V. Calvert, and G.H. Snyder. 1999. Silicon fertilizers for citrus in 
Florida. Proc. Fla. State Hort. Soc. 112:5-8. 






26 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

26. Matichenkov, V.V., E. A. Bocharnikova, D.V. Calvert, and G.H. Snyder. 2000. Comparison 
study of soil silicon status in sandy soils of south Florida. Soil Crop Sci. Florida Proc. 
59:132-137. 

27. Matichenkov, V.V., D.V. Calvert, G.H. Snyder, B. Whalen, and Y. Wan. 2000. Nutrients 
leaching reduction by Si-rich substances in the model experiments. In Proc. 7 th Inter, conf. 
wetland systems for water pollution control, Lake Buena Vista, Florida, Nov. 11-16, 2000, 
583-592. 

28. Matichenkov, V.V. and E. A. Bocharnikova. 2000. The relationship of silicon to soil physical 
and chemical properties. Proc. Inter. Conf. Silicon in agriculture, in press. 

29. Meyer, J. H. and M. Keeping. 1999. Past, present and future silicon research in the South 
African sugar industry. In Silicon in agriculture, Program agenda and abstracts, Sept. 26-30, 
1999, Fort Lauderdale, Florida, USA, 10. 

30. Raid, R.N., D.L. Anderson, and M.F. Ulloa. 1991 . Influence of cultivar and soil amendment 
with calcium silicate slag on foliar disease development and yield of sugarcane. Florida 
Agricultural Experimental Station Journal Ser. N R-01689. 

31. Reimers, N.F.. 1990. Natural uses. Dictionary-reference book, Moscow, Misl. 

32. Savant, N.K., G.H. Snyder, and L.E. Datnoff. 1 997. Silicon management and sustainable rice 
production. Advances in Agronomy 58:151-199. 

33. Savant, N.K., G.H. Korndorfer, L.E.Datnoff, and G.H. Snyder. 1999. Silicon nutrition and 
sugarcane production: a review. J. Plant Nutr. 22(12):1853-1903. 

34. Silva, J. A. 1969. The role of research in sugar production. Hawaiian Sugar Technologists 
Association: 1969 Report. 

3 5 . Sokolova, T. A. . 1 985 . The clay minerals in the humid regions of US SR. Novosibirsk, Nayka. 

36. Voronkov, M.G., G.I. Zelchan, and A.Y. Lykevic. 1978. Silicon and life. Riga, Zinatne. 

37. Yoshida, S., 1975. The physiology of silicon in rice. Tech. Bull, n.25., Food Fert. Tech. 
Centr., Taipei, Taiwan. 



27 



Matichenkov and Calvert: Silicon as a Beneficial Element for Sugarcane 

Table 1. Concentrations of monosilicic acid, polysilicic acid and acid-extractable Si in Histosols, 
Spodosols, Entisols, and Mollisols (mg Si kg" 1 of soil). 



Soil 


Soluble silicon 


Acid-extractable 
silicon 


Monosilicic acid 


Polysilicic acid 


Histosol (Florida, Lauderhill series) 


Native 


24.3-46.5 


0-0.8 


15-45 


Cultivated without 
silica fertilizers 


13.4-32.4 


1.5-2.7 


97-127 


Cultivated with silica 
fertilizers 


15.3-96.2 


1.5-23.4 


93-548 


Spodosol (Florida,Ancona series) 


Native 


1.4-2.3 


2.4-12.7 


45-75 


Cultivated 


2.3-6.1 


1.7-2.4 


42-57 


Entisol (Louisiana, Mhoon series) 


Native 


19.1-20.3 


27.3-29.8 


319-325 


Cultivated 


11.5-14.2 


88.9-117.5 


279-319 


Mollisol (Louisiana, Iberia series) 


Native 


23.2-23.8 


40.0-58.2 


294-415 


Cultivated 


12.3-19.5 


56.3-116.5 


171-298 



28 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 2. The effect of location, soil type, source and rate of fertilizer application on yield of 
sugarcane and sugar. 



Soil 


Si 
fertilizer 


Rate, 
ton/ha 


Limestone 
or fertilizer 


Sugar 


Cane 


Reference 


t/ha 


% 


t/ha 


% 


Aluminos 

humic 

Latosol, 

Mauritius 


Electric 

furnace 

slag 





NPK 


27.4 


100 


266.7 


100 


Ayres, 1966 





NPK + 

lime 
4.94t/ha 


26.7 


97.4 


256.8 


96.3 


6.177 


NPK 


33.8 


123.4 


313.7 


117.6 


Humic 

Latosol, 

Hawaii 


TVA 
slag 





P 0.28t/ha 


23.4 


100 


253 


100 


Fox et al., 
1967 





Lime 4.5 
t/ha + P 
1.112t/ha 


20.7 


88.5 


262 


103.5 


4.5 


P 0.28t/ha 


31.6 


135.0 


327 


129.2 


4.5 


P1.112t/ha 


32.7 


139.7 


338 


133.5 


Humic 

Latosol, 

Hawaii 


Calcium 
silicate 





- 


- 


- 


131 


100 


Silva, 1969 


0.83 


- 


- 


- 


151 


115.3 


1.66 


- 


- 


- 


166 


126.7 


Histosol, 
Florida 


Calcium 

silicate 

slag 





- 


12.5 


100 


126 


100 


Raid et al., 
1991 





P 


18.1 


144.8 


150 


119.0 


6.7 


- 


15.8 


126.4 


156 


123.8 


6.7 


P 


23.8 


190.4 


194 


153.9 



29 



Selassi et al.: Maximizing Economic Returns from Sugarcane Harvesting through Optimal Harvest Scheduling 

MAXIMIZING ECONOMIC RETURNS FROM SUGARCANE PRODUCTION 
THROUGH OPTIMAL HARVEST SCHEDULING 



Michael E. Salassi 

Department of Agricultural Economics and Agribusiness 

Louisiana Agricultural Experiment Station 

LSU Agricultural Center, Baton Rouge, LA 70803 

Lonnie P. Champagne 

Louisiana Sugar Cane Products Inc. 
Baldwin, LA 70514 

Benjamin L. Legendre 

Division of Plant Science 

Louisiana Cooperative Extension Service 

LSU Agricultural Center, Baton Rouge, LA 70803 

ABSTRACT 

The long-term viability of the sugar industry depends upon finding ways to produce sugar 
more economically through production management decisions which can reduce production costs 
or increase returns. Harvest scheduling is one such practice which has a direct impact on net farm 
returns. Sugarcane cultivars have distinct sucrose maturation curves, which may vary up or down 
from year to year depending upon weather and other factors. A study was conducted on a 
commercial sugarcane farm to predict sugar per acre across the harvest season and to develop a 
programming model which could determine the order of harvest of fields on the farm which would 
maximize total sugar produced and net returns above harvest costs. Optimal adjustment of harvest 
of individual fields resulted in increased sugar yield per acre and total farm net returns. 

INTRODUCTION 

As a sugarcane plant matures throughout the growing season, the amount of sucrose in the 
cane increases. Most of this sucrose production occurs when the plant is fully mature and begins to 
ripen. Several studies have developed models to predict the sucrose level in sugarcane. Crane et al. 
(1982) developed a stubble replacement decision model for Florida sugarcane producers. They 
reported that sugar accumulation is a function of both sucrose accumulation and vegetative growth. 
The study suggested that the accumulation of sugar may be approximated as a quadratic function of 
time. Chang (1995), in research on Taiwanese sugarcane cultivars, suggested that individual 
cultivars have distinct sucrose maturation curves with different peak levels. The study concluded 
that the sugar content of a cultivar could be predicted as a function of time with reasonable accuracy 
and that the within-season trend of sucrose accumulation follows a second order curve. 

During the harvest season, second stubble and older stubble fields are usually harvested first, 
followed by more recently planted fields, first stubble and then plantcane. Within this general order 
of crop harvest, producers attempt to estimate the sugar content of cane in the field in order to 

30 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

harvest fields at a point where the sugar content in the cane is at or near a maximum. If individual 
sugarcane cultivars have distinct sucrose maturation curves, which may vary up or down from year 
to year depending upon weather and other factors, then the sugar content of individual fields could 
be incorporated into a model which would determine an optimal order of harvest for all fields on a 
particular farm, which would maximize total sugar produced (or total net returns received) on the 
farm. 

Applications of crop harvest scheduling models utilizing some type of operations research 
procedure are most common in the timber industry. Most of these applications involve the use of 
either linear programming or simulation models. Recent studies have investigated the use of Monte 
Carlo integer programming (Nelson et al., 1991; Daust and Nelson, 1993), bayesian concepts (Van 
Deusen, 1996), and tabu search procedures (Brumelle et al., 1998). Several studies have developed 
crop growth models to predict the harvest date of agricultural crops (Lass et al.,1993; Malezieux, 
1 994; Wolf, 1 986). However, most of these studies utilize optimal harvest decision rules based upon 
agronomic characteristics of the crop rather than economic principles. 

Several studies have addressed various aspects of sugarcane productivity and harvest 
operations. Two studies have evaluated the economics of sugarcane stubble crop replacement in 
Florida (Crane et al., 1982) and Louisiana (Salassi and Milligan, 1997). These studies evaluated the 
optimal crop cycle length by comparing annualized future net returns from replanting to estimated 
returns from extending the current crop cycle for another year. Semenzato (1995) developed a 
simulation algorithm for scheduling sugarcane harvest operations at the individual farm level in such 
a way that the lapse of time between the end of burning and processing is minimized. The model 
calculated the maximum size of a field which could be harvested and have all of its cane processed 
within a specified period of time. This study focused on farm size and equipment availability in 
order to efficiently utilize limited resources in a timely manner. A recent study in Australia did 
determine optimal sugarcane harvest schedules which maximized net returns using mathematical 
programming procedures (Higgins et al., 1998; Muchow et al, 1998). However, the modeling 
framework in this study encompassed many farms within a production region over a multi-year 
harvest period. Furthermore, the smallest unit of time within the harvest scheduling model was one 
month. 

The purpose of this study was to develop a methodology for the incorporation of within- 
season sucrose accumulation in sugarcane into an optimal single-season, daily harvest scheduling 
model at the individual farm level. The objective of the general modeling procedure was to capture 
the dynamic effect of sucrose accumulation during the growing season and to utilize this 
information, within a mathematical program modeling framework, in determining when specific 
sugarcane fields should be harvested in order to maximize total farm net returns. Data for this 
analysis were obtained from Agricultural Research Service, USDA experimental research tests 
conducted in Louisiana over several years. Sucrose levels were estimated as a function of time for 
major cultivars currently produced commercially in the state. These data were then incorporated into 
a mathematical programming model which determined an optimal harvest schedule which 
maximizes whole farm net returns for a given farm situation. Production and harvest data collected 
from a commercial sugarcane farm in Louisiana in 1996 were used to evaluate the ability of the 
modeling procedure to improve farm returns through adjustment of the actual harvest schedule. 



31 



Selassi et al.: Maximizing Economic Returns from Sugarcane Harvesting through Optimal Harvest Scheduling 

MATERIALS AND METHODS 

Sugar Prediction Models 

The amount of raw sugar in a field of sugarcane is a function of several variables. Two 
important measures of sugarcane yield include tons of sugarcane per acre and pounds of raw sugar 
produced per acre. The relationship between sugar per acre and factors which influence it can be 
stated simply as follows: 

( 1 ) S A = TRS x TONS = TRS x POP x STWT 

where S A is total pounds of raw sugar per acre, TRS is theoretical recoverable sugar in pounds of 
sugar per ton of cane, TONS is the tons of sugarcane produced per acre, POP is the per acre 
population of sugarcane stalks in the field, and STWT is the stalk weight. Although the population 
of sugarcane stalks within a field can be assumed to be constant throughout the harvest season, the 
same assumption cannot be made for the other factors in the relationship. Theoretical recoverable 
sugar and stalk weight both increase as the harvest season progresses. In order to incorporate this 
yield increase within a whole-farm mathematical programming harvest scheduling model, estimates 
must be obtained for the predicted levels of each of these factors for each variety of sugarcane 
produced on the farm for every day of the harvest season. 

Sucrose maturity data developed at the ARS, USDA Sugar Cane Research Unit in Houma, 
Louisiana, were used in the analysis. Stalk weight and sugar content of the commercial sugarcane 
cultivars grown in Louisiana were sampled at intervals during the harvest season from 1 98 1 to 1 996. 
The data included measurements of theoretical recoverable sugar, sugar per stalk and stalk weight 
by Julian date for 3 to 16 years, depending upon variety. The harvest season for sugarcane in 
Louisiana has historically run from the first of October through the end of December. Observations 
for each commercial cultivar ranged from Julian date 255 to 346 or approximately the middle of 
September through the middle of December. The age of the crop (plantcane or stubble) was also 
included. 

Models were estimated for stalk weight and sugar per stalk in order to predict the amount of 
sugarcane and raw sugar in the field for each day of the harvest season. Previous research suggests 
that a quadratic model can be used to model sugar accumulation (Crane et al., 1982). Graphical 
analysis of both the stalk weight as well as the sugar per stalk data suggested that these variables 
could be estimated using a semi-log functional form. Biological response functions of stalk weight 
and sugar per stalk were estimated for each cultivar as follows: 

95 

(2) STWT ct = P + P, LNJD + p 2 CROP + E P ; YEAR; + € 

i=81 
95 

(3) SPS ct = a + a i LNJD + a 2 CROP + E a { YEA^ + e 

i=81 



32 






Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

where STWT ct represents stalk weight in pounds per stalk of cultivar c on day t, SPS ct represents 
sugar per stalk in pounds of cultivar c on day t, LNJD is the natural log of Julian date (numeric day 
of the year), CROP is a (0,1) indicator variable representing crop age as either plantcane or stubble 
crop, and YEAR; represents discrete indicator variables for different years. Only two categories of 
the indicator variable CROP were included in the model as stubble crops for a given variety 
generally have similar sucrose accumulation levels regardless of crop age. These stubble crop 
sucrose levels, however, are significantly different than plant cane sucrose levels. The annual 
indicator variables for year were included to capture the relationship that sugarcane cultivars have 
distinct sugar accumulation curves which shift vertically from year to year depending upon weather 
and other factors. The base year for comparison in this estimation was 1996 and the indicator 
variables served the purpose of adjusting the sugar accumulation curve to factors in a given year by 
shifting the intercept of the prediction equation. All models were estimated using SAS (SAS 
Institute, version 6. 1 2). The estimates of stalk weight and sugar per stalk were combined with stalk 
populations to estimate cane and sugar yield for each field. 

Estimated models of stalk weight and sugar per stalk for each sugarcane cultivar are shown 
in Tables 1 and 2. Julian date (LNJD) and crop age (CROP) were found to be highly significant in 
the stalk weight prediction models (Table 1). Positive signs on the Julian date variable indicate that 
stalk weight increases throughout the harvest season. The signs on the significant crop age variables 
were negative, as expected, indicating that stalk weight tends to be greater for plantcane crops than 
for older stubble crops. Coefficients of determination for specific variety models ranged from 0.36 
to 0.81 . In several of the estimated equations, indicator variables for years were significant, which 
implies that the stalk weight growth curves vary from year to year depending upon weather and other 
factors. Similar results were found for the sugar per stalk prediction models (Table 2). Julian date 
was highly significant with positive coefficients indicating sugar accumulation increases during the 
harvest season and crop age was found to be significant in six of the seven equations estimated. The 
sign on the estimated coefficient for crop age was negative in each of the six equations in which it 
was significant. Coefficients of determination were very high in the sugar per stalk models ranging 
from 0.86 to 0.90. Durbin- Watson tests for autocorrelation either failed to reject the hypothesis of 
no autocorrelation or were inconclusive, indicating that the error terms from the model predictions 
were not serially correlated. The White test for heteroskedasticity (White, 1980) failed to reject the 
hypothesis of homoskedasticity for each cultivar tested, indicating that error terms from the model 
predictions have a constant variance. The absence of autocorrelation and heteroskedasticity 
indicated that the estimated parameters in the prediction models were efficient (minimum variance) 
estimators. 

Farm Level Production Estimates 

A sample data set was developed from information collected from a commercial sugarcane 
farm in Louisiana for the 1996 harvest season. Characteristics of the farm are presented in Table 3. 
Stalk number estimates were collected on September 18-19 and October 2, 1996 from each of the 
fields on the farm. The number of samples taken per field depended upon the size of the field, but 
a target of one count was taken for every one and half acres. In a randomly selected area of the field, 
a twenty-five foot distance was measured between the middle of two rows. Then, the number of 
millable stalks within that distance was counted and then converted to an estimate of stalk population 
number per acre and field. Sample stalk counts for each field were then averaged to estimate a mean 

33 



Selassi et al.: Maximizing Economic Returns from Sugarcane Harvesting through Optimal Harvest Scheduling 

stalk population per field. Ten-stalk samples were cut from randomly selected locations in each field 
on October 7 and 9, 1996. Each stalk sample was weighed and milled to obtain a juice sample for 
analysis. The average stalk weight and estimated theoretical recoverable sugar from the juice 
analysis were combined with field information to develop stalk weight and sugar per stalk 
measurements by field. 

Prediction models of stalk weight and sugar per stalk were then adjusted to the 1996 crop 
year. This adjustment was incorporated into each prediction model as a parallel shift in the intercept. 
Stalk weight and sugar per stalk were then estimated for each day of the harvest season using the 
estimated prediction models with adjusted intercepts. 

Estimates of tons of sugarcane per acre and pounds of raw sugar per acre were calculated by 
multiplying stalk weight and sugar per stalk by stalk population as follows: 

(4) CANE ft - POP f x STWT ct / 2000 

(5) SUGARft = POP f x SPS ct 

where CANE ft is the estimated tons of sugarcane per acre in field /on Julian date /, POP f is the 
estimated stalk population per acre in field/ STWT ct is the estimated stalk weight in pounds for 
cultivar c on Julian date t, SUGAR ft is the estimated pounds of raw sugar per acre in field/on Julian 
date t, and SPS ct is the estimated sugar per stalk in pounds for cultivar c on Julian date t. Estimated 
yields per field were then adjusted for field conditions (recovery and trash) and differences between 
theoretical recoverable sugar and commercial recoverable sugar as follows: 

(6) ADJCANE ft = CANE ft x (l+TRASH f ) x FIELDRECOVERY f 

(7) ADJSUGARft = SUGAR ft x 0.8345 x SCALEF ACTOR 

ADJCANE ft represents the tons of sugarcane actually harvested from the field and delivered to the 
mill for processing. TRASH f is a percentage estimate of leaf matter and other trash in the harvested 
cane, and FIELDRECOVERY f is a percentage estimate the amount of sugarcane in the field actually 
recovered by harvest operations. Estimated levels of trash and field recovery were determined on 
an individual field basis from producer information. ADJSUGAR ft represents the actual pounds of 
raw sugar recovered from the processed cane. The estimated sugar yield is multiplied by a standard 
factor (0.8345) to convert theoretical recoverable sugar into commercially recoverable sugar. This 
standard is used by sugar mills to estimate recovery since the actual liquidation factor will not be 
known until the end of season. Accounting for differences from the laboratory analysis to the fields, 
the estimated sugar per field is reduced by a scale factor. The assumed scale factor is 92%. 

Mathematical Programming Formulation 

The determination of a harvest schedule was formulated as a linear mathematical 
programming model which maximized producer net returns above harvest costs over total farm 
acreage. Farm returns were derived from the sale of sugar and molasses less a percentage of the total 
production as a "payment-in-kind" to the factory for processing and a percentage of the producer's 

34 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

share paid to the land owner as rent. Since preharvest production costs were assumed to be 
independent of harvest operations, only harvest costs were included in the model. Harvest costs 
were assumed to be a function of the total tonnage of sugarcane harvested. The objective function 
for the model was defined as follows: 

(8) Z = (P S x Sp ) + (P m x Mp) - (C h x Tt ) 

where Z represents total farm level producer net returns from sugar and molasses production above 
harvesting costs, P s represents the price received per pound of sugar (cents per pound), S p is the 
producer's share of sugar produced (pounds), P m is the price of molasses (dollars per gallon), M p is 
the producer's share of molasses (gallons), C h is the cost of harvesting sugarcane (dollars per ton), 
and T t is the total tons of sugarcane harvested. 

The functional constraints in the model consist of two sets of binding constraints and several 
transfer rows. The first three functional constraints are transfer rows that accumulate the total 
pounds of sugar produced, tons of sugarcane harvested, and gallons of molasses recovered, 
respectively. The first set of binding constraints forces the model to choose each field exactly once 
during the harvest season. The model can harvest any percentage of a field on any available day. 
Harvest of individual fields were restricted to certain defined periods, based upon crop age, by 
including estimated daily sugar accumulation for only the days during which harvest of the field is 
permitted. The second set of binding constraints creates a daily limit on the tons of sugarcane that 
may be harvested in one day. Each day has a constraint row that limits the tons of cane harvested 
to less than a specified daily quota amount. The model can be expanded to handle any number of 
fields, and the days available for harvest can be customized to any particular harvest season length. 

RESULTS AND DISCUSSION 

Two different harvest scenarios were solved by the harvest scheduling model. The solution 
results for each of these two scenarios are shown in Table 4. The first solution represents results 
from simulating the producer's actual daily harvest schedule. After the 1 996 harvest season ended, 
the producer provided information on the specific day each field was harvested as well as actual 
sugar yields obtained. The actual harvest schedule solution in Table 4 is based on the date of actual 
harvest by field and the predicted sugarcane and sugar yields from the estimated prediction models. 
Sugarcane (tons) and sugar (pounds) yields per acre achieved by the producer closely matched 
predicted yields from the estimated models. Predicted total sugarcane production was 16,964 tons 
of sugarcane compared to the actual production of 1 6,639 tons reported by the producer. Estimated 
producer returns above harvest costs for the actual harvest schedule were $326,771. Average 
sugarcane yield over the whole farm was 30.5 tons per acre, resulting in an average sugar yield of 
5,573 pounds per acre. 

A second harvest scheduling model was solved for a solution in which harvest dates for 
individual fields were constrained to specified intervals. In Louisiana, sugarcane harvest begins with 
fields which contain the oldest stubble crops (second-stubble and older), then proceeds to younger, 
first stubble crops. All stubble crop fields are usually harvested first. Within each stubble group, 
varieties are usually harvested in order of maturity class: very early, early, and mid-season (Faw, 
1 998). Finally, fields containing plantcane which are being harvested for the first time are harvested 

35 



Selassi et al.: Maximizing Economic Returns from Sugarcane Harvesting through Optimal Harvest Scheduling 

at the end of the harvest season in order to avoid damage of future stubble crops from early harvest. 
Plantcane fields are usually harvested beginning with varieties that deteriorate rapidly after a freeze 
and end with harvest of varieties that deteriorate at a slower rate after a freeze (more freeze tolerant). 
An additional consideration which impacts the harvest schedule is soil type. Extended periods of 
rain during the harvest season makes harvest of sugarcane on heavy textured clay soils difficult. 
Harvest operations on excessively wet fields containing clay soils can severely rut a field and 
possibly damage the stubble crop which would be harvested the following year. As a result, fields 
containing heavy textured clay soils would generally be harvested before fields containing lighter 
textured sandy soils. 

In the constrained harvest model, possible harvest dates were specified for each field in the 
sample data set which conformed to traditional harvesting practices. Generally stated, these harvest 
date ranges began with second-stubble harvest beginning on October 1 st and continuing into 
November, first-stubble harvest beginning in late October and continuing through November, and 
plantcane harvest beginning in late November and continuing through the end of December. 
Harvesting periods by crop age in the constrained harvest model were also adjusted for soil type. 
The resulting defined harvest periods included in the model were as follows: (a.) October 1- 
Novemberl: second-stubble and older crops, all soil types; (b.) October 20 - November 15: first- 
stubble crops, heavy soil; (c.) October 25 - November 25: first-stubble crops, mixed soil; (d.) 
November 1 - December 31: first-stubble crops, light soil; (e.) November 25 - December 31: 
plantcane crops, heavy soil; (f.) December 1 - December 31: plantcane crops, mixed soil; and (g.) 
December 1 - December 3 1 : plantcane crops, light soil. These defined harvest periods were based 
on the distribution of soil types on the particular farm being analyzed. A farm with a different 
distribution of soil types would probably have had a slightly different set of defined harvest periods. 
Solution results from this model indicated that sugar production and net returns could be increased 
with relatively minor adjustments to the actual harvest schedule. Optimal adjustment of harvest of 
individual fields resulted in a projected increase in total farm net returns of $17,360, or 
approximately $3 1 per harvested acre. Average harvested yield of sugarcane increased by 0.7 tons 
per acre resulting in an increase in average sugar yield per acre of 263 pounds. Analysis of 
individual field results indicated that the optimal harvest date changed an average of 13 days from 
the actual harvest date with some fields being harvested earlier and other fields harvested later in the 
season. 

One factor which would have an effect on optimal harvest schedule determination to 
maximize net returns would be related to harvest travel costs. Harvest travel cost, i.e., the cost of 
moving sugarcane harvesting equipment from one field to another on the farm during the harvest 
season, would significantly impact net returns above harvest costs for farms on which individual 
fields are located at considerable distances from one another. Although harvest travel costs were not 
included in the analysis presented here, they should be considered when comparing alternative 
harvest schedules with the purpose of maximizing net returns. The relevant cost measure to consider 
in this decision analysis would be the change in travel costs among different schedules. For a 
specific change from one harvest schedule to another, this change in travel cost could be positive or 
negative. Inclusion of travel costs in the analysis should be considered in a whole farm basis. Whole 
farm harvest travel costs can be minimized by restricting harvest of fields within close proximity to 
each other to one defined harvest period and restricting fields in another locality to a different harvest 
period. 

36 



.. 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

CONCLUSIONS 

The long- term viability of the sugar industry will depend upon finding ways to produce sugar 
more economically through reduction of production costs and efficient management of available 
resources. Maximizing net returns for a whole farm, rather than trying to produce the maximum 
amount of sugar per field, should be the primary goal of producers. The purpose of this study was 
to develop a methodology to assist in scheduling the sequence in which sugarcane fields are 
harvested to maximize producers' economic returns. Models which predicted stalk weight and sugar 
per stalk by cultivar were estimated as a function of Julian date and crop age as well as indicator 
variables representing years of production with different growing conditions. These models were 
then used to predict sugar yields by cultivar and field for a sample farm. The optimization linear 
programming model used the estimated accumulation of stalk weight and sugar per stalk with field 
information to generate yield predictions. The predicted yields were used to select a harvest schedule 
subject to constraints that maximized producer net returns above harvest cost. 

The ability to predict sugarcane tonnage and raw sugar yields allows producers and mill 
personnel to more effectively plan the harvest of a sugarcane crop based on the current status of that 
crop. The type of harvest scheduling model developed here, although somewhat complex, could be 
standardized to allow for easy imputation of sucrose and tonnage accumulation data as well as 
individual farm data. A producer, or crop consultant, could potentially analyze the yield of each 
cultivar of sugarcane in the farm's crop mix and make decisions concerning harvest as well as future 
plantings. Optimization of harvest schedules could potentially recover more sugar from the fields, 
which directly increases the sugar recovered by the mills. Knowledge of the size and maturity stage 
of the crop could allow mills to more effectively assign delivery quotas among producers and plan 
the harvest schedule to maximize sugar production. Interest in site specific farming using global 
positioning satellites (GPS) and global information system (GIS) is growing among sugarcane 
producers, but the limiting factor is the ability to attribute yield to location. The model developed 
in this study allows for the possibility of predicting sugar yield for individual fields. This 
information can be useful in designing fertility programs, weed control programs and in making 
crop replacement decisions on an individual field basis. 

REFERENCES 

1. Brumelle, Shelby, Daniel Granot, Merja Halme, and Ilan Vertinsky. 1998. A tabu search 
algorithm for finding good forest harvest schedules satisfying green-up constraints. 
European Journal of Operational Research. 106:408-424. 

2. Chang, Y. S. 1995. The trend of sucrose accumulation during maturation of sugarcane with 
special reference to the maturity of sugarcane cultivars. Report of the Taiwan Sugar 
Research Institute. 148:1-9. 

3. Crane, Donald R., T. H. Spreen, J Alvarez and G. Kidder. 1982. An analysis of the stubble 
replacement decision for Florida sugarcane growers, Agricultural Experiment Station, 
Institute of Food and Agricultural Sciences, University of Florida. Bulletin 822. 



37 



Selassi et al.: Maximizing Economic Returns from Sugarcane Harvesting through Optimal Harvest Scheduling 

4. Daust, David K., and John D.Nelson. 1993. Spatial reduction factors for strata-based harvest 
schedules. Forest Science. 39:152-165. 

5. Faw, Wade F. 1998 Sugarcane Harvesting Schedule. Sugarcane Circular Letter No. 1 1-98, 
Louisiana Cooperative Extension Service, Louisiana State University Agricultural Center. 

6. Higgins, A. J., R. C. Muchow, A. V. Rudd, and A. W. Ford. 1998. Optimising harvest date 
in sugar production: a case study for the Mossman mill region in Australia - 1. Development 
of operations research model and solution. Field Crops Research. 57:153-162. 

7. Lass, L. W., R. H. Callihan, and D. O. Everson. 1 993. Forecasting the harvest date and yield 
of sweet corn by complex regression models. Journal of the American Society for 
Horticultural Science. 118:450-455. 

8. Malezieux, E. 1994. Predicting pineapple harvest date in different environments using a 
computer simulation model. Agronomy Journal. 86:609-617. 

9. Muchow, R. C, A. J. Higgins, A. V. Rudd, and A. W. Ford. 1998. Optimising harvest date 
in sugar production: a case study for the Mossman mill region in Australia - 1. Sensitivity to 
crop age and crop class distribution. Field Crops Research. 57:243-251. 

1 0. Nelson, John, J. Douglas Brodie, and John Sessions. 1 99 1 . Integrating short-term, area-based 
logging plans with long-term harvest schedules. Forest Science. 37:101-122. 

11. Salassi, M. E., and S. B. Milligan. 1997. Economic analysis of sugarcane variety selection, 
crop yield patterns, and ratoon crop plow out decisions. Journal of Production Agriculture. 
10:539-545. 

12. SAS Institute. 1989. SAS/OR User's Guide, Version 6, 1 st edition. SAS Institute, Cary,NC. 

13. Semenzato, R. 1995. A simulation study of sugar cane harvesting. Agricultural Systems. 

47:427-437. 

14. Van Deusen, Paul C. 1996. Habitat and harvest scheduling using Bayesian statistical 
concepts. Canadian Journal of Forest Research. 26:1375-1383. 

1 5 . White, H. 1 980. A heteroskedasticity-consistent covariance matrix estimator and a direct test 
of heteroskedasticity. Econometrica. 48:817-838. 

16. Wolf, S. 1986. Predicting harvesting date of processing tomatoes by a simulation model. 
Journal of the American Society for Horticultural Science. 111:11-16. 



38 









... 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 1. Parameter Estimates for Stalk Weight Prediction Models 



Sugarcane Varieties 


VAR 


LCP 


LHo 


CP 


CP 


CP 


CP 


LCP 




82-89 


83-153 


79-318 


70-321 


65-357 


72-370 


85-384 


INT 


-7.717** 


-6.747** 


-8.868** 


-6.672** 


-6.884** 


-5.550** 


-9.192** 




(-5.10) 


(-4.68) 


(-6.51) 


(-6.92) 


(-6.92) 


(-6.34) 


(-3.53) 


LNJD 


1.805** 


1.621** 


2.040** 


1.652** 


1.718** 


1.441** 


1.988** 




(6.81) 


(6.41) 


(8.57) 


(9.82) 


(9.89) 


(9.40) 


(4.35) 


CROP 


-0.373** 


-0.312** 


-0.295** 


-0.330** 


-0.352** 


-0.389** 


-0.158* 




(-7.46) 


(-6.56) 


(-6.50) 


(-10.27) 


(-10.53) 


(-13.44) 


(-1.88) 


1981 


- 


- 


- 


0.190** 
(2.56) 


0.097 
(1.32) 


0.107 
(1.47) 


- 


1982 


- 


- 


- 


0.091 


-0.294** 


0.013 


- 











(1.19) 


(-3.85) 


(0.17) 




1983 


- 


- 


" 


-0.154** 
(-2.02) 


-0.372** 
(-4.86) 


-0.109 
(-1.46) 


- 


1984 


- 


- 


- 


-0.233** 
(-3.13) 


-0.474** 
(-6.39) 


-0.090 
(-1.22) 


- 


1985 


- 


- 


" 


-0.215** 
(-2.90) 


-0.610** 
(-8.27) 


-0.152** 
(-2.09) 


- 


1986 


- 


- 


" 


-0.227** 
(-3.06) 


-0.397** 
(-5.37) 


-0.144* 
(-1.98) 


- 


1987 


- 


- 


-0.347** 


-0.483** 


-0.509** 


-0.392** 


- 








(-3.53) 


(-5.80) 


(-6.07) 


(-4.88) 




1988 


- 


- 


-0.055 


0.001 


-0.181** 


-0.138* 


- 








(-0.64) 


(0.01) 


(-2.46) 


(-1.89) 




1989 


- 


- 


-0.101 


0.092 


-0.037 


0.016 


- 








(-1.13) 


(1.20) 


(-0.48) 


(0.21) 




1990 


0.214** 


- 


0.187** 


0.259** 


0.034 


0.212** 


- 




(2.55) 




(2.15) 


(3.50) 


(0.41) 


(2.91) 




1991 


-0.862** 


-0.813** 


-0.637** 


-0.981** 


-0.985** 


-0.805** 


- 




(-9.99) 


(-10.65) 


(-7.11) 


(-12.79) 


(-12.87) 


(-10.77) 




1992 


-0.459** 


-0.372** 


-0.317** 


-0.483** 


-0.572** 


-0.364** 


- 




(-5.47) 


(-5.02) 


(-3.64) 


(-6.52) 


(-7.75) 


(-5.00) 




1993 


-0.374** 


-0.400** 


-0.375** 


-0.280** 


-0.359** 


-0.293** 


- 




(-4.46) 


(-5.40) 


(-4.31) 


(-3.77) 


(-4.87) 


(-4.03) 




1994 


-0.009 


-0.160** 


-0.025 


-0.098 


-0.287** 


-0.109 


-0.061 




(-0.11) 


(-2.15) 


(-0.29) 


(-1.32) 


(-3.89) 


(-1.49) 


(-0.62) 


1995 


-0.161* 


-0.130* 


-0.081 


-0.000 


-0.222** 


-0.116 


0.061 




(-1.92) 


(-1-75) 


(-0.93) 


(-0.01) 


(-3.01) 


(-1.59) 


(0.62) 


Adj. R 2 


0.81 


0.79 


0.73 


0.80 


0.78 


0.80 


0.36 


n 


72 


62 


98 


158 


158 


153 


36 


DW 


1.77 


2.03 


1.89 


1.94 


2.25 


1.84 


2.42 


White prb 


0.34 


0.89 


0.74 


0.41 


0.34 


0.87 


0.36 



Notes: Numbers in parentheses are ^-values. Single and double asterisks (*) denote statistical 

significance at the 10% and 5% levels, respectively, n is the sample size, DW is the Durbin- 

Watson statistic, and White prb is the probability level of the White test for heteroskedasticity. 



39 



Selassi et al.: Maximizing Economic Returns from Sugarcane Harvesting through Optimal Harvest Scheduling 

Table 2. Parameter Estimates for Sugar per Stalk Prediction Models 









Sugarcane Varieties 






VAR 


LCP 


LHo 


CP 


CP 


CP 


CP 


LCP 




82-89 


83-153 


79-318 


70-321 


65-357 


72-370 


85-384 


INT 


-3.511** 


-3.296** 


-4.064** 


-3.470** 


-3.932** 


-2.442** 


-4.081** 


LNJD 


(-18.62) 
0.664** 


(-14.40) 
0.626** 


(-24.19) 
0.764** 


(-25.99) 
0.663** 


(-29.80) 
0.741** 


(-19.95) 
0.486** 


(-15.74) 
0.757** 


CROP 


(20.08) 
-0.024** 


(15.58) 
-0.014* 


(26.05) 
-0.017** 


(28.49) 
-0.029** 


(32.17) 
-0.027** 


(22.68) 
-0.041** 


(16.64) 
0.004 


1981 


(-3.86) 


(-1.86) 


(-2.96) 


(-6.54) 
0.018* 


(-6.11) 
0.027** 


(-10.07) 
0.010 


(0.43) 


1982 


_ 


. 




(1.77) 
-0.011 


(2.71) 
-0.037** 


(0.96) 
-0.009 




1983 


_ 


. 




(-1.00) 
-0.028** 


(-3.60) 
-0.022** 


(-0.86) 
-0.035** 




1984 


_ 






(-2.62) 
-0.041** 


(-2.17) 
-0.042** 


(-3.37) 
-0.021** 




1985 


. 


. 




(-3.93) 
-0.037** 


(-4.31) 
-0.052** 


(-2.04) 
-0.034** 




1986 


. 






(-3.65) 
-0.032** 


(-5.29) 
-0.003 


(-3.35) 
-0.022** 




1987 






-0.005 


(-3.09) 
-0.033** 


(-0.32) 
-0.008 


(2.15) 
-0.038** 




1988 






(-0.44) 
-0.004 


(-2.87) 
-0.006 


(-0.68) 
-0.004 


(-3.40) 
-0.022** 




1989 






(-0.35) 
0.001 


(-0.56) 
0.003 


(-0.44) 
0.028** 


(-2.20) 
-0.014 




1990 


0.011 




(0.12) 
0.005 


(0.26) 
0.006 


(2.81) 
0.009 


(-1.34) 
0.003 




1991 


(1.06) 
-0.097** 


-0.113** 


(0.46) 
-0.070** 


(0.58) 
-0.147** 


(0.80) 
-0.079** 


(0.33) 
-0.108** 




1992 


(-9.02) 
-0.034** 


(-9.36) 
-0.044** 


(-6.32) 
-0.017 


(-13.85) 
-0.047** 


(-7.76) 
-0.014 


(-10.34) 
-0.047** 




1993 


(-3.27) 
-0.047** 


(-3.74) 
-0.064** 


(-1.58) 
-0.039** 


(-4.54) 
-0.049** 


(-1.43) 
-0.012 


(-4.58) 
-0.033** 




1994 


(-4.54) 
0.004 


(-5.42) 
-0.020 


(-3.68) 
0.012 


(-4.79) 
-0.021** 


(1.20) 

-0.008 


(-3.29) 
-0.011 


-0.008 


1995 


(0.35) 
-0.019* 


(-1.66) 
-0.017 


(1.11) 

-0.008 


(-2.05) 
0.005 


(-0.78) 
-0.015 


(-1.04) 

-0.014 


(-0.84) 
-0.005 




(-1.79) 


(-1-43) 


(-0.76) 


(0.49) 


(1.50) 


(-1.41) 


(-0.46) 


Adj. R 2 


0.89 


0.86 


0.90 


0.89 


0.89 


0.86 


0.89 


n 


72 


62 


98 


158 


158 


153 


36 


DW 


2.01 


2.44 


2.13 


1.99 


2.23 


1.88 


2.74 


White prb 


0.37 


0.39 


0.86 


0.20 


0.82 


0.74 


0.14 



Notes: Numbers in parentheses are ^-values. Single and double asterisks (*) denote statistical 
significance at the 10% and 5% levels, respectively, n is the sample size, DW is the Durbin- 
Watson statistic, and White prb is the probability level of the White test for heteroskedasticity. 









40 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 3. Sample Farm Acreage and Production Characteristics 



Farm data: 








Farm size (harvested acreag 


s) 556.9 




Number of fields 


112 




Smallest field (acres) 


0.3 




Largest field ( 


^acres) 


19.6 




Variety data: 








LCP 82-89 


plantcane 


1 field 


1.3 acres 


LCP 82-89 


stubble crop 


13 fields 


44.0 acres 


LHo 83-153 


plantcane 


2 fields 


6.7 acres 


LHo 83-153 


stubble crop 


6 fields 


31.8 acres 


CP 79-318 


stubble crop 


4 fields 


14.2 acres 


CP 70-321 


plantcane 


12 fields 


74.2 acres 


CP 70-321 


stubble crop 


43 fields 


228.9 acres 


CP 65-357 


stubble crop 


7 fields 


38.0 acres 


CP 72-370 


plantcane 


3 fields 


13.6 acres 


CP 72-370 


stubble crop 


14 fields 


61.7 acres 


LCP 85-384 


plantcane 


5 fields 


37.3 acres 


LCP 85-384 


stubble crop 


2 fields 


5.2 acres 



Table 4. Comparison of actual harvest schedule with optimal harvest schedules 

Actual harvest schedule 1 
Solution Summary 



Constrained optimal 
harvest schedule 



Returns above harvest costs 

Returns above harvest costs per acre 

Total sugar (pounds) 

Total cane (tons) 

Total molasses (gallons) 

Acres 

Average CRS (pounds sugar/ton) 

Sugar per acre (pounds) 

Cane per acre (tons) 



$326,771 

$587 

3,103,709 

16,964 

90,008 

556.9 

183.0 

5,573 

30.5 



$344,131 

$618 

3,250,056 

17,373 

94,252 

556.9 

187.1 

5,836 

31.2 



1 Producer's actual harvest schedule with total sugar and cane production estimated from prediction 
models. Producer records report actual production of 16,639 tons of sugarcane and 2,961,500 



pounds of sugar. 



41 



Gravois et al.: Cultivar and crop effects of sugarcane bull shoots on sugarcane yield in Louisiana. 

CULTIVAR AND CROP EFFECTS OF SUGARCANE BULL SHOOTS 
ON SUGARCANE YIELD IN LOUISIANA 

Kenneth A. Gravois 1 , Benjamin L. Legendre 2 , and Keith P. Bischoff 

1 Louisiana State University Agricultural Center, Sugar Research Station, P.O. Box 604, St. 

Gabriel, LA 70776. Louisiana State University Agricultural Center, Cooperative Extension 

Service, Baton Rouge, LA 70894. (formerly of USDA-ARS, Southern Regional Research Center 

Sugarcane Research Unit, P.O. Box 470, Houma, LA 70361). 

ABSTRACT 

Bull shoots are late-sprouting, large-diameter tillers that often appear late in the season in 
sugarcane {Saccharum spp.) grown in south Louisiana. The effect of bull shoots on sugarcane yield 
has not been assessed in Louisiana. The objectives of this study were to evaluate the cultivar and 
crop effects of bull shoots on sugarcane yield and yield components. Cultivar effects of bull shoots 
were evaluated during 1998 and 1999 at the USDA-ARS Ardoyne Farm at Chacahoula, LA. Crop 
effects of bull shoots were evaluated during 1998 at a test conducted on Joel Landry's farm near 
Paincourtville, LA. Sugarcane cultivars produced significantly different amounts of bull shoots. 
Sugarcane cultivars LHo 83-153 and LCP 85-384 produced the least amount of cane yield derived 
from bull shoots, averaging 3.2 and 4.4 percent of the total cane yield for the two years, respectively. 
Sugarcane cultivar HoCP 85-845 produced the greatest cane yield derived from bull shoots, 16.1 
percent of the total cane yield for the two years. For all cultivars, both sucrose concentration and 
fiber content were lower for the bull shoots than for the whole stalks. For the test conducted at the 
Joel Landry Farm, the plantcane crop derived 16.6 percent of its total cane yield from bull shoots, 
whereas the first-ratoon crop derived 11.8 percent of its total cane yield from bull shoots. For both 
tests, the overall effect of bull shoots was positive because of the net increase in sucrose yield per 
unit area. However, bull shoots may have an adverse effect on processing because of added 
polysaccharides, starch, and color precursors. With the additional costs of transportation and 
processing and the negative effects on sugar quality, bull shoots may likely have an overall negative 
effect on overall sugar production. 

INTRODUCTION 

Bull shoots are late-sprouting, large-diameter tillers that often appear late in the growing 
season in sugarcane grown in south Louisiana. Bull shoots are also referred to as suckers or water 
sprouts. Some sugarcane cultivars tend to produce more bull shoots than others, and the problem 
is more pronounced in some years. Bull shoots are considered to produce additional weight with 
minimal sucrose concentration adding significant transportation and milling costs. 

Sugarcane is clonally propagated for commercial production. In Louisiana, whole stalks and, 
to a lesser extent, smaller billet pieces are planted in the soil during August and September to begin 
a cycle of crops. Usually, a plantcane crop and two to three ratoon crops are harvested from a single 
planting. Because of Louisiana's temperate climate, the crop remains dormant in the winter months 
following harvest. In the spring, new shoots emerge to begin the subsequent crop. Once a sugarcane 
crop is harvested, the roots are physiologically active for only a short while (Baver et al, 1 962). The 
roots cease to function and quickly die. For each new ratoon, a shoot that develops from an 

42 



Journal American Society of Sugarcane Technologists, Vol. 22, 2001 

underground overwintering bud quickly develops its own root system. Like many grasses, sugarcane 
relies on tillering to attain a desired plant population. In Louisiana, the tillering period usually 
ranges from late April through early June. Maximum tillering occurs approximately 500°C d after 
regrowth (Inman-Bamber, 1994). More tillers are produced than can normally become mature 
millable stalks. Tiller senescence occurs after the canopy closes beyond 70% interception of 
photosynthetically active radiation (Inman-Bamber, 1994). 

Suckering, or the formation of bull shoots, begins in fields that are six to seven months of 
age (Hess, 1954). The formation of bull shoots begins in fields where sunlight is able to penetrate 
to the soil surface. It is common to observe a flush of bull shoots produced after sugarcane has 
lodged. In Hawaii, this flush of tillers is important to the overall contribution of cane yield. In 
Mauritius, bull shoots are not cut during hand harvesting and serve as an important beginning toward 
the next crop cycle. In Louisiana, some cultivars, like HoCP 85-845, can produce bull shoots even 
when the crop remains erect with a dense canopy. The cultivar CP 72-370 also has a tendency to 
produce bull shoots in Louisiana. However, the leaf angle of CP 72-370 is extremely erect and may 
allow enough sunlight to penetrate the canopy, thus allowing bull shoots to form late in the growing 
season. Salter and Bonnet (2000) indicated that high soil nitrogen level was one of several factors 
that may contribute to late season sucker production. 

The effects of sugarcane bull shoots on sugarcane yield parameters have not been quantified 
for different cultivars or for different sugarcane crops (plantcane vs first ratoon). Therefore, our 
objectives were to assess cultivar and crop effects of sugarcane bull shoots on sugarcane yield and 
yield components. 

MATERIALS & METHODS 

Tests were conducted in 1998 and 1999 to determine the effect of bull shoots on different 
sugarcane cultivars at the USDA-ARS Sugarcane Research Unit's Ardoyne Farm at Chacahoula, 
LA. Data were collected each year from the plantcane crop of the second line trials of the USDA- 
ARS sugarcane breeding program. Cultivars used as controls in the second line trials (CP 70-321, 
LHo 83-153, LCP 85-384, and HoCP 85-845) were replicated five times throughout the trials and 
were harvested from this test for analyses. Each plot was a single row 4.9 m long and 1 .8 m wide. 
The control cultivars in the second line trials were arranged as a randomized complete block design. 
The soil type was a Commerce silt loam. 

In 1998, a test was conducted on Joel Landry Farms in Paincourtville, LA to determine the 
effect of sugarcane bull shoots on different sugarcane crops (plantcane vs first ratoon). The soil type 
for this test was also a Commerce silt loam. The cultivar tested was HoCP 85-845 in adjacent fields 
of a plantcane and first-ratoon crop. The experimental design at this location was a randomized 
complete block with a split-plot arrangement of treatments. Whole plots were crop, and sub plots 
were whole stalk and bull shoot treatments. Each plot was a single row 4.9 m long and 1 .8 m wide. 

The tests conducted at the Ardoyne Farm were harvested on December 17, 1998 and 
November 23, 1999. The test conducted at the Joel Landry Farm was harvested on December 18, 
1998. Just prior to harvest, all stalk types were counted in each plot. For the Ardoyne Farm tests, 
whole stalks were counted as well as bull shoots, which were divided into two categories: those 
stalks greater than one meter and those stalks less than one meter in height. Hand-cut stalk samples 

43 



Gravois et al.: Cultivar and crop effects of sugarcane bull shoots on sugarcane yield in Louisiana. 

of five stalks of each stalk type were harvested and sent to the sucrose laboratory for quality 
analyses. In some instances, less than five stalks were harvested when stalk type counts were less 
than five. In the Joel Landry Farm test, stalk counts were done similarly except that the bull shoots 
were not categorized by height. Ten hand-cut stalks of each stalk type were harvested for analyses 
in the sucrose laboratory. All samples were cut level with the ground, topped through the apical bud, 
stripped of leaf material, bundled, and tagged. Bundle weight was recorded upon entry into the 
sucrose laboratories. 

The samples from the Joel Landry farm were processed at the LSU Sugar Research Station 
sucrose laboratory at St. Gabriel, LA. Fiber content (g/kg) was determined by chopping six stalks 
with a Jeffco cutter-grinder (Jeffress Brothers Ltd., Brisbane Queensland, Australia), mixing, and 
taking a 600-g sub-sample for fiber analysis (Tanimoto, 1964). Each sample was pressed with a 
hydraulic press at 10.35 MPa pressure for one minute to separate the juice from the residue 
(bagasse). The residue was weighed and then oven-dried for three days at a temperature of 40.5°C. 
The weight of the dry plug was then recorded. A portion of the crusher juice was analyzed for Brix 
(percent soluble solids w/w) by refractometer (Chen and Chou, 1 993). Pol of the clarified juice was 
obtained with an automated saccharimeter. Fiber content and sucrose concentration were estimated 
as described by Gravois and Milligan (1992). 

Samples from the Ardoyne Farm were analyzed each year at the USDA-ARS Sugarcane 
Research Unit's sucrose laboratory at the Ardoyne Farm. Samples were prepared with a prebreaker 
(Legendre, 1992). For quality analysis, 1000-g samples were pressed with 2.01 MPa pressure for 
seventy- five seconds. The remaining sample plug was oven-dried for three days at a temperature of 
40.5°C. Sucrose concentration (g/kg) was obtained using Brix, pol, and fiber percent cane along 
with recent modifications to the formula (Legendre, 1 992). Using the fibraque correction, New Fiber 
content = Fiber * 1.3; New Pol = Pol * (100 - New Fiber)/(100 - Fiber); New Brix = Brix * (100- 
New Fiber)/(100-Fiber) * Z, where Z = 1.15 - 0.0018((1000 - Corrected Residue Weight)/ 10). The 
factor Z further corrects the Brix to reflect the lower purity of the juice remaining in the pressed core 
sample. Thus, the Winter-Carp formula is calculated as follows: 

Sucrose concentration = 0.5 * ((0.28 * New Pol - 0.08 * New Brix) * (100 - (56.67 * New 
Fiber)/(100 - New Fiber))) 

These modifications in the sucrose concentration formula result in lower values and more closely 
reflect the yield of commercially recoverable sugar as reported by the mills. 

Cane yield (Mg/ha) was estimated as the product of stalk number per unit area (no. per m 2 ) 
and mean stalk weight (kg). Sucrose yield (Mg/ha) was the product of cane yield and sucrose 
concentration divided by 10. 

Data for the USDA Ardoyne Farm experiment were analyzed with the following mixed 
model: 

T ijkl =M + Y i + R j(i) + V k + S,+ YV ik + YS U + VS kl + YVS ikl + E ijkl 

where fi was the overall mean; Y t was year i; R j(i) was replication^ within Year i; V k was Cultivar k, 

44 



Journal American Society of Sugarcane Technologists, Vol. 22, 2001 

S[ was stalk type /. YV ik , YS it , VS kl , and YVS M were the interactions, and E ljk was the residual. Crop 
and stalk type and their interaction were considered fixed effects, with the remaining effects 
considered as random effects in the model. 

Data for the Joel Landry Farm experiment were analyzed with the following mixed model: 

T ijk = ft + C i + R J(0 + S k + CS ik + E ijk 

where T ijk is observation/ in crop i, of stalk type k; fJ, is the overall mean; C, is crop i\ S k is stalk type 
k; CS lk is stalk type by crop interaction; and E ijk is the residual. Replication was considered a random 
effect, and crop and stalk type were considered fixed effects in the model. Means separation 
techniques were based on LSD (P=0.05). 

A separate experiment was conducted in 1986 to determine the effect of date of sampling and 
sucrose concentration on stalk density. Five experimental clones from the L84 assignment series and 
the control cultivar CP 65-357 were sampled from the infield tests at the St. Gabriel Research 
Station. Stalk density and sucrose concentration were evaluated for each cultivar on August 13, 
1986; October 2, 1986; and December 1, 1986. Stalk density (g/cm 3 ) was estimated based on stalk 
height (cm), stalk diameter (cm), and stalk weight (g) measurements from five stalks. Stalk volume 
was estimated as: 71 * stalk height * (radius) 2 . Stalk density was estimated as stalk weight/stalk 
volume. Sucrose concentration was estimated as described by Gravois and Milligan ( 1 992). Partial 
correlation coefficients among the traits were obtained after adjusting for date and replication effects 
in the model. 

RESULTS & DISCUSSION 

For the tests conducted at the Ardoyne Farm, both sugarcane cultivars and stalk types 
differed significantly for all traits (Table 1 ). Based on cane yield in 1 998, the cultivar HoCP 85-845's 
total bull shoot cane yield was 26.0 Mg/ha, which was 21.5 percent of the total cane yield for that 
cultivar (Table 2). In contrast, only 2.3 Mg/ha or 2. 1 percent of the total cane yield of the cultivar 
LHo 83-153 was attributed to bull shoots. LCP 85-384 is the most widely grown cultivar in 
Louisiana, harvested on 71 percent of the state's 2000 acreage (Louisiana Cooperative Extension 
Service Census 2000). The effect of bull shoots on LCP 85-384 was minimal. Only 6.6 and 2.1 
percent, in 1998 and 1999, respectively, of LCP 85-384's total cane yield was contributed by bull 
shoots, with the majority of bull shoots being under one meter in 1998. In 1999, LCP 85-384 was 
the cultivar with the least amount of cane yield derived from bull shoots. 

The effect of crop on bull shoot production was evaluated in the 1998 test conducted at the 
Joel Landry Farm. HoCP 85-845 stalk type (whole stalks, bull shoots, and total stalks) was 
significantly different for all sugarcane traits (Table 3). Crop (plantcane vs. first ratoon) effects were 
significant for sucrose yield, sucrose concentration, stalk number, stalk weight, and fiber content. 
Sucrose yield, sucrose concentration, and stalk weight means of the bull shoots were significantly 
higher for the plantcane crop than for the first-ratoon crop (Table 4). Conversely, fiber content of 
the bull shoots was significantly lower for the plantcane crop than for the first-ratoon crop. Similar 
to the results of the Ardoyne Farm test, the bull shoots had a lower sucrose concentration and fiber 
content compared to the whole stalks. In the Joel Landry Farm test, bull shoots accounted for 16.6 

45 



Gravois et al.: Cultivar and crop effects of sugarcane bull shoots on sugarcane yield in Louisiana. 

and 1 1.8 percent of the total cane yield in the plantcane and first-ratoon crops, respectively. The 
overall effect of bull shoots on sugarcane production was positive when assessed by sucrose yield 
for both plantcane and first-ratoon crops. 

The production of sugarcane is measured by the field cane yield produced per unit area. The 
quality of that cane yield is measured by the sucrose concentration. In sugarcane produced in 
Louisiana, the tops and side leaves of the stalks are removed either by controlled agricultural burns 
or mechanically by extractor fans in combine harvesting systems. Tops and side leaves can decrease 
sugarcane quality if processed with whole stalks of sugarcane (Ivin and Doyle, 1989). 

In a combine harvesting system, short bull shoots would likely be easily extracted with the 
tops and side leaves through the extractor fan systems. Some portion of the tall bull shoots would 
likely have a greater chance of being discarded through the extractor fans because of their lower 
sucrose concentration, which makes these stalk portions less dense than the whole stalks. This 
premise is supported by the data collected in the 1986 stalk density study. As expected, sucrose 
concentration significantly increased for each sampling date (August through December). Likewise, 
stalk density significantly increased for each sampling date: 0.95 g/cm 3 in August, 1 .06 g/cm 3 in 
October, and 1.13 g/cm 3 in December. As the sucrose concentration of the stalks increased, stalk 
density increased. There was no variety x date interaction, indicating that all varieties followed this 
pattern. The lower stalk density of the bull shoots would make separation of the bull shoots from 
the whole stalks more achievable through an air flow fan extractor system. However, as noted in 
these studies, the bull shoots had larger stalk diameters. Bull shoot billet pieces would likely weigh 
more than whole stalk billet pieces of similar length, which would tend to offset the stalk density 
differential between the two stalk types. 

In a whole stalk harvesting system, both short and tall bull shoots would be harvested and 
sent to the factory, although some of the shorter bull shoots would not carry over to the heap. Since 
bull shoots are living green shoots, burning would have a minimal effect on reducing the cane yield 
derived from bull shoots. The increase in cane yield is offset by a lower sucrose concentration for 
the bull shoots. However, the overall effect of bull shoots as measured by sucrose yield was positive 
in the Ardoyne Farm test for each cultivar in both 1998 and 1999 and in the Joel Landry Farm test 
in 1 998. Other economic factors would tend to diminish the positive effect of bull shoots on sucrose 
yield. First, both the factory and grower are incurring transportation costs to what is essentially poor 
quality cane. The overall effect of bull shoots at the factory would be to lower both sucrose 
concentration, a negative aspect, and fiber content, a positive aspect. While the overall effect of bull 
shoots on sucrose yield in the field is positive, bull shoots may have an adverse effect on processing 
because of added polysaccharides, starch, and color precursors. With the additional costs of 
transportation and processing and the negative effects on sugar concentration, bull shoots may likely 
have a negative effect on overall sugar production. 



46 



Journal American Society of Sugarcane Technologists, Vol. 22, 2001 

REFERENCES 

1. Baver, L.D., H.W. Brodie, T. Tanimoto, and A.C. Trouse. 1962. New approaches to the 
study of cane root systems. Proc. Int. Soc. Sugar Cane Technol. Congr. 1 1 :248-252. 

2. Chen, J.C.P. and C.C. Chou. 1993. Meade-Chen Cane Sugar Handbook, 12 th ed. John 

Wiley and Sons, Inc. 

3. Gravois, K.A. and S.B. Milligan. 1992. Genetic relationships between fiber and sugarcane 
yield components. Crop Sci. 32:62-67. 

4. Hess, J. W. 1954. The influence of suckers on the yield of sugarcane. Sugar Journal 16:25- 
31. 

5. Inman-Bamber, N.G. 1994. Temperature and seasonal effects of canopy development and 
light interception of sugarcane. Field Crops Res. 36:41-51. 

6. Ivin,P.C. and CD. Doyle. 1989. Some measurements of the effect of tops and trash on cane 
quality. Proc. Australian Soc. Sugar Cane Technol. 11:1-7. 

7. Legendre,B.L. 1992. The core/press method of predicting the sugar yield from cane for use 
in payment. Sugar J. 54(9):2-7. 

8. Salter, B. and G.D. Bonnett. 2000. High soil nitrate concentrations during autumn and 
winter increase suckering. Proc. Australian Soc. Sugar Cane Technol. 22:322-327. 

9. Tanimoto, T. 1964. The press method of cane analysis. Hawaii, Plant. Rec. 57(2): 133- 150. 



47 



Gravois et al.: Cultivar and crop effects of sugarcane bull shoots on sugarcane yield in Louisiana. 



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48 






Journal American Society of Sugarcane Technologists, Vol. 22, 2001 

Table 2. Trait means by year and cultivar for the 1998-1999 USD A Ardoyne Farm tests 









— -1998 










Sucrose 


Cane 


Sucrose 


Stalk 


Stalk 


Fiber 


Cultivar 


yield 


yield 


concentration 


number 


weight 


content 




(Mg/ha) 


(Mg/ha) 


(g/kg) 


(No./ha) 


(kg) 


(g/kg) 


Bull Shoots (Short) 1 














CP 70-321 


0.095 


4.9 


19.3 


9639 


0.46 


164.8 


CP 72-370 


0.003 


4.4 


0.7 


11432 


0.39 


168.8 


LHo 83-153 


-0.006 


1.1 


-5.7 


4707 


0.26 


156.8 


LCP 85-384 


-0.001 


4.6 


-0.2 


12328 


0.42 


152.6 


HoCP 85-845 


-0.019 


6.9 


-2.8 


15018 


0.46 


146.5 


LSD(0.05) 


NS 


NS 


2.3 


NS 


NS 


10.0 


Bull Shoots (Tall) 1 














CP 70-321 


0.183 


5.8 


31.6 


6052 


0.92 


163.3 


CP 72-370 


0.560 


14.8 


40.4 


9863 


1.29 


164.5 


LHo 83-153 


0.007 


1.2 


5.9 


1121 


0.21 


134.5 


LCP 85-384 


0.073 


3.7 


19.8 


4483 


0.66 


130.9 


HoCP 85-845 


0.701 


19.1 


36.7 


13225 


1.46 


165.3 


LSD(0.05) 


0.500 


12.9 


10.6 


NS 


0.35 


62.9 


Bull Shoots (Total) 














CP 70-321 


0.278 


10.7 


26.0 


15691 


0.74 


163.7 


CP 72-370 


0.447 


19.2 


23.3 


21295 


0.96 


165.6 


LHo 83-153 


0.008 


2.3 


3.6 


2690 


0.17 


133.8 


LCP 85-384 


0.082 


8.3 


9.9 


15916 


0.49 


125.8 


HoCP 85-845 


0.697 


26.0 


26.8 


28244 


1.21 


160.3 


LSD(0.05) 


NS 


NS 


8.4 


NS 


NS 


60.8 


Whole Stalks 














CP 70-321 


11.276 


93.5 


120.6 


59625 


1.56 


173.1 


CP 72-370 


12.354 


103.9 


118.9 


71505 


1.46 


178.1 


LHo 83-153 


13.983 


109.5 


127.7 


81367 


1.36 


164.0 


LCP 85-384 


14.850 


116.2 


127.8 


85178 


1.37 


159.9 


HoCP 85-845 


11.120 


94.8 


117.3 


66349 


1.43 


191.8 


LSD(0.05) 


NS 


20.5 


5.3 


16206 


0.14 


9.1 


Total Stalks 














CP 70-321 


11.545 


104.2 


110.8 


75316 


1.48 


172.1 


CP 72-370 


12.801 


123.1 


104.0 


92800 


1.38 


176.2 


LHo 83-153 


14.064 


111.8 


125.8 


84057 


1.34 


162.0 


LCP 85-384 


14.977 


124.5 


120.3 


101094 


1.29 


157.7 


HoCP 85-845 


11.814 


120.8 


97.8 


94593 


1.38 


185.0 


LSD (0.05) 


NS 


19.4 


4.8 


15191 


0.11 


8.6 



49 



Gravois et al.: Cultivar and crop effects of sugarcane bull shoots on sugarcane yield in Louisiana. 



Table 2. cont'd. 



1 Length of short bull shoots was under one meter, and the length of tall bull shoots was over one 
meter. 



50 









—1999 










Sucrose 


Cane 


Sucrose 


Stalk 


Stalk 


Fiber 


Cultivar 


yield 


yield 


concentration 


number 


weight 


content 




(Mg/ha) 


(Mg/ha) 


(R/kg) 


(No./ha) 


(kg) 


(g/kg) 


Bull Shoots (Short) 1 














CP 70-321 


0.053 


2.3 


23.0 


12553 


0.20 


136.5 


LHo 83-153 


0.016 


1.8 


8.9 


13001 


0.12 


137.3 


LCP 85-384 


0.013 


1.1 


11.7 


8966 


0.13 


127.3 


HoCP 85-845 


0.012 


3.4 


3.6 


12777 


0.29 


133.2 


LSD(0.05) 


0.015 


1.2 


5.4 


NS 


0.10 


6.8 


Bull Shoots (Tall/ 














CP 70-321 


0.069 


2.2 


31.3 


4707 


0.57 


112.6 


LHo 83-153 


0.083 


1.9 


43.8 


2017 


0.95 


131.8 


LCP 85-384 


0.032 


1.2 


26.5 


1569 


0.48 


73.1 


HoCP 85-845 


0.246 


8.3 


29.6 


16139 


0.59 


136.6 


LSD(0.05) 


0.095 


2.2 


NS 


6158 


NS 


NS 


Bull Shoots (Total) 














CP 70-321 


0.114 


4.5 


25.3 


14571 


0.36 


110.6 


LHo 83-153 


0.106 


3.7 


28.7 


15019 


0.62 


134.8 


LCP 85-384 


0.042 


2.3 


18.4 


6950 


0.30 


73.3 


HoCP 85-845 


0.260 


11.7 


22.2 


28917 


0.52 


135.5 


LSD(0.05) 


0.106 


3.4 


13.6 


10485 


NS 


56.7 


Whole Stalks 














CP 70-321 


8.823 


64.4 


137.0 


55814 


1.15 


145.6 


LHo 83-153 


11.846 


85.1 


139.2 


75539 


1.13 


133.6 


LCP 85-384 


14.058 


105.3 


133.5 


91678 


1.16 


151.8 


HoCP 85-845 


12.228 


97.9 


124.9 


69487 


1.40 


157.0 


LSD(0.05) 


3.390 


26.1 


1.9 


14738 


NS 


NS 


Total Stalks 














CP 70-321 


8.991 


68.9 


130.5 


70385 


1.10 


143.6 


LHo 83-153 


11.935 


88.8 


134.4 


90558 


1.11 


133.5 


LCP 85-384 


14.117 


107.6 


131.2 


98628 


1.14 


150.2 


HoCP 85-845 


12.483 


109.6 


113.9 


98404 


1.31 


154.7 


LSD(0.05) 


3.140 


27.3 


2.2 


13001 


NS 


NS 



Journal American Socierv of Suearcane Technologists, Vol. 22, 2001 



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51 



Gravois et al.: Cultivar and crop effects of sugarcane bull shoots on sugarcane yield in Louisiana. 

Table 4. Trait means by crop for the Joel Landry Farm test conducted during 1998 1 . 





Sucrose 


Cane 


Sucrose 


Stalk 


Stalk 


Fiber 


Stalk Type 


yield 


yield 


concentration 


number 


weight 


content 




(Mg/ha) 


(Mg/ha) 


(g/kg) 


(No./ha) 


(kg) 


(g/kg) 


Plantcane 














Whole stalk 


9.35 


82.5 


113.3 


76959 


1.06 


194.5 


Bull shoots 


1.55 


16.4 


94.7 


23909 


0.68 


138.6 


Total 


10.90 


98.9 


110.2 


100868 


0.97 


181.5 


LSD (0.05) 


1.83 


16.9 


18.3 


8490 


0.09 


5.1 


First ratoon 














Whole stalk 


11.59 


92.0 


126.0 


95639 


0.96 


195.1 


Bull shoots 


0.59 


12.3 


48.3 


26898 


0.44 


154.9 


Total 


12.18 


104.3 


116.8 


122537 


0.85 


186.0 


LSD (0.05) 


0.52 


6.7 


14.5 


8781 


0.09 


18.0 



'LSD values to compare two main-plot (crop) means at the same or different sub-plot (stalk type) 
treatments are 1 .77 Mg/ha for sucrose yield, 5.7 g/kg for sucrose concentration, 7179 No./ha for 
stalk number, 0.06 kg for stalk weight, and 5.9 g/kg for fiber content. 



52 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002. 

ECONOMICALLY OPTIMAL CROP CYCLE LENGTH 
FOR MAJOR SUGARCANE VARIETIES IN LOUISIANA 

Michael E. Salassi and Janis Breaux 

Department of Agricultural Economics and Agribusiness 
LSU Agricultural Center, Baton Rouge, LA 70803 

ABSTRACT 

The widespread adoption of the high-yielding variety LCP85-384 has resulted in two significant changes 
in the production sector of the Louisiana sugarcane industry. Plant characteristics of this variety make 
it very suitable for combine harvesting and have helped promote the conversion from wholestalk 
harvesting to combine harvesting in the state. Secondly, the variety is also an excellent stubbling variety, 
resulting in the expansion of standard sugarcane crop cycles beyond harvest of second stubble. Outfield 
trial yield data over the 1 996-2000 period for major sugarcane varieties produced in Louisiana were used 
to determine the optimal crop cycle length which would maximize the net present value of producer 
returns. Cane yield and sugar per ton data for plantcane through third stubble were used to estimate the 
annualized net return of crop cycles through harvest of second and third stubble and to determine the 
breakeven level of fourth stubble yields which would justify production and harvest. Analysis of yield 
and net return data for the varieties CP 70-321, LCP 85-384, and HoCP 85-845 indicated that minimum 
yield levels necessary to keep older stubble in production for harvest depend directly upon the yields of 
the prior crop cycle phases and differ significantly across varieties. 

INTRODUCTION 

The production sector of the Louisiana sugarcane industry has undergone tremendous change over 
the past few years. Many sugarcane producers have switched from the use of wholestalk harvesters to 
combine harvesters. The performance rate difference between these two harvesters, coupled with the 
relatively more perishable billeted sugarcane, has caused producers and mills to look more closely at the 
timing and scheduling of sugarcane harvesting, transport, and milling operations. The release of the 
variety LCP 85-384 in 1993 has resulted in substantial changes in the sugarcane varieties grown in 
Louisiana. This variety is a high yielding variety with excellent stubbling ability (Legendre, 2000). In 
1 995, the leading sugarcane variety grown in Louisiana was CP 70-32 1 , accounting for 49 percent of total 
acreage (Gravois, 1999). Other leading varieties produced included CP 65-357 and LCP 82-89, 
representing 15 percent and 13 percent of total state acreage, respectively. Acreage of LCP 85-384 only 
accounted for 3 percent of total sugarcane acreage in 1995. By 2000, acreage of LCP 85-384 had 
increased to 71 percent of total state sugarcane acreage. CP 70-321 and HoCP 85-845 were the second 
and third leading varieties produced in 2000 with only 14 percent and 8 percent of total acreage, 
respectively. Partly due to the widespread adoption of LCP 85-384 as well as the expansion of sugarcane 
into new production areas, total sugarcane acreage in Louisiana has increased from 370,000 acres in 1 996 
to 490,000 acres in 2000 (USD A, 2001). Total sugar production over the four-year period increased by 
57 percent to 1.65 million tons of sugar, raw value. 

The widespread adoption of the variety LCP 85-384 has caused producers to reevaluate the 
number of stubble crops to keep in production before plowing out and replanting. Traditionally, most 
sugarcane producers in Louisiana would harvest a plantcane crop and two stubble crops and then plow 

53 



anner: 

Time period 


Item 


Cashflow 





Planting costs 


PC 


1 


Plantcane net returns 


Rl 


2 


First stubble net returns 


R2 


3 


Second stubble net returns 


R3 


4 


Third stubble net returns 


R4 



n 



n-1 stubble net returns Rn 



At the beginning of the crop cycle, planting costs per acre (PC) are incurred with harvest beginning 
the following year. Net returns per acre to the producer are then received for the harvest of plantcane 

54 






Selassi and Breaux: Economically Optimal Crop Cycle Length for Major Sugarcane Varieties in Louisisana 

out the stubble after harvest of the second stubble crop. As a result of the excellent stubbling ability of 
LCP 85-384, producers are now considering such production decisions as how long should stubble crops 
be kept in production before plowing out or whether a stubble crop should be kept in production if a net 
profit could be made from its harvest. Although these questions are currently related to the production 
of LCP 85-384 in Louisiana, this basic production decision is relevant to the production of any sugarcane 
variety in any region or location. 

Crane et al. (1980, 1982) developed a conceptual model of the stubble replacement decision for 
sugarcane production in Florida. Yield prediction equations (Alvarez et al., 1982) were estimated and 
integrated into a decision model of the stubble replacement problem for sugarcane varieties grown in 
Florida at that time. A more recent study in Louisiana used net present value methods to estimate the 
economic returns from the production of sugarcane varieties over an entire crop cycle (Salassi and 
Milligan, 1997). This study utilized data from advanced variety trials conducted at ten locations across 
Louisiana from 1990 through 1994. 

The basic purpose of this article is to outline a methodology which can be used to determine the 
optimal number of sugarcane stubble crops to keep in production with the goal of maximizing producer 
net returns. Time value of money concepts are presented for purposes of evaluating the total cash flow 
of a sugarcane crop cycle over a multiyear period. Plantcane and stubble crop yields from outfield tests 
are then used to determine the optimal number of stubble crops for three major sugarcane varieties 
currently produced in Louisiana. 

MATERIALS AND METHODS 

Economic evaluation of sugarcane crop cycle length is generally concerned with determining the 
optimal length of a crop cycle which would maximize economic returns. More specifically, it involves 
the determination of when to plow out the existing stubble crop and replant to start a new crop cycle. The 
objective is to determine the optimal number of sugarcane stubble crops to harvest which would 
maximize average net returns to the producer over the entire crop cycle. Therefore, planting costs, 
cultivation and harvest costs, as well as yields and raw sugar prices, must be considered over the entire 
crop cycle. In order to correctly evaluate stubble decisions, the total cash flow from a sugarcane crop 
cycle, along with the appropriate adjustments for the time value of money, must be considered. 

The cash flow stream from a sugarcane crop cycle can be depicted in the following 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002. 

(Rl) through the final stubble crop harvest (Rn). The decision faced by the producer is when to end 
the crop cycle with the objective of maximizing net returns. This problem is a farm management 
example of investment analysis, in which a sum of money is invested which yields annual net returns 
in the following years (Boehlje and Eidman, 1984; Kay and Edwards, 1999). 

The net present value (NPV) of a crop cycle income stream can be represented as: 
NPV = Rl + R2 + R3 + R4 + ... Rn - PC 

(1+r) 1 (1+r) 2 (1+r) 3 (1+r) 4 (l+r) n 

or 
n 
NPV= £(l+r)- l R t -PC 
t=l 

where NPV is the net present value per acre of the income stream, Rl is the net returns per acre from 
plantcane, R2 is the net returns per acre from first stubble, R3 is the net returns per acre from second 
stubble, PC is the initial planting cost per acre, and r is a discount rate. The NPV of income from 
a crop cycle can be interpreted as the total income from harvest of plantcane and stubble crops less 
planting costs and all cultivation and harvest costs incurred adjusted for the time value of money. 



In order to compare the relative profitability of different crop cycles and to determine 
breakeven yields and sugar prices required to keep a stubble crop in production for harvest, the NPV 
of the income stream must be annualized This annualized value (ANPV) can be obtained by 
multiplying the NPV estimate by a capital recovery factor: 

n 
ANPV= [r/l-(l+r) n ] x £ (1 + r) 1 R , - PC 

t=l 

The annualized net present value (ANPV) of a crop cycle income stream can be interpreted as the 
average net return per year over a particular crop cycle. This is the net income estimate that should 
be maximized in order to maximize returns from a crop cycle. The decision rule which can be used 
would state that a sugarcane stubble crop should be kept in production for harvest if the net returns 
from harvest of that crop would increase the ANPV of the crop cycle income stream. If harvest of 
the stubble crop would result in a decrease in the average annualized net income, it should be plowed 
out even if a profit could be made from its harvest. Positive net returns from older stubble crops are 
no guarantee that average net returns are being maximized. 

To evaluate optimal sugarcane crop cycle length for major varieties produced in Louisiana, 
yield data for plantcane through third stubble crops were obtained from outfield tests conducted by 
the LSU Agricultural Center, the USDA Sugarcane Research Unit, and the American Sugar Cane 
League over the 1 996-2000 period. Sugar per acre, cane yield in tons per acre, and sugar per ton 
values for the varieties CP 70-321, LCP 85-384, and HoCP 85-845 are shown in Table 1. Net 
returns per acre to the producer were estimated for a raw sugar price of 1 9 cents per pound and with 
a 30 pound per ton reduction in sugar per ton to reflect a 10 percent trash content in commercially 
recoverable sugar (CRS). Estimated production costs for various phases of the sugarcane production 

55 



Selassi and Breaux: Economically Optimal Crop Cycle Length for Major Sugarcane Varieties in Louisisana 

cycle in Louisiana were taken from published 2001 estimates (Breaux and Salassi, 2001). Present 
value of net returns were calculated using a five percent discount rate. Total planting costs per acre 
of production cane is shown in Table 2 and includes all costs associated with fallow and seedbed 
preparation, purchase and expansion of seedcane, as well as the final mechanical planting of 
production cane. 

RESULTS AND DISCUSSION 

Total NPV and ANPV estimates of net returns were estimated for the varieties CP 70-321, 
LCP 85-384, and HoCP 85-845 for crop cycles extending through harvest of second and third stubble 
(Tables 3-5). Planting cost and production cost estimates for 2001 were used in the analysis. Based 
on the sugar yields used in this analysis, producer net returns would be maximized in the production 
of all three varieties by extending the crop cycle through harvest of at least third stubble. 

Sugar per acre yields for CP 70-321, adjusted for average trash content, ranged from 7,020 
pounds per acre for plantcane to 5,663 pounds per acre for third stubble (Table 3). Harvest through 
second stubble yielded a NPV of $39 per acre and a ANPV of $14 per acre. Estimated net returns 
per acre from a third stubble crop were $96 per acre, which is higher than the ANPV through second 
stubble. Therefore, the average net returns over the crop cycle could be increased by extending the 
crop cycle through harvest of a third stubble crop. After factoring in third stubble net returns, the 
NPV of the crop cycle increased to $1 18 per acre, or $33 per acre per year. 

Higher sugar per acre yields for LCP 85-384 resulted in higher estimates of net returns per 
acre compared to other varieties. With plantcane, first stubble, and second stubble sugar per acre 
yields above 7,400 pounds, the NPV of net returns of a crop cycle through harvest of second stubble 
was estimated to be $379 per acre, or an average of $139 per acre per year of harvest (Table 4). 
Third stubble yield of 6,973 pounds of sugar per acre resulted in producer net returns of $221 per 
acre, higher than the ANPV through second stubble. Extension of the crop cycle through a third 
stubble harvest increased NPV of net returns to $562 per acre, or $1 58 per acre on an annual basis. 

The NPV of crop cycle net returns for HoCP 85-845 were estimated to be $127 per acre 
through harvest of second stubble and $336 per acre through harvest of third stubble (Table 5). 
Commercially recoverable sugar per acre yields declined to 6,622 pounds for second stubble but 
increased to 7,3 14 pounds for third stubble. As a result, extension of the crop cycle through harvest 
of a third stubble crop increased annual net returns by $48 per acre. 

Although no yield data were available for fourth stubble yields, breakeven sugar yields 
required to economically justify harvest of a fourth stubble crop were estimated for each of the three 
varieties at two different raw sugar price levels (Table 6). In order to maximize net returns over the 
crop cycle, a fourth stubble crop should be kept in production for harvest only if the projected net 
returns per acre equal or exceed the ANPV through third stubble. Average CRS values for each 
variety were used to determine breakeven sugar per acre and tonnage per acre values for a fourth 
stubble crop. At a raw sugar price of 1 9 cents per pound, breakeven fourth stubble sugar yields were 
estimated to be 5,010 pounds per acre for CP 70-321, 6,314 pounds per acre for LCP 85-384, and 
5,651 pounds per acre for HoCP 85-845. An increase in projected raw sugar price to 21 cents per 
pound lowered the required breakeven sugar per acre yields by approximately 500 pounds. 

56 









Journal American Society of Sugarcane Technologists, Vol. 22, 2002. 

CONCLUSIONS 

In order to maximize economic net returns from the production of sugarcane, the optimal 
length of a crop cycle must be determined. This article presented a methodology for determining the 
optimal crop cycle length for sugarcane grown in any location. Outfield yield data through third 
stubble were used to determine optimal crop cycle length for three major varieties of sugarcane 
grown in Louisiana. Breakeven yields required to economically justify harvest of a fourth stubble 
crop were also estimated. Although sugarcane yield data through harvest of third stubble used in this 
study were the most comprehensive data available for the varieties studied, the time period 
represented by these data is relatively short (1996-2000). This may be a limitation to the results 
presented here and suggests that this area needs additional research as more time series data becomes 
available. 

Three general conclusions can be drawn from this analysis. First, the economically optimal 
sugarcane crop cycle length is one which maximizes average net returns per acre over the entire crop 
cycle. Net returns over a multiyear crop cycle should be adjusted for the time value of money, 
thereby annualizing the total NPV of returns over the years of harvest. A decision rule which can 
be used to evaluate older stubble would state that a stubble crop should be kept in production for 
harvest only if the net returns from that crop would increase the average net returns over the crop 
cycle. Positive net returns from harvest of older stubble is no guarantee that average returns are 
being maximized. Secondly, economic evaluation of keeping older stubble in production is variety- 
and field-specific. Varieties with different yields and production costs will have different breakeven 
yields. Finally, when considering whether to keep current fields of older stubble in production, 
include the impact of varying sugar prices and yields. Higher (lower) projected stubble crop yields 
decrease (increase) required breakeven sugar prices. Lower (higher) projected sugar prices increase 
(decrease) required breakeven stubble crop yields. 



REFERENCES 

1. Alvarez, J., D. R. Crane, T. H. Spreen, and G. Kidder. 1982. A yield prediction model for 
Florida sugarcane. Agricultural Systems. 9:161-179. 

2. Boehlje, Michael D., and Vernon R. Eidman. 1984. Farm Management (chapter 8). John 
Wiley and Sons, New York. 

3. Breaux, Janis, and Michael E. Salassi. 2001. Projected costs and returns - sugarcane, 
Louisiana, 2001. LSU Agricultural Center, Department of Agricultural Economics and 
Agribusiness, A.E.A. Information Series No. 192. 

4. Crane, Donald R., and Thomas H. Spreen. 1980. A model of the stubble replacement 
decision for Florida sugarcane growers. Southern Journal of Agricultural Economics. 12:55- 
64. 



57 



Selassi and Breaux: Economically Optimal Crop Cycle Length for Major Sugarcane Varieties in Louisisana 

5. Crane, D.R., T.H. Spreen, J. Alvarez, and G. Kidder. 1982. An analysis of the stubble 
replacement decision for Florida sugarcane growers. University of Florida Agricultural 
Experiment Station Bulletin No. 882. 

6. Gravois, Kenneth. 1999. The 1999 Louisiana sugarcane variety survey. Sugarcane research 
annual progress report, 1999. Louisiana Agricultural Experiment Station, Louisiana State 
University Agricultural Center, Baton Rouge, LA., pp. 91-96. 

7. Kay, Ronald D., and William M. Edwards. 1999. Farm Management, 4 th edition. 
WCB/McGraw-Hill, New York. 

8. Legendre, Benjamin L. 2000. Sugarcane planting recommendations and suggestions. 
Louisiana Cooperative Extension Service, Louisiana State University Agricultural Center, 
Baton Rouge, LA. 

9. Salassi, M. E., and S. B. Milligan. 1997. Economic analysis of sugarcane variety selection, 
crop yield patterns, and ratoon crop plow out decisions. Journal of Production Agriculture. 
10:539-545. 

1 0. United States Department of Agriculture. 200 1 . Sugar and Sweetener Situation and Outlook 
Report. Economic Research Service, SSS-230, January. 









58 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002. 



Table 1. Mean sugarcane yields for three commercial varieties across locations, 1996-2000. 



Variety 



Sugar per acre 



Cane yield 



Sugar per ton 



Plantcane. 1996-2000 : 

CP 70-321 
LCP 85-384 
HoCP 85-845 

First stubble. 1996-2000 : 

CP 70-321 
LCP 85-384 
HoCP 85-845 

Second stubble. 1996-2000 : 

CP 70-321 
LCP 85-384 
HoCP 85-845 

Third stubble. 1997-2000 : 

CP 70-321 
LCP 85-384 
HoCP 85-845 



(lbs. /acre) 



(tons/acre) 



7899 


30.0 


8919 


33.1 


7898 


32.3 


7771 


29.0 


9414 


34.5 


8115 


31.5 


6452 


25.3 


8429 


32.0 


7574 


30.1 


6354 


24.2 


7847 


29.3 


8215 


31.8 



(lbs. /ton) 



264 
270 
245 



269 

273 
257 



256 
264 
250 



264 
268 
260 



Table 2. Total sugarcane planting costs per acre. 



Cost per acre Percent of acre Total cost per acre 



Cost item : 

Fallow / seedbed preparation 
Cultured seedcane 
Hand planting seedcane 
Propagated seedcane 
Mechanical planting seedcane 
Total planting cost 



per acre) 


(%) (d 


ollars per acre) 


231.61 


1.00 


231.61 


499.75 


0.03 


17.77 


250.78 


0.03 


8.92 


73.91 


0.19 


15.02 


162.01 


0.97 


156.78 



430.11 



Planting cost allocation based on an initial planting of 0.032 acres of cultured seedcane followed by 
two seedcane expansions using a 5:1 planting ratio. 



59 



Selassi and Breaux: Economically Optimal Crop Cycle Length for Major Sugarcane Varieties in Louisisana 

Table 3. Annualized crop cycle net returns for CP 70-321. 



Crop cycle phase 


Recoverable 


Harvest 


through 


Harvest 


through 




sugar yield 


second stubble 


third stubble 




(lbs. per acre) 




(dollars 


per acre) 




Fallow / Plant a 


— 




($430) 




($430) 


Plantcane b 


7020 




$181 




$181 


First stubble b 


6931 




$231 




$231 


Second stubble b 


5718 




$101 




$101 


Third stubble b 


5663 




~ 




$96 


NPV of total returns 


~ 




$39 




$118 


ANPV of total returns' 1 


— 




$14 




$33 





a Nominal fallow, seedbed preparation and planting cost. 

b Nominal net returns per acre above cultivation and harvest costs. 

c Net present value of total net returns over crop cycle. 

d Annualized net present value of net returns. 

Table 4. Annualized crop cycle net returns for LCP 85-384. 



Crop cycle phase 


Recoverable 
sugar yield 


Harvest through Harvest through 
second stubble third stubble 




(lbs 


per acre) 


(dollars per acre) 




Fallow / Plant a 




— 


($430) 


($430) 


Plantcane b 




7944 


$252 


$252 


First stubble b 




8384 


$370 


$370 


Second stubble b 




7488 


$271 


$271 


Third stubble b 




6973 


— 


$221 


NPV of total returns 




~ 


$379 


$562 


ANPV of total returns' 1 




— 


$139 


$158 





a Nominal fallow, seedbed preparation and planting cost. 

b Nominal net returns per acre above cultivation and harvest costs. 

Net present value of total net returns over crop cycle. 

d Annualized net present value of net returns. 









60 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002. 

Table 5. Annualized crop cycle net returns for HoCP 85-845. 



Crop cycle phase 


Recoverable 
sugar yield 


Harvest through 
second stubble 


Harvest through 
third stubble 




(lbs. 


per acre) 




(dollars 


per acre) 




Fallow / Plant a 




— 




($430) 




($430) 


Plantcane b 




6945 




$175 




$175 


First stubble b 




7151 




$252 




$252 


Second stubble b 




6622 




$188 




$188 


Third stubble b 




7314 




— 




$254 


NPV of total returns c 




— 




$127 




$336 


ANPV of total returns d 




— 




$47 




$95 



a Nominal fallow, seedbed preparation and planting cost. 

b Nominal net returns per acre above cultivation and harvest costs. 

c Net present value of total net returns over crop cycle. 

d Annualized net present value of net returns. 



Table 6. Breakeven fourth stubble yields for three major varieties. 



Fourth stubble yield 



CP 70-321 



LCP 85-384 



HoCP 85-845 



ANPV a (third stubble) 



$33 



$158 



$95 



Breakeven yield : 
Sugar per acre (190) 
Avg. CRS b 
Est. tons per acre 



5010 

233 

21.5 



6314 
239 
26.4 



5651 

223 
25.3 



Sugar per acre (2 1 f) 
Avg. CRS b 
Est. tons per acre 



4546 
233 
19.5 



5731 
239 
24.0 



5129 

223 
23.0 



a Annualized net present value of net returns. 

b Average commercially recoverable sugar in pounds per ton of cane. 



61 



Grigg et al.: Seasonally Maintained Shallow Water Tables Improve Sustainability of Histosols Planted to Sugarcane 

SEASONALLY MAINTAINED SHALLOW WATER TABLES IMPROVE 
SUSTAINABILITY OF HISTOSOLS PLANTED TO SUGARCANE 

Brandon C. Grigg 

Soil and Water Research Unit, USDA-ARS, Baton Rouge, LA 70808 

George H. Snyder 

Everglades Research and Education Center 
University of Florida, IFAS, Belle Glade, FL 33430 

Jimmy D. Miller 

Sugarcane Field Station, USDA-ARS, Canal Point, FL 33438 

ABSTRACT 

Subsidence of Histosols, caused by microbial degradation of these drained soils, is a major 
concern in the Everglades Agricultural Area (E AA) of south Florida. Our obj ective was to determine 
if seasonal maintenance of shallow water tables would effectively decrease soil degradation and 
subsidence while allowing conventional production of sugarcane (Saccharum spp.). We compared 
the effects of seasonally maintained water tables at 0.15 and 0.40 m depths, and the currently 
practiced 0.60 m depth, on microbial degradation of a Lauderhill soil (Lithic Medisaprist). We 
maintained seasonal water tables from the beginning of May through September during the typical 
wet season. Fields were drained to or below 0.6 m from the soil surface during the remainder of the 
year to allow for conventional harvest and cultural management. We took surface soil samples 
bimonthly, applied the substrate 14 C-benzoate, and monitored 14 C0 2 respiration as an indicator of 
Histosol degradation. Seasonally maintained water tables at 0.15 and 0.40 m reduced microbial 
degradation of the organic soil, resulting in modeled subsidence rates of 1.4 cm y" 1 and 2.0 cm y' 1 , 
respectively, when compared to 4.3 cm y" ' for the conventional 0.6 m depth. Decreased soil 
degradation and increased sustainability resulting from shallow water table maintenance was a direct 
result of increased soil water content and the corresponding decrease in air-filled pore space. 
Seasonal maintenance of shallow water tables appears compatible with current production practices 
for sugarcane, and will enable significant conservation of EAA Histosols. 

INTRODUCTION 

Histosols, the organic soils common to the EAA, are fertile, with high native carbon (C), 
nitrogen (N), and phosphorus (P) levels. Conventional agricultural practices for sugarcane 
production in the EAA include maintenance of water tables at or below 0.6 m from the soil surface. 
The aerobic soil environment created by agricultural drainage enables microbial mineralization of 
the organic soil, and release of C, N, and P for microbial and plant uptake. Off-loading of excess N 
and P resulting from soil mineralization has been addressed through development and adoption of 
on-farm management practices (Izuno et. al., 1995). During soil mineralization, the rate of C lost 
as carbon dioxide (C0 2 ) exceeds the rate of C attenuation and storage. This results in land 
subsidence of up to 4 cm y" 1 (Stephens and Johnson, 1951; Stephens et al., 1984). However, no 
sugarcane management practices have been adopted to address the land subsidence issue. 

62 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Considering the economic impact of sugarcane production on the EAA region and the state 
(Schueneman, 1 998), it is important to maintain sugarcane production in this region. However, it 
is also important to explore sugarcane management practices that ensure soil resource and 
environmental sustainability. One way to reduce microbial degradation and to increase soil resource 
sustainability is to maintain shallow water tables. This practice would decrease aerobic soil 
degradation of the organic soil, primarily by reducing the air-filled pore space and the oxygen (0 2 ) 
available. 

Past research shows that sugarcane is tolerant of, and can be successfully grown in, soils with 
a seasonally maintained shallow water table (Gascho and Shih, 1979; Kang et. al., 1986; Snyder et. 
al., 1978). However, past research relating shallow water table management to soil sustainability 
of EAA Histosols considers only full-season water table maintenance (Stephens and Johnson, 1951; 
Volk, 1972). The impacts of seasonally maintained water tables on Histosol sustainability are not 
adequately quantified. We suggest that seasonally maintained shallow water tables can substantially 
improve soil sustainability, while allowing for current crop management practices and yield. Our 
objective was to assay the effects of seasonal shallow water table management on soil sustainability. 

MATERIALS AND METHODS 

The research site was established in 1997 near South Bay, FL (Figure 1) and consisted of 
seven 6.7 ha fields (180 m x 370 m). The organic soil was a Lauderhill muck soil (Lithic 
Medisaprist). Bulk density and particle density were determined in the lab and were then used to 
determine pore space by calculation (Blake and Hartge, 1 986a; Blake and Hartge, 1 986b; Danielson 
and Sutherland, 1986). 

Three fields under water table management, one each at target water table depths of 0.15 
(WT-1), 0.40 (WT-2), and 0.60 m (WT-3) below soil surface (Figure 2), were planted to sugarcane 
and were separated by four unplanted buffer fields of equal size. Water tables in each field were 
controlled at the previously mentioned depths using automatically-controlled, diesel-powered pumps 
positioned at the supply canal inlet and outlet for each experimental field. In response to needs 
expressed by Glaz ( 1 995), water tables were maintained from approximately May (following Spring 
germination and stand establishment) through September (Figure 2). This corresponds with the 
warm, high-rainfall portion of the growing season. During the remainder of the year, fields were 
drained, with a target water table depth of 0.6 m (Figure 2) to allow for conventional harvest and 
cultural practices. 

Using a stainless steel bucket auger (0.07 m diameter), field soil samples were collected 
every two months from the surface 0.00-0. 15m of the soil profile, midway between sugarcane rows. 
We weighed triplicate soil samples, dried them in a 105°C oven for 24 h, and determined soil water 
content by difference. 

Tate (1979a and 1979b) used a substrate-induced respiration assay to successfully model 
effects of flooded management on microbial decomposition of Histosols of the EAA. We modified 
the assay, using benzoate instead of salicylate to model organic soil mineralization, as suggested by 
Williams and Crawford (1 983). Williams and Crawford ( 1 983) successfully used benzoate to model 

63 



Grigg et al.: Seasonally Maintained Shallow Water Tables Improve Sustainability of Histosols Planted to Sugarcane 

degradation of peat similar in many respects to Histosols of the EAA. In concurrent studies the 
benzoate assay was sensitive to changes in water management on EAA Histosols (data not shown). 
We applied 14 C(carboxyl)-benzoate at a rate of 861 MBq kg" 1 wet soil (specific activity, 577MBq 
jimole ', Sigma Chemicals, St. Louis, MO). 

We assayed 6 homogenous soil samples from each field. We conducted substrate assays at 
room temperature (22 ± 1 ° C) within 6 h of sample collection. Substrates were mixed with 1 g (wet 
weight) of soil from each of the field samples. Samples were incubated for 2 h (Zibilske, 1994), and 
evolved C0 2 including 14 C0 2 was collected in a lMNaOH trap solution. Following incubation, we 
mixed 1 mL of the trap solution with 5 mL of scintillation cocktail (ScintoSafe Plus 50%, Fisher 
Scientific, Pittsburgh, PA) and determined rate of 14 C0 2 respired by microorganisms in the soil 
degradation process (Model LS 3801, Beckman Instruments, Fullerton, CA). 

Data were analyzed using the Analysis of Variance procedure in SAS v.8 software (SAS, 
1999), and statistical differences between means were determined using Fisher's LSD (a=0.05). 
Regression analysis was also conducted using the SAS v.8 software. 

RESULTS AND DISCUSSION 

Seasonal shallow water table maintenance treatments resulted in significant differences in 
soil water content (Table 1). Seasonal maintenance of water tables at the 0.15 m depth (WT-1) 
significantly increased water content of the surface soil. Only WT- 1 caused soil aeration to fall below 
1 % air- filled porosity (Table 1 ), a minimum volume required for adequate soil aeration and aerobic 
microbial activity (Paul and Clark, 1989). The depth to the shallow water table was highly variable 
during the free-drainage period resulting in no significant differences in soil water content, however 
there was a trend for greater soil water content and decreased air-filled porosity with the seasonal 
WT-1 treatment when compared to either WT-2 or WT-3 treatments (Table 1). While the seasonal 
shallow water tables were maintained, WT-2 increased soil water content in comparison to 
conventional water table management (WT-3). This difference was not significant at the a=0.05 
level, but was significant at the a=0.10 level. 

Assay results (Table 2) indicated shifts in responses to changes in water table management 
similar in magnitude to those for gross respiration reported by Volk (1972), who evaluated water 
table impacts on subsidence of EAA Histosols in lysimeters with re-packed soil. During periods of 
shallow water table maintenance, the conventional water management practice (WT-3) resulted in 
the greatest assayed microbial activities (Table 2 and Figure 3). 

Elevated assay results associated with conventional management (WT-3) indicate 
significantly reduced sustainability of the organic soil relative to either WT-1 or WT-2, the 
seasonally maintained shallow water tables. Moreover, when compared to WT-3, seasonal shallow 
water table treatments generally improved sustainability of organic matter throughout the periods 
of free drainage (Table 2). We maintained shallow water tables for only four to five months during 
the warm, wet portion of each year. This suggests that WT-1 and WT-2 result in residual 
suppression of soil degradation which has not been previously reported for Histosols of the EAA 



64 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

region. This is likely a result of reduced aerobic microbial populations during the beginning of the 
free drainage periods (Table 1). 

The WT-1 treatment resulted in greater overall Histosol sustainability when compared to 
WT-2 (Table 2). However, maintenance of either WT-1 or WT-2 decreased microbial degradation 
of the organic soil by up to 50 % when compared to WT-3. This in turn suggests that WT-1 and 
WT-2 increase Histosol sustainability by as much as two times that of WT-3, the conventional water 
management practice. 

During the short duration of this study, direct measurement of subsidence was not 
practicable. To relate our benzoate assay to soil subsidence, we regressed our benzoate assay results 
(periods under shallow water table management) on subsidence rates for full-season shallow water 
table management as reported by Stephens and Johnson (1951). This regression analysis resulted 
in the following equation: 

Subsidence = 3.63 x BA - 1.63 Adjusted R 2 = 0.90 [1] 

where subsidence is in units of cm y" 1 , and BA (benzoate assay) is in units of mmoles h" 1 Mg" 1 . We 
then fit our data for overall treatment effects to equation [ 1 ] , resulting in modeled overall subsidence 
rates of 1.4 cm y" ' and 2.0 cm y 1 , for WT-1 and WT-2, respectively. The conventional water 
management practice, WT-3, resulted in an overall subsidence rate of 4.3 cm y" 1 using the same 
fitting procedure. 

These estimates are comparable to projections of Stephens and Johnson (1951) that indicate 
WT-1, WT-2 and WT-3 would result in subsidence rates of 0.6, 2.2 and 3.7 cm y" 1 , respectively, if 
maintained throughout the year. Maintaining seasonal shallow water tables for only five months out 
of a year resulted in projected subsidence rates only slightly higher than those projected by Stephens 
and Johnson (195 1) for full-season shallow water table management. Stephens and Johnson (1 95 1 ) 
used elevation changes to measure subsidence rather than an assay. This would take into account 
decomposition throughout the soil profile. Our projections likely overestimate subsidence rates for 
the entire soil profile, as they are based on assay of the surface 0.00-0.15 m of the soil profile, and 
the greatest potential soil degradation rates. Correlation of benzoate assay results with directly 
measured soil subsidence rates is needed to validate the model for the Lauderhill soil and other 
Histosols of the EAA. 

CONCLUSIONS 

As a result of maintaining seasonal shallow water tables for only five months out of a year, 
our assay indicates subsidence rates slightly greater than that projected for full-season shallow water 
table management. These data support seasonal shallow water table management as a means of 
reducing subsidence and improving sustainability of valuable EAA soil resources. Shallow water 
tables not only increase soil sustainability during the portion of the year when they are maintained, 
but can also residually increase sustainability during the harvest season when fields are drained. This 
study should be replicated on other sites with different organic soil characteristics. Improved 



65 



Grigg et al.: Seasonally Maintained Shallow Water Tables Improve Sustainability of Histosols Planted to Sugarcane 

correlation of assay results to directly measured subsidence rates should show that seasonal water 
table management is as effective as full-season maintenance in improving soil sustainability. 

Given the current sugarcane varieties and production technology, an immediate shift to full- 
season shallow water table management is not realistic without negatively influencing sugarcane 
production and the EAA and Florida agricultural economies. WT-2 appears the best fit with current 
sugarcane varieties and production technology. The WT-1 treatment provides the greatest potential 
increase in soil sustainability. Research should be conducted to develop new sugarcane varieties 
suitable for production under seasonally maintained shallow water tables. 

Shih and others (1997) reported decreased subsidence rates for the last 10 years based on 
changes in soil elevation on known transects throughout the EAA. They attribute decreased 
subsidence in part to shallow water table management, a result of Best Management Practice 
implementation for P off-loading (Shih et al., 1 997). Decreased soil degradation and mineralization 
would result in reduced nutrient off-loading as indicated by Davis (1991). Future research should 
also address the effects of seasonal shallow water table management on nutrient off-loading. 
Improved sugarcane management including shallow water table maintenance can be an 
environmentally and economically sound production system. As a conservation practice, seasonal 
shallow water table management could double the production life of valuable EAA soil resources. 

ACKNOWLEDGEMENTS 

We express our appreciation to the Florida Sugar Cane League, Clewiston, FL, for financial 
support, and the U.S. Sugar Corporation, Clewiston, FL, for providing and maintaining the research 
site. We thank Dr. Robert Tate HI, Department of Environmental Sciences, Rutgers University, New 
Brunswick, NJ, for consultation on methodology. We also thank Drs. Joan Dusky and Van Waddill 
of the Everglades Research and Education Center, Belle Glade, FL, for providing equipment and 
facilities for this research project. 

REFERENCES 

1. Blake, G.R., and K.H. Hartge. 1986a. Bulk Density, p. 363-375. In A. Klute (ed.). Methods 
of Soil Analysis, Part 1- Physical and Miner alogical Methods. ASA-SSSA, Madison, WL. 

2. Blake, G.R., and K.H. Hartge. 1986b. Particle Density, p. 377-382. In A. Klute (ed.). 
Methods of Soil Analysis, Part 1- Physical and Mineralogical Methods. ASA-SSSA, 
Madison, WL. 

3. Danielson, R.E., and P.L. Sutherland. 1986. Porosity, p. 443-461. In A. Klute (ed.). Methods 
of Soil Analysis, Part 1- Physical and Mineralogical Methods. ASA-SSSA, Madison, WL. 

4. Davis, S.M. 1991. Growth, decomposition, and nutrient retention of Cladium jamaicense 
Crantz and Typha domingensis Pers. in the Florida Everglades. Aquat. Bot. 40:203-224. 



66 









Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

5. Gascho, G.J., and S.F. Shih. 1979. Varietal response of sugarcane to water table depth. 1. 
Lysimeter performance and plant response. Soil and Crop Science Society of Florida 
Proceedings. 38:23-27. 

6. Glaz, B. 1995. Research seeking agricultural and ecological benefits in the Everglades. J. 
Soil Water Conserv. 50:609-612. 

7. Izuno, F.T., A.B. Bottcher, F.J. Coale, C.A. Sanchez, and D.B. Jones. 1995. Agricultural 
BMPs for phosphorus reduction in South Florida. Trans. ASAE. 38:735-744. 

8. Kang, M.S., G.H. Snyder, and J.D. Miller. 1986. Evaluation of Saccharum and related 
germplasm for tolerance to high water table on organic soil. J. Am. Soc. Sugarcane Technol. 
6:59-63. 

9. Paul, E. A., and F.E. Clark. 1 989. Soil microbiology and biochemistry. Academic Press, Inc., 
San Diego, CA. p. 17. 

10. SAS. 1999. SAS Procedures Guide, Version 8. SAS Institute, Inc., Cary, N. C, 1643 pp. 

1 1 . Schueneman, T.J. 1998. An overview of Florida sugarcane. Florida Cooperative Extension 
Service, IF AS, University of Florida, Gainesville, SS-AGR-232. 

12. Shih, S.F., B. Glaz, and R.E. Barnes, Jr. 1997. Subsidence lines revisited in the Everglades 
Agricultural Area, 1997. Agricultural Experiment Station, IF AS, University of Florida, 
Gainesville, Bulletin 902. 

13. Snyder, G.H., H.W. Burdine, J.R. Crockett, G.J. Gascho, D.S. Harrison, G. Kidder, J.W. 
Mishoe, D.L. Myhre, F.M. Pate, and S.F. Shih. 1978. Water table management for organic 
soil conservation and crop production in the Florida Everglades. Agricultural Experiment 
Station, IF AS, University of Florida, Gainesville, Bulletin 801. 

14. Stephens, J.C., L.H. Allen, Jr., and E. Chen. 1984. Organic soil subsidence. In T.L. Holzer 
(ed.). Man-induced land subsidence: Geological Society of America Reviews in Engineering 
Geology. 6:107-122. 

15. Stephens, J.C., and L. Johnson. 1951. Subsidence of organic soils in the upper Everglades 
region of Florida. Soil and Crop Sci. Soc. Fla. Proc. 1 1:191-237. 

16. Tate, R.L., Hi. 1979a. Effect of flooding on microbial activities in organic soils: carbon 
metabolism. Soil Sci. 128:267-273. 

17. Tate, R.L., HI. 1979b. Microbial activity in organic soils as affected by soil depth and crop. 
Appl. Environ. Microbiol. 37:1085-1090. 



67 



Grigg et al.: Seasonally Maintained Shallow Water Tables Improve Sustainability of Histosols Planted to Sugarcane 

1 8. Volk, B.G. 1 972. Everglades Histosol subsidence: 1 . C0 2 evolution as affected by soil type, 
temperature, and moisture. Soil and Crop Sci. Soc. Fla. Proc. 32:132-135. 

19. Williams, R.T., and Crawford, R.L. 1983. Effects of various physiochemical factors on 
microbial activity in peatlands aerobic biodegradative processes. Can. J. Microbiol. 
29:1430-1437. 

20. Zibilske, L.M. 1994. Carbon Mineralization, p. 835-863. In R.W. Weaver et al. (ed.). 
Methods of Soil Analysis, Part 2 -Microbiological and Biochemical Properties. ASA-SSSA, 
Madison, WI. 



! 



68 



■fc 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 1. Treatment impacts on soil water content and air-filled porosity for the period when 
shallow water tables were maintained, for the drained period enabling conventional harvest and 
cultivation, and for the water management practice overall. 

Average Soil Water Content [Air-Filled Porosity f ] 
Treatment Shallow Water Table Drained Overall 1 



m 3 nv 3 [%]- 



WT-1 § 0.77 [1] a 11 0.72 [6] a 0.74 [4] a 

WT-2 0.67 [11] b 0.59 [19] a 0.62 [16] b 

WT-3 0.59 [19] b 0.59 [19] a 0.59 [19] b 



f Air-filled porosity determined as the difference between calculated total porosity and volumetric 

water content. 

^Overall refers to the overall water treatment effect, being the average water content or air-filled 

porosity for the entire year, including the periods of shallow water table management and free 

drainage. 

treatments are based on the depth at which the seasonal shallow water table was maintained with 

WT-1=0.15 m depth, WT-2=0.4 m depth, and WT-3=0.6 m depth. 

Statistical comparisons are valid in a soil depth, within a column. Means followed by the same 

letter are not significantly different (Fisher's LSD, a = 0.05). 



69 



Grigg et al.: Seasonally Maintained Shallow Water Tables Improve Sustainability of Histosols Planted to Sugarcane 

Table 2. Water management impacts on the benzoate assay of soil degradation for the period when 
shallow water tables were maintained, for the drained period enabling conventional harvest and 
cultivation, and for the water management practice overall. 

Benzoate Assay of Histosol Degradation 
Treatment Shallow Water Table Drained Overall 



mmoles h" 1 Mg" 1 dry soil 

WT-1* 0.68 a § 0.97 a 0.84 a 

WT-2 0.95 b 1.05 a 1.00 b 

WT-3 1.50 b 1.71a 1.63 b 



Overall refers to the overall water treatment effect, being the average benzoate assay of Histosol 

degradation for the entire year, including the periods of shallow water table management and free 

drainage. 

^Treatments are based on the depth at which the seasonal shallow water table was maintained with 

WT-1=0.15 m depth, WT-2=0.4 m depth, and WT-3=0.6 m depth. 

Statistical comparisons are valid in a soil depth, within a column. Means followed by the same 

letter are not significantly different (Fisher's LSD, a = 0.05). 



70 



■* 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 




Figure 1 . The research site ( * ) located in the Everglades Agricultural Area lies south of Lake 
Okeechobee (shaded black) in western Palm Beach County, Florida. 



Soil Surface 





Q. 
Q 



eg 
H 



0.2 - 



0.4 



0.6 



0.8 



WT-1 



WT-2 



WT-3 



WT-1, 2, and 3 



Shallow Water Tables Maintained 



Free Drainage 



0.2 



0.4 



0.6 



0.8 



-S 
o. 

<u 

Q 

1 

Im 

<d 

•*— * 
C3 



May - September 



October - April 



Figure 2. Water table depth for each treatment [WT-1=0. 1 5 m depth, WT-2=0.4 m depth, and WT- 
3=0.6 m depth] during seasonal shallow water table maintenance and during free drainage. 



71 



Grigg et al.: Seasonally Maintained Shallow Water Tables Improve Sustainability of Histosols Planted to Sugarcane 



T 3.5 



o 
2 



Q 

UJ 

Q 

2 

o 
w 
Q 



X 

o 



3.0 - 



2.5 - 



2.0 - 



1.5 - 



< 

u l.o H 

u 



w 

< 

C 
N 

W 
03 



0.5 - 



0.0 



WT 1,0.15 m 
WT 2, 0.30 m 
WT 3, 0.60 m 

A WT Applied 
V WT Removed 




II I I I I II I I In I I I I I I I I f I I 

10/97 12/97 02/98 04/98 06/98 08/98 10/98 12/98 02/99 04/99 06/99 08/99 



SAMPLE DATE 

Figure 3. Study-long assay results as affected by water table management. Error bars indicate 
standard error of the mean. Treatments are based on the depth at which the seasonal shallow water 
table was maintained with WT-1=0.15 m depth, WT-2=0.4 m depth, and WT-3=0.6 m depth. 









72 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial 

Adoption 



Barry Glaz, Jimmy D. Miller, Peter Y.P. Tai 

USDA-ARS 
Sugarcane Field Station 
Canal Point, FL 33438 

Christopher W. Deren 

University of Florida 

Everglades Research and Education Center 

Belle Glade, FL 33430 

Manjit S. Kang 

Department of Agronomy 

Louisiana Agricultural Experiment Station 

Baton Rouge, LA 70803-21 10 

Paul M. Lyrene 

Agronomy Department 
University of Florida 
Gainesville, FL 3261 1 

and 

Bikram S. Gill 

Department of Plant Pathology 

Kansas State University 

Manhattan, KS 66505-5502. 

ABSTRACT 

The sugarcane (interspecific hybrids of Saccharum spp.) breeding and selection program in 
Canal Point (CP) Florida increased the number of genotypes advanced to its final selection stage, 
Stage IV, from 11 to 14. This change resulted from recently reported evidence that replications 
could be decreased without reducing experimental precision in Stage IV. The major purpose of this 
study was to determine if advancing an additional three new genotypes to Stage IV would improve 
the likelihood of identifying successful cultivars. A secondary objective was to determine if 
genotypes with high or mediocre yields in the penultimate stage, Stage HI, could be expected to have 
similar yields in Stage IV. Data were reviewed from 24 cycles of Stage HI, and 16 cycles of Stage 
IV. Genotype correlations between Stage JH and Stage IV were significant but low for sugar yield 
(Mg sugar ha" 1 ) (r = 0.27) and economic index ($ ha" 1 ) (r = 0.28). No genotype that ranked worse 
than 15th in both sugar yield and economic index in Stage III was later used on more than 1% of 
Florida's annual sugarcane hectarage. It is usually necessary to select from genotypes ranking worse 
than 1 5th in Stage HI to advance 1 1 genotypes to Stage IV, because genotypes are normally discarded 

73 



Glaz et al.: Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial Adoption 

due to disease susceptibility and poor agronomic type. It is unlikely that advancing more than 1 1 
genotypes from Stage III would improve the likelihood of identifying productive commercial 
cultivars, unless other changes are made that improve the quality of genotypes advanced to Stage HI. 



INTRODUCTION 

The sugarcane breeding and selection program at Canal Point, Florida is a cooperative 
program conducted by the USDA- Agricultural Research Service, the Florida Sugar Cane League, 
Inc., and the University of Florida Institute of Food and Agricultural Sciences. A previous study 
examined the final replicated testing stage (Stage IV) of the CP program (Brown and Glaz, 2001). 
Before that study, 1 1 promising genotypes were tested at 10 locations in Stage IV. Each genotype 
was replicated eight times and harvested as three annual crops, the plant-cane, first-ratoon, and 
second-ratoon crops at each location. The 1 1 promising genotypes in Stage IV were advanced from 
approximately 130 genotypes that were annually advanced from Stage II to Stage HI (Glaz et al., 
2001). Major criteria for advancement from one stage to the next are high yields, economic index, 
disease resistance or tolerance, and agronomic traits. A principal conclusion of Brown and Glaz 
(2001) was that experimental precision would remain similar in Stage IV if replications were reduced 
from eight to four. 

The Florida Sugarcane Variety Committee selects the genotypes to advance from Stage HI 
to Stage IV. This committee is composed of personnel representing growers, mills, and research and 
extension agencies participating in the CP breeding and selection program. Many criteria are 
considered in the selection process by committee members. However, most of the genotypes 
advanced to Stage IV in any given year can be classified into three groups using yield, disease, and 
agronomic criteria. The first group of genotypes has high yields and acceptable disease profiles and 
agronomic characteristics at all locations in Stage HI. The second most desirable group is composed 
of genotypes with high yields at some locations. If 1 1 genotypes are not yet selected, the remaining 
entries are selected from among genotypes that had mediocre yields in Stage HI but may have had 
some other redeeming characteristics, such as desirable agronomic traits, high theoretical recoverable 
sugar yields, or excellent disease resistance. 

The committee usually limited its selections to 1 1 genotypes due to resources assigned to 
Stage IV. However, Brown and Glaz (2001) proposed a redistribution of resources in Stage IV that 
would not compromise experimental precision and allow for testing of more genotypes. In most 
years, there were not more than 1 1 genotypes in the first two groups of genotypes advanced from 
Stage EI to Stage IV. However, several genotypes from the third group usually needed to be 
discarded when only 1 1 genotypes were advanced. 

Among the genotypes with high yields, several usually have severe disease susceptibilities. 
The committee is very strict about not advancing such genotypes to Stage IV. Due to this policy and 
the ever increasing disease pressures on sugarcane in Florida, the committee often selected genotypes 
that ranked below 20th in yield or economic index in Stage HI to advance 1 1 relatively disease-free 
genotypes. 



74 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Kang et al. (1988) reported that genotype repeatability was low between the two stages for 
1 1 genotypes tested for one Stage III and one Stage IV cycle. Glaz and Miller (1982) reported that 
Stage IV results predicted reasonably well the commercial yields of five released genotypes. A 
logical follow-up to the studies of Brown and Glaz (2001), Kang et al. (1988), and Glaz and Miller 
(1982) was to determine how well genotype performance in Stage III corresponded to performance 
in Stage IV, and ultimately to commercial success for many Stage III and IV cycles. With this 
information, a more informed choice could be made about whether to reduce replications and 
increase the number of genotypes in Stage IV. The major purpose of this study was to determine if 
advancing an additional three new genotypes to Stage IV would improve the likelihood of identifying 
successful cultivars. This led into a secondary objective which was to determine if a genotype with 
high or mediocre yields in Stage HI would be expected to have similar yields in Stage IV. 



MATERIALS AND METHODS 

Results from 24 Stage HI cycles from the CP 69 through the CP 92 series of the CP sugarcane 
cooperative breeding and selection program were reviewed. The CP 69 series was planted in Stage 
IE in 1970; and the final harvest of the CP 92 series in Stage HI was in 1995. Stage HI is the 
penultimate selection stage, and the first stage of the program in which genotypes are planted at 
multiple locations, replications, and annual crop cycles. About 1 30 new genotypes are now annually 
advanced to Stage DL These remain in the field for a plant-cane and a flrst-ratoon harvest. This 
study specifically focused on 21 to 42 of the Stage EQ genotypes in each Stage HI cycle for which 
data were collected for both the plant-cane and first-ratoon crops. 

Sixteen Stage IV cycles were reviewed; these cycles included the CP 77 through the CP 92 
series. The CP 77 series was planted in Stage IV in 1980; and the final harvest of the CP 92 series 
in Stage rV was in 1999. Stage IV is the final selection stage in the CP program. Ten to 13 new 
genotypes were advanced to most of these Stage IV cycles, but only 1 or 1 1 were planted at all 
Stage IV locations. The genotypes in Stage IV were analyzed from the plant-cane through the 
second-ratoon crop. The characteristics compared between Stage EI and Stage IV were sugar yield, 
(Mg sugar ha" 1 ), and economic index, measured in $ ha" 1 (Deren et al., 1995). The economic index 
calculation accounts for costs such as planting, milling, and transportation of cane to the mill. For 
calculations of economic index, the same costs were used over all years of the study. Also, 
theoretical recoverable sugar (kg sugar Mg" 1 cane) was discussed for some genotypes. Theoretical 
recoverable sugar (TRS) was calculated according to Arceneaux (1935) until 1993 and according 
to Legendre (1992) since 1993. 

Sugar yield and economic index were reported for both Stage in and Stage IV as a percentage 
of a commercially grown check cultivar. The check was CP 63-588 in Stages III and IV in the CP 
77 and 78 series. In the CP 79 series, the check remained CP 63-588 in Stage EI but was CP 70- 
1 133 (Rice et al., 1978) in Stage IV. From the CP 80 through the CP 92 series, the check was CP 
70-1 133 in both Stage m and Stage IV. 

Stage HI was planted at four locations each year, three with organic soils and one with a sand 
soil. In most cases, Stage IV was planted at these same locations, on the same days as Stage IE. The 
organic soils were Terra Ceia mucks (Euic, hyperthermic Typic Medisaprists), Pahokee mucks (Euic, 

75 



Glaz et al.: Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial Adoption 

hyperthermic Lithic Medisaprists), Lauderhill mucks (Euic, hyperthermic Lithic Medisaprists), and 
Dania mucks (Euic, hyperthermic, shallow Lithic Medisaprists). The sand soils were Malabar sands 
(Loamy, siliceous, hyperthermic Grossarenic Ochraqualfs ) and Pompano Fine sands (Siliceous, 
hyperthermic Typic Psammaquents). Stage IV was planted at an additional 5 to 8 locations each 
year. One of these locations had Pompano Fine sand soils, and another had Tony muck soils (Euic, 
hyperthermic Typic Medisaprists). The Torry mucks have 30-50% organic matter rather than 70- 
85% organic matter which is characteristic of the organic soils at the Stage IH locations. The 
remaining Stage IV tests were on organic soils similar to the organic soils of the Stage in locations. 

Stage III plots were 4.6 m long with rows spaced 1.5 m apart. Plots were two rows wide, 
with a border row surrounding the Stage HI experiment, but not individual plots. Each Stage HI plot 
had a 1 .5 m alley on one end and a 6 m alley on the other end. Stage III experiments were planted 
in randomized complete-block designs with two replications. Stage IV plots were 1 0.7 m long with 
rows spaced 1.5 m apart and 1.5 m alleys, and planted in randomized complete-block designs. From 
the CP 77 through the CP 88 series, plots were four rows wide with four replications per experiment. 
From the CP 89 through the CP 92 series, plots were two rows wide with eight replications per 
experiment. A border row surrounded all Stage IV experiments, and in the case of the CP 89 through 
the CP 92 series, a border row surrounded each Stage IV plot. Agronomic practices, such as 
fertilization, pesticide application, cultivation, and water control, were conducted by the landowner 
in whose field each experiment was planted. 

Sugar yield was estimated by multiplying cane tonnage by TRS . Cane tonnage was estimated 
by multiplying stalk number by stalk weight in all Stage HI tests and in all Stage TV tests after the 
CP 88 series. Stalk number was estimated by counting total millable stalks per plot during the 
summer. Stalk weight was estimated from a 10-stalk sample collected in October in Stage HI and 
from October through April in Stage IV. The TRS was estimated from the juice extracted from the 
same 10-stalk sample. In Stage IV, from the CP 77 through the CP 88 series, cane tonnage was 
estimated by weighing entire plots, and TRS was estimated from 15-stalk samples. The stalk 
samples from which TRS and stalk weights were estimated were collected from sugarcane that was 
burnt in the field before it was cut and sampled for the Stage TV CP 77 through CP 88 series. All 
other stalk samples were of stalks not previously burnt. 

RESULTS AND DISCUSSION 

By the year 2000, 32 CP sugarcane cultivars were released in Florida since the CP 69 series 
finished its second year of testing in Stage III in 1972 (Table 1). With sugar yield used as the 
ranking criterion, 18 of these 32 cultivars ranked among the top four places in Stage HI (Fig. 1). 
Eight of these 32 cultivars ranked number one in Stage HI in sugar yield. Five cultivars ranked from 
fifth through eighth place, seven ranked from ninth through twelfth place, one ranked in fourteenth 
place, and one ranked below fifteenth place. 

Ranking based on economic index resulted in a similar distribution as for sugar yield (Fig. 
2). Seventeen genotypes ranked from first through fourth place in Stage HI, five ranked fifth through 
eighth, seven ranked from ninth through thirteenth place, and three cultivars ranked below fifteenth 
in economic index in Stage HI. 



76 






Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

The only genotype from Stage III with a rank inferior to 15th that was released on the basis 
of sugar yield was CP 89-1509 (Tai et al., 2000) (Table 1). CP 89-1509 was released for production 
on sand soils only; it was not evaluated on organic soils in Stage IV due to its low yields on organic 
soils in Stage HI. Using economic index as the selection criterion, three genotypes that ranked 
inferior to 15th in Stage in were released. One was CP 89-1509. Also released were CP 85-1308 
(Tai et al., 1995) and CP 85-1432 (Deren et al., 1994). None of these cultivars has been used on 
more than 1% of Florida's sugarcane hectarage in any one year. 

These 24 cycles of Stage HI data show that the better the ranking for either sugar yield or 
economic index in Stage HI, the more likelihood that the genotype would eventually be released. 
Twenty-eight of 3 1 CP cultivars released since 1979 ranked better than 1 5th in both sugar yield and 
economic index in Stage HI. Only one has been released that ranked below 1 5th in both sugar yield 
and economic index, and two ranked inferior to 1 5th in economic index, but better than 1 5th in sugar 
yield. Of these three cultivars, one was a special release for sand soils. 

Monitoring the level of commercial use after a genotype's release is a further measure of its 
success. We considered that a cultivar was commercially successful in Florida if it was used at least 
for one year on > 1 % of Florida's sugarcane hectarage. With this lenient criterion, only 1 4 of the 32 
released cultivars became commercially successful (Table 1). Eleven of these 14 cultivars ranked 
first through fourth in Stage EQ using sugar yield as the ranking criterion. The worst rank in Stage 
HI was ninth. Using economic index as the ranking criterion gave similar results, except that one 
cultivar ranked 10th and one 13th in Stage HI. 

Five of the CP cultivars that were tested in Stage HI since 1970 were used on more than 1 5% 
of the hectarage for at least one year (Table 1). The lowest ranking in Stage in for any of these 
"widely used" cultivars in Stage m was for CP 72-1210 (Miller et al., 1981); it ranked sixth in both 
Mg sugar and $ ha' 1 . Cultivars CP 70-1 133 and CP 80-1743 (Deren et al., 1991) were first in both 
categories, CP 72-2086 (Miller et al., 1984) second in both categories, and CP 80-1827 (Glaz et al., 
1990) third in both categories in Stage HI. 

Most genotypes that later became commercial cultivars ranked among the top 1 5 in Stage HI 
in either sugar yield or economic index. Further, the worst rank in Stage HI for either sugar yield or 
economic index of any widely used cultivar was sixth. A conservative conclusion is that as long as 
there are at least 1 1 genotypes advanced from Stage III to Stage IV, Stage HI, under its current 
structure, is adequate for identifying genotypes that will be widely used commercial cultivars in 
Florida. For the goal of identifying successful commercial cultivars (used on at least 1% of 
commercial hectarage for at least 1 year) for Florida, these data indicate that sufficient confidence 
can be placed in Stage HI rankings to warrant not increasing the number of Stage IV entries beyond 
1 1 if doing so would require advancing genotypes from Stage HI that ranked worse than 1 5th in 
sugar yield and economic index. 

For genotypes that are advanced from Stage HI to Stage IV but not released commercially, 
another measurement of their success is how well they yielded in Stage IV. A benefit of identifying 
high-yielding genotypes in Stage IV is that they become a source of parental clones with reliable 
probabilities of producing commercially acceptable progeny. In general, both sugar yield and 
economic index as a percent of the check cultivar in Stage HI were not good predictors of production 

77 



] 



Glaz et al.: Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial Adoption 

in Stage IV. Correlations were significant but low (Fig. 3 and 4). This indicates that some genotypes 
that had poor yields in Stage HI had high yields in Stage IV and vice versa. Therefore, we looked 
specifically at performance in Stage IV of (1) genotypes that ranked worse than 14th in sugar yield 
or economic index in Stage HI and (2) genotypes that ranked either first or second in sugar yield in 
Stage m. 

From the CP 77 through the CP 92 series, 40 genotypes advanced from Stage HI to Stage IV 
ranked worse than 1 4th in Stage HI in either sugar yield or economic index (Table 2). Twenty-seven 
of these genotypes ranked worse than 14th in Mg sugar ha" 1 in Stage HI. Five of these 27 proceeded 
to rank either first or second in sugar yield in Stage IV. Twenty-five genotypes ranked worse than 
14th in economic index in Stage HI. Six of these 25 ranked either first or second in economic index 
in Stage IV. Of these six, CP 85-1308 eventually became a commercial cultivar. Approximately 
20% of the genotypes that were mediocre in Stage HI were highly successful in Stage IV. Several 
of these genotypes probably would have been released commercially except for disease 
susceptibilities that manifested after they were advanced to Stage IV. Attempts were made to use 
all of these successful Stage IV genotypes in crosses for several years at Canal Point. 

A more detailed analysis further refines the strategy of advancing genotypes from Stage HI 
to Stage IV. The lowest ranked genotype in Stage HI to later rank either first or second in Stage IV 
was CP 85-1308, which ranked 21st in economic index in Stage HI (Table 2). However, it also 
ranked seventh in sugar yield in Stage HI. Cultivar CP 85-1308 helps identify a characteristic of 
other genotypes that had poor rankings in Stage HI, but then ranked either first or second in Stage 
IV in one of these characters. Each of these genotypes ranked better than 20th in either sugar yield 
or economic index in Stage HI. Thus, the selection committee could choose not to advance to Stage 
IV any genotype that ranked below 20th in both sugar yield and economic index. However, the 
selection committee should be careful not to follow the above guideline when there are several 
genotypes with consecutive ranks and similar percentages of the check that rank below 20th in both 
sugar yield and economic index. 

Another issue is how soon within the selection program decision makers can be reasonably 
certain that they have identified genotypes that will perform well commercially. In the case of the 
CP program, this question could be posed as: if a superior genotype is identified in Stage HI, is it 
necessary to further evaluate it in Stage IV or could its release be immediately put on a fast track? 
There were 25 genotypes that ranked either first or second in sugar yield in Stage HI from the CP 77 
through the CP 92 series (Table 3). Of the 14 that ranked first in Stage HI, two ranked first in Stage 
IV, and 6 became commercial cultivars. Of the 1 1 genotypes that ranked second in Stage HI, two 
ranked first in Stage IV and only these two became commercial cultivars. Thus, 8 of the 25 
genotypes that ranked either first or second in Stage HI became commercial cultivars. However, 8 
others of the 25 genotypes that ranked first or second in Stage HI then ranked among the lowest 6 
Stage IV genotypes in sugar ha" 1 and $ ha" 1 . This shows that although Stage HI successfully 
identified some high-yielding Stage IV genotypes, it also incorrectly predicted that an equal number 
would be high yielding. 

There are several explanations for the poor correlations between Stage IH and Stage IV 
yields. Stage HI has smaller plots, fewer replications, and fewer locations than Stage IV. Probably 
of more importance, all Stage HI samples for TRS were taken during the final three weeks of 

78 



m^ 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

October. For Stage IV, TRS samples were collected from October through April, the typical Florida 
harvest season. Some genotypes remain low in TRS in October and through November and 
sometimes December, others remain low throughout the harvest season. Recently, additional TRS 
sampling was begun for Stage HI in January and February. This new practice may help improve 
agreement between Stage III and Stage IV genotype performance. 

Another important reason that genotype performance may not agree well between Stage HI 
and Stage IV is that Stage HI data are collected through the first-ratoon crop and Stage IV through 
the second-ratoon crop. Genotype CP 90-1 113 serves as an example that second-ratoon yields can 
be markedly different from those of plant cane and first ratoon for a given genotype. In Stage HI, 
CP 90- 1113 ranked first in sugar yield and second in economic index (Table 3). In Stage IV, CP 90- 
1113 had high sugar yields in the plant-cane crop (Glaz et al., 1995) but ranked among the lowest 
in sugar yield in the second-ratoon crop (Glaz et al., 1998). Alvarez and Schueneman (1991) 
reported that the cost of planting is high relative to other costs in the Florida sugarcane cycle. Due 
to this high cost, the Canal Point program tries to release genotypes that will maintain high yields 
through at least three annual harvests. Therefore, it is critical to identify genotypes such as CP 90- 
1113 in Stage IV before they are released. However, this decline in yield does not occur with 
sufficient frequency among genotypes to warrant extending Stage DI one more crop year. 

Poor repeatability between the two selection stages can also be explained by using 
CP 80-1743 as an example. CP 80-1743 was the highest ranking genotype in its Stage ITJ cycle for 
both sugar yield and economic index but was mediocre in Stage IV for both characters (Table 3.) 
From the CP 77 through the CP 88 series, yields were estimated in Stage HI by counting stalks and 
weighing a 10-stalk sample. In Stage IV, whole plots were weighed. After the CP 88 series, yields 
were estimated in both stages by counting stalks and weighing stalk samples. The Stage HI 
procedure was probably the more accurate for CP 80-1743 because its plot weights were 
substantially reduced in almost all Stage IV plots by severe rat damage after stalk counting would 
have occurred but before plots were weighed. Similar damage was not caused to other genotypes 
in the same Stage IV tests; and CP 80-1743 was identified as a mediocre genotype in Stage IV for 
sugar yield, although it was identified as a genotype with a high TRS (Glaz et al., 1 985). It was only 
due to later work of Eiland and Miller ( 1 992) that CP 80- 1 743 was released. CP 80- 1 743 is currently 
the most widely grown cultivar in Florida (Glaz, 2000), which suggests that rat damage in 
experimental plots does not predict similar damage in commercial fields. 

Another reason that may account for differences in genotype performance between Stage HI 
and Stage IV is that the genotypes are evaluated in each stage in different years. For Florida, Kang 
et al. (1987) reported significant genotype x year interaction for plant-cane sugar yields of Stage ni 
genotypes; whereas, Brown and Glaz (2001) suggested that genotype performance across years was 
similar in Stage IV. Milligan et al. (1 990) reported that genotype x year effects were most important 
in ratoon crops in Louisiana, but not more important than genotype x location effects. Since Stage 
IV tests genotypes during later years than Stage HI, genotype x year interaction may play a role in 
the differences in genotype performance noted between Stages IH and IV. 

This study reviewed 24 cycles of Stage III and 16 cycles of Stage IV data. During these 
cycles, at least 10 or 1 1 genotypes per year were advanced to all Stage IV locations where they were 
evaluated as potential commercial cultivars for Florida. The intent of the committee responsible for 

79 



Glaz et al.: Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial Adoption 

advancing genotypes from Stage HI to Stage IV was generally to advance the genotypes with the 
highest rankings for sugar yield and economic index. However, due to concerns with pests and 
agronomic type, several lower ranking genotypes from Stage III were routinely advanced to Stage 
IV. 

Stage HI results were analyzed by comparing them to actual commercial use and to Stage IV 
data. One conclusion was that advancing 1 1 genotypes from Stage HI to Stage IV was sufficient for 
identifying commercial cultivars that would be widely used in Florida. The data showed that it 
would be very unlikely to identify widely used cultivars from genotypes that ranked worse than 1 5th 
in both sugar yield and economic index in Stage HI as it is currently structured. 

The study of Brown and Glaz (200 1 ) has helped improve a limiting factor in the CP program, 
the low number of genotypes that can be analyzed in Stage IV. To take advantage of this 
opportunity, we recommend improving the caliber of genotypes that are advanced to Stage HI to 
improve the likelihood of identifying cultivars from 14 advanced genotypes to Stage IV. The most 
logical immediate approach to achieve this objective is to expand genotype numbers in the three 
selection stages prior to Stage HI: Seedlings, Stage I, and Stage H. However, Tai et al. (1980) 
reported that sugar yield in Stage II was not an effective predictor of sugar yield in Stage HI. Further, 
much of the percentage of increased genotypes maybe lost to disease susceptibility if new diseases 
or races of current diseases appear. Therefore, ongoing monitoring and review would be an 
important component of this strategy. 



ACKNOWLEDGMENTS 

The authors acknowledge the assistance of Velton Banks, Weldin Cardin, Dow McClelland, 
Wayne Jarriel, Lewis Schoolfield, Louis Serraes, and Howard Weir who served as agricultural 
science technicians for at least 5 years in either the Stage HI or Stage IV phase of the Canal Point 
program during the years for which data were reviewed in this study. 

REFERENCES 

1 . Alvarez, J. and T.J. Schueneman. 1991 . Costs and returns for sugarcane production on muck 
soils. Information Report EI 91-3, Food and Resource Economics Department, Institute of 
Food and Agricultural Sciences, University of Florida. 

2. Arceneaux, G. 1935. A simplified method of making theoretical sugar yield calculations 
in accordance with Winter-Carp-Geerligs formula. International Sugar Journal 37:264-265. 

3. Brown, J.S. and B. Glaz. 2001. Analysis of resource allocation in final stage sugarcane 
clonal selection. Crop Science 41:57-62. 

4. Deren, C.W., J. Alvarez, and B. Glaz. 1995. Use of economic criteria for selecting clones 
in a sugarcane breeding program. Proc. Int. Soc. Sugar Cane Tech. 21:2, 437-447. 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

5. Deren, C.W., B. Glaz, P.Y.P. Tai, J,D. Miller, and J.M. Shine, Jr. 1991. Registration of CP 
80-1743' sugarcane. Crop Sci. 31:235-236. 

6. Deren, C.W., J.M. Shine, Jr., P.Y.P. Tai, B. Glaz, J,D. Miller, and J.C. Comstock. 1994. 
Registration of CP 85-1432' sugarcane. Crop Sci. 34:1405. 

7. Eiland, B.R. and J.D. Miller. 1 992. Performance of 1 2 sugarcane cultivars grown on organic 
soil and subjected to mechanical harvesting. J. Am. Soc. Sugar Cane Technologists 12:58- 
64. 

8. Glaz, B. 2000. Sugarcane variety census: Florida 2000. Sugary Azucar 95 (12): 22-24, 26- 
29. 

9. Glaz, B., J.C. Comstock, P.Y.P. Tai, J.D. Miller, J. Follis, J.S. Brown, and L.Z. Liang. 2001 . 
Evaluation of new Canal Point sugarcane clones: 1999-2000 harvest season. U.S. 
Department of Agriculture, Agricultural Research Service, ARS-157. 

10. Glaz, B. and J.D. Miller. 1982. Comparison of commercial and experimental yields in 
sugarcane. Proceed. HI Inter- American Sugar Cane Seminar: Varieties and Breeding, p. 1 39- 
143. 

1 1 . Glaz, B., P.Y.P. Tai, J.C. Comstock, and J.D. Miller. 1998. Evaluation of new Canal Point 
sugarcane clones: 1996-97 harvest season. U.S. Department of Agriculture, Agricultural 
Research Service, ARS-146. 

12. Glaz, B., P.Y.P. Tai, J.L. Dean, M.S. Kang, J.D. Miller, and O.Sosa, Jr. 1985. Evaluation 
of new Canal Point sugarcane clones: 1984-85 harvest season. U.S. Department of 
Agriculture, Agricultural Research Service. 

13. Glaz, B., P.Y.P. Tai, J.D. Miller, C.W. Deren, J.M Shine, Jr., J.C. Comstock, and O.Sosa, 
Jr. 1995. Evaluation of new Canal Point sugarcane clones: 1994-95 harvest season. U.S. 
Department of Agriculture, Agricultural Research Service, ARS- 109- 1994. 

14. Glaz, G., P.Y.P. Tai, J.D. Miller, and J.R. Orsenigo. 1990. Registration of 'CP 80-1827* 
sugarcane. Crop Sci. 30:232-233. 

15. Kang, M.S., B. Glaz, J.D. Miller, and P.Y.P. Tai. 1988. Clonal repeatability of the stability- 
variance statistic in sugarcane. J. Am. Soc. Sugar Cane Technologists 8:50-55. 

16. Kang, M.S., J.D. Miller, P.Y.P. Tai, J.L. Dean, and B. Glaz. 1987. Implications of 
confounding of genotype x year and genotype x crop effects in sugarcane. Field Crops Res. 
15:349-355. 

17. Legendre, B.L., 1992. The core/press method for predicting the sugar yield from cane for 
use in cane payment. Sugar Journal 54(9):2-7. 



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Glaz et al.: Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial Adoption 

18. Miller, J.D., P.Y.P. Tai, B. Glaz, J.L. Dean, and M.S. Kang. 1984. Registration of CP 72- 
2086 sugarcane. Crop Sci. 24:210. 

19. Miller, J.D., E.R. Rice, J.L. Dean, and P.Y.P. Tai. 1981. Registration of CP 72-1210 
sugarcane. Crop Sci. 21:797. 

20. Milligan, S.B., K.A. Gravis, K.P. Bischoff, and F.A. Martin. 1990. Crop effects on broad- 
sense heritabilities and genetic variances of sugarcane yield components. Crop Sci. 30:344- 
349. 

21. Rice, E.R., J.D. Miller, N.I. James, and J.L. Dean. 1978. Registration of CP 70-1133 
sugarcane. Crop Sci. 17:526. 

22. Tai, P.Y.P., B. Glaz, J.D. Miller, J.M. Shine, Jr., J.E. Follis, and J.C. Comstock. 2000. 
Registration of 'CP 89-1509' sugarcane. Crop Sci. 40:1498. 

23. Tai, P.Y.P., J.D. Miller, C.W. Deren, B. Glaz, J.M. Shine, and J.C. Comstock. 1995. 
Registration of 'CP 85-1308' sugarcane. Crop Sci. 35:1213. 

24. Tai, P.Y.P., J.D. Miller, B.S. Gill, and V. Chew. 1980. Correlations among characters of 
sugarcane in two intermediate selection stages. Proc. Int. Soc. Sugar Cane Tech. 17:2, 1 1 19- 
1128. 



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Table 1 . Commercial sugarcane cultivars released in Florida that were tested in Stage HI since 1 970, 
the year each cultivar was advanced from Stage HI to Stage IV, number of genotypes with which 
each cultivar was compared, and its rankings for sugar yield and economic index in Stage DDL 





Year 


Number of 






Highest 




advanced 


genotypes 






commercial 


Cultivar 


to Stage IV 


in Stage m 


Rank in Stage m 


hectarage 








Mg sugar ha" 1 


$ha' 


% 


CP 69-1052 


1972 


24 


1 


1 


<1.0 


CP 70-1133 


1973 


21 


1 


1 


30.7 


CP 72-1210 


1974 


22 


6 


6 


61.0 


CP 72-2086 


1976 


31 


2 


2 


18.0 


CP 73-1547 


1976 


31 


4 


13 


9.8 


CP 74-2005 


1977 


35 


4 


4 


5.8 


CP 75-1082 


1978 


32 


11 


12 


<1.0 


CP 75-1553 


1978 


32 


5 


5 


<1.0 


CP 75-1632 


1978 


32 


14 


7 


<1.0 


CP 77-1776 


1980 


28 


11 


4 


<1.0 


CP 78-1247 


1981 


38 


11 


8 


<1.0 


CP 78-1628 


1981 


38 


1 


1 


7.9 


CP 78-2114 


1981 


38 


9 


10 


6.1 


CP 80-1743 


1983 


23 


1 


1 


22.1 


CP 80-1827 


1983 


23 


3 


3 


18.2 


CP 81-1238 


1984 


38 


3 


3 


<1.0 


CP 81-1254 


1984 


38 


1 


1 


1.6 


CP 82-1172 


1985 


30 


5 


3 


<1.0 


CP84-1198 t 


1987 


36 


21 


32 


3.8 


CP 85-1308 


1988 


41 


7 


21 


<1.0 


CP 85-1382 


1988 


41 


3 


10 


<1.0 


CP 85-1432 


1988 


41 


6 


17 


<1.0 


CP 85-1491 


1988 


41 


11 


4 


<1.0 


CP 88-1508 


1991 


42 


3 


4 


1.3 


CP 88-1540 


1991 


42 


12 


12 


<1.0 


CP 88-1762 


1991 


42 


1 


2 


4.1 


CP 89-1509 


1992 


42 


29 


21 


<1.0 


CP 89-2143 


1992 


42 


2 


1 


1.2 


CP 89-2377 


1992 


42 


1 


2 


<1.0 


CP 92-1213 


1995 


42 


10 


9 


<1.0 


CP 92-1640 


1995 


42 


4 


6 


<1.0 


CP 92-1666 


1995 


42 


1 


2 


<1.0 



f A note describing CP 84- 
not discussed in the text. 



1 198 suggests an error in its Stage EI data. Therefore, CP 84-1 198 is 



83 



Jim 



Glaz et al.: Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial Adoption 



Table 2. Rank and % of check in Stages IH and IV for sugar yield and economic index of 40 
genotypes from 16 years of Stage IH that ranked worse than 14 th in either sugar yield or economic 
index in Stage HI. 



Mg sugar ha" 



$ha 



Genotype 



Stage 

m 



Stage 
IV 



Stage 

m 



Stage 
IV 



Stage 


Stage 


Stage 


Stage 


m 


IV 


in 


IV 


— Rank — 


% of check 


9 


9 


117.0 


78.3 


17 


8 


108.3 


115.8 


19 


10 


107.1 


89.0 


13 


7 


129.9 


76.9 


19 


5 


97.2 


95.3 


33 


10 


79.8 


81.6 


12 


5 


89.8 


81.4 


15 


1 


85.9 


93.2 


16 


2 


76.0 


86.4 


21 


2 


84.8 


117.5 


17 


3 


90.8 


113.8 


14 


9 


93.4 


80.0 


25 


2 


85.1 


93.9 


7 


3 


96.0 


91.3 


15 


4 


93.2 


89.9 


8 


10 


90.7 


60.0 


13 


9 


87.8 


80.2 


10 


1 


89.7 


104.0 


21 


3 


81.1 


103.2 


24 


5 


79.3 


99.6 


16 


7 


94.0 


95.2 


11 


2 


101.7 


107.6 


27 


4 


87.4 


105.1 


14 


6 


95.0 


97.1 


9 


8 


103.6 


99.2 


27 


9 


90.0 


91.9 


16 


7 


81.7 


96.3 


17 


1 


81.4 


110.8 


18 


2 


80.8 


110.7 


9 


10 


90.6 


82.9 


5 


4 


97.1 


104.8 


27 


6 


68.9 


98.1 


20 


10 


87.8 


85.8 


14 


11 


93.2 


84.2 


19 


9 


89.6 


85.9 


15 


1 


93.2 


107.5 


13 


9 


87.1 


89.9 


20 


3 


80.1 


106.1 


24 


11 


76.0 


79.5 


16 


8 


85.1 


91.8 



—Rank — 



% of check 



CP 77-1404 
CP 78-1263 
CP 78-1979 
CP 79-1580 
CP 81-1435 
CP 81-2062 
CP 83-1351 
CP 83-1773 
CP 84-1572 
CP 85-1308 
CP 85-1432 
CP 86-1180 
CP 86-1747 
CP 86-1882 
CP 86-1427 
CP 87-1018 
CP 87-1121 
CP 87-1274 
CP 87-1475 
CP 87-1733 
CP 88-1165 
CP 88-1561 
CP 88-1834 
CP 88-1836 
CP 89-1331 
CP 89-1632 
CP 90-1151 
CP 90-1436 
CP 90-1464 
CP 90-1510 
CP 90-1535 
CP 90-1549 
CP 91-1865 
CP 91-1880 
CP 91-1883 
CP 91-1914 
CP 92-1320 
CP 92-1641 
CP 92-1647 
CP 92-1684 



17 
17 
12 
15 

8 

5 

17 
13 
18 

7 

6 
25 
15 
19 

7 

16 
19 
15 

8 
21 
13 
15 
14 
17 
20 
34 

3 

14 
19 
23 
24 
29 
12 
16 
30 
20 

15 
24 
27 

18 



8 
7 

10 
5 
3 
5 
5 
1 
2 
2 
3 
9 
2 
5 
7 

10 
9 
2 
5 
8 
5 
6 
2 
7 
8 
9 
7 
3 
1 
9 
6 
4 
9 
11 
8 
1 
10 
5 

11 
7 



99.2 
103.4 
111.1 
115.6 
101.0 
103.7 
90.4 
93.3 
79.7 
97.6 
98.1 
85.4 
90.7 
88.6 
97.3 
89.4 
89.1 
89.9 
99.2 
84.6 
95.4 
93.8 
94.7 
93.0 
96.0 
84.1 
103.4 
86.5 
82.1 
80.9 
80.2 
74.4 
92.8 
89.9 
83.1 
87.9 
91.9 
84.6 
81.0 
90.6 



95.6 

114.0 

99.5 

84.5 

94.1 

90.2 

84.4 

100.9 

91.8 

109.4 

104.0 

79.5 

98.7 

89.1 

88.7 

76.0 

92.4 

107.3 

102.6 

96.4 

99.4 

98.9 

103.2 

96.0 

94.4 

88.8 

93.9 

105.9 

106.7 

83.8 

97.0 

101.5 

87.1 

85.8 

87.4 

101.4 

90.6 

98.7 

78.8 

94.9 






84 



^ 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 



Table 3. Rank and % of check from 16 years of Stages III and IV for sugar yield and economic 
index of 25 genotypes that ranked first or second in sugar yield in Stage HI. 







Mg 


sugar ha" 1 






$ha 








Stage 


Stage 


Stage 


Stage 


Stage 


Stage 


Stage 


Stage 


Genotype 


m 


rv 


m 


rv 


m 


IV 


m 


rv 




— Rank— - 


% of check 


— Rank- 


% of check 


CP 77-1055 


2 


2 


113.0 


117.3 


5 


1 


134.2 


117.6 


CP 77-1148 


1 


5 


129.5 


99.4 


1 


10 


193.4 


77.9 


CP 78-1 156 


2 


6 


127.8 


114.3 


2 


3 


153.5 


118.6 


CP78-1628 f 


1 


2 


156.6 


122.2 


1 


2 


183.8 


128.8 


CP 79-1288 


1 


8 


161.3 


79.7 


1 


6 


216.5 


77.9 


CP 79-1380 


2 


1 


152.9 


94.1 


2 


3 


165.3 


84.8 


CP 80-1 743 f 


1 


7 


113.3 


85.1 


1 


6 


131.8 


85.8 


CP 80-1827 f 


2 


1 


96.7 


105.7 


3 


1 


97.6 


110.7 


CP81-1254 1 


1 


1 


109.7 


104.5 


1 


1 


126.9 


119.2 


CP 81-2149 


2 


9 


108.2 


85.8 


10 


9 


104.5 


83.9 


CP 82-1505 


2 


4 


104.4 


94.5 


5 


7 


102.6 


90.2 


CP 82-1587 


1 


9 


109.3 


78.9 


1 


9 


102.6 


78.8 


CP 85-1207 


1 


5 


114.2 


99.1 


2 


5 


118.9 


102.2 


CP 85-1808 


2 


8 


104.9 


84.8 


1 


8 


120.9 


92.3 


CP 86-2024 


1 


8 


122.7 


83.5 


1 


8 


136.1 


85.5 


CP 87-1226 


1 


3 


110.7 


105.3 


11 


8 


88.7 


90.7 


CP 88-1762 1 


1 


4 


109.0 


101.0 


2 


5 


118.1 


103.0 


CP 88-1912 


2 


3 


108.7 


101.9 


1 


3 


119.9 


105.8 


CP 89-2143 f 


2 


1 


131.9 


113.9 


1 


1 


150.9 


122.1 


CP 89-2377 t 


1 


3 


132.8 


105.4 


2 


6 


131.7 


106.5 


CP 90-1113 


1 


10 


107.6 


83.7 


2 


9 


117.3 


88.4 


CP 91-1924 


1 


3 


125.2 


96.1 


1 


2 


152.8 


99.8 


CP 91-2246 


2 


7 


103.3 


88.2 


2 


6 


111.2 


90.4 


CP 92-1 167 


2 


2 


108.3 


108.4 


5 


4 


102.8 


106.1 


CP 92-1666 f 


1 


1 


119.5 


111.9 


2 


1 


113.6 


112.7 



f These genotypes were later released as commercial cultivars in Florida. 



85 



Glaz et al.: Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial Adoption 



Z 2 



6 7 8 9 

Sugar yield rank in Stage III 




; 



13 



14 



15 



>15 



Figure 1. Rank of sugar yield (Mg sugar ha" 1 ) in Stage EI and number of genotypes with the 

same rank for 32 sugarcane genotypes that became commercial cultivars in Florida from 
the CP 69 through the CP 92 series. 



$ 

o 
c 



E 

3 

z 



5 — 



4 + 



6 7 8 9 10 

$ per ha rank in Stage III 



11 



12 



13 



14 



15 >15 



Figure 2. Rank of economic index ($ ha" 1 ) in Stage lH and number of genotypes with the same 
rank for 32 sugarcane genotypes that became commercial cultivars in Florida from the 
CP 69 through the CP 92 series. 



86 



. 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 




91 95 98 101 

Stage III genotypes (% check) 



Figure 3. Correlation of sugar yield (measured as Mg sugar ha" 1 ) as percent of check cultivar in 
Stage III with sugar yield as percent of check cultivar in Stage IV for 1 1 7 genotypes 
from 16 Stage IH and Stage IV cycles. 



87 



Glaz et al.: Sugarcane Genotype Repeatability in Replicated Selection Stages and Commercial Adoption 






140 




80 100 120 

Stage III genotypes (% check) 



140 



Figure 4. Correlation of economic index ($ ha" 1 ) as percent of check cultivar in Stage in with 
economic index as percent of check cultivar in Stage IV for 1 17 genotypes from 16 
Stage EQ and Stage IV cycles. 



88 



-^ 



PEER 

REFEREED 

JOURNAL 

ARTICLES 



MANUFACTURING 
SECTION 



89 



Andrews and Godshall: Comparing the Effects of Sulphur Dioxide on Model Sucrose and Cane Juice Systems 

COMPARING THE EFFECTS OF SULPHUR DIOXIDE 
ON MODEL SUCROSE AND CANE JUICE SYSTEMS 

L.S. Andrews and M.A. Godshall 

Sugar Processing Research Institute, Inc. 

1 100 Robert E. Lee Blvd 

New Orleans, LA 

ABSTRACT 

Sulphur dioxide (S0 2 ) has been used for centuries to minimize color in food processing and 
fruit and vegetable storage. In the sugar industry, it is used routinely by sugar beet processors to 
reduce and prevent color formation in white refined sugar. Sugarcane processors throughout the 
world use S0 2 to produce plantation white sugars. This study was undertaken to determine the effect 
of S0 2 on pure sucrose solutions in comparison to real factory sugarcane juice streams. Sugar 
systems included 1 5 brix pure sucrose, clarified juice and mixed juice from a Louisiana sugarcane mill. 
A pH of 8.0 was obtained by adding milk of lime then lowered to approximately pH 5.0 with either 
S0 2 or HC1 (control). Several samples ranging from pH 5 to 8 were processed at 0-120 min at 85° 
C. Analyses included pH, S0 2 , color, calcium, and invert (as a measure of sucrose loss). Results 
indicated that the model system was much more sensitive to low levels of S0 2 than real juice samples 
which demonstrated a greater buffering capacity. The pH levels of the model sucrose solution 
dropped rapidly, and invert levels increased with time. There was 1.6 % loss of sucrose in the S0 2 
trial as compared with no sucrose loss with HC1. Clarified juice resisted changes in pH with both S0 2 
and HO. Sucrose loss at 120 min of processing and a pH of 5.0 was only 0.88 %. There was a 
maximum color reduction of 1 0- 1 5 % in the S0 2 trial, whereas no color reduction or sucrose loss was 
observed in the HC1 trial. The mixed juice was very resistant to pH changes, and a minimum pH of 
6.0 was achieved with 4800 ppm S0 2 No sucrose loss was observed in either trial with mixed juice, 
and color reduction was the same in both the S0 2 and HC1 trials. In real juice streams, S0 2 reduced 
color by 10-15 % more than clarification alone but also induced some sucrose loss (0.88%) after a 
lengthy time. 

INTRODUCTION 

Sulphur dioxide has traditionally been used in food processing and produce storage to 
niinimize color formation due to browning reactions associated with amino acids interacting with 
invert sugars in the Maillard reaction. Sugar beet processors routinely use sulphur dioxide in process 
streams for the same purpose. Among sugar cane processors worldwide there is mixed interest in 
usage of sulfitation. In the United States, sulfitation has rarely been used in cane raw sugar factories 
since the 1950's. Today, there is renewed interest in the effectiveness of sulfur dioxide as a color 
retardant as many US factories are considering the production of high quality low color raw sugar 
to be sold as a food grade sugar. 

Under normal ambient temperature and pressure, sulphur dioxide is a colorless, pungent 
smelling, nonflammable gas. In very low concentrations this gas can cause extreme eye and 
respiratory irritation, thus must be used in a controlled environment (Anonymous, 1996). The 

90 









^ 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Egyptians and Romans burned sulfur to form sulfur dioxide (S0 2 ) as a means of sanitizing wine- 
making equipment and today S0 2 is used to treat most light colored dehydrated fruit and vegetables 
to prevent undesirable enzymatic and non enzymatic "browning" reactions. Sulfur dioxide provides 
the added benefit of acting as a food preservative and functions as an antioxidant (McWeeny, 1981). 
Sulfite additive has been used extensively in the food industry to retard Maillard reactions. McWeeny 
(1981) discussed the two main groups of reactions between sugars, ascorbic acid and their 
dehydration products and bisulfite, primarily the hydroxy sulfonate and organo sulfur compounds. 

Browning reactions, of whatever type, are caused by the formation of unsaturated, colored 
polymers of varying composition. Compounds that engender browning usually contain a carbonyl or 
potential carbonyl grouping (Hodge, 1 953). Browning can be inhibited by compounds that block or 
eliminate or combine with carbonyl groups. The multiplicity of studies regarding browning reaction 
theories is reviewed thoroughly in Hodge's (1953) review article. 

The purpose of sulfiting purified and clarified thin beet juices are 1) to control juice color 
formation; 2) to improve the boiling properties of the juices; and 3) reduce the excess alkalinity 
(McGinnis, 1982). Two methods of sulfuring are 1) by sulfur stove, burning elemental sulfur for 
production of sulfite and 2)bubbling sulfur dioxide through process streams. Also produced during 
these processes is the undesired sulfate ion that can interfere with crystallization causing an increase 
in molasses purity and production. The oxidation of sulfite to sulfate is greatly retarded as the sugar 
concentration is increased. Sulfitation can control juice color by interfering with chromophoric 
molecular groups include carbonyl (ketones), carbonyl (aldehydes), carboxyl, and amido. "These 
compounds are characterized by an electron imbalance, an electronically excited state, a molecular 
resonance, an absorption of specific bands of transmitted light, and to the beholder, color" (McGinnis, 
1 982). Color compounds in cane and beet sugar products include naturally occurring pigments along 
with a large heterogeneous variation of color compounds produced during processing. It has been 
estimated that for a 98.5°pol raw sugar, colorants account for approximately 1 5-20 % of the weight 
of non sugars. In granulated refined sugar the estimate is approximately 30 ppm (Clarke and 
Godshall, 1988). 

In the cane sugar factory, the major role of sulfur dioxide has been to make white sugar rather 
than raw sugar through inhibition of color forming reactions. This is achieved by addition of S0 2 to 
the alkenic double bond in an CX,P~ unsaturated carbonyl intermediate as well as to the carbonyl 
group, which yields P-sulfonated aldehydes that are of comparatively low reactivity in reactions 
leading to the production of browning compounds by the Maillard reaction and degradation of invert 
sugars (Shore, et al., 1984). Sulfur dioxide also has the ability to inhibit or retard enzymatic 
browning reactions. Sulfur dioxide added as 300-500 ppm to raw beet juice resulted in minimal (5%) 
color reduction (Shore, et al., 1 984). Onna and Sloane ( 1 978) reported that 300 ppm decreased color 
in syrup and whole raw sugars by about 25% with crystal color reduced by 46%. Final refined 
granulated sugar from this process had 35% less color. 

During processing and storage at elevated temperatures, sugar products will darken. All 
industries that use sugar products are in turn susceptible to color changes in their products which may 
or may not be desirable (Zerban, 1947). When cane and beet juices are heated and limed during 
clarification, invert sugar disappears and the color of juices increases with the amount of lime added. 

91 






Andrews and Godshall: Comparing the Effects of Sulphur Dioxide on Model Sucrose and Cane Juice Systems 

Much of this color is bound to calcium precipitate in the defecation process. Color changes 
additionally occur during heating and evaporation processes, since the juices are exposed to continual 
heating (70-75° C) over several hours at slightly alkaline pH in the beet industry and slightly acid pH 
in the cane industry. The higher the alkalinity of clarified beet juice, the greater the color increase. 
The color of clarified cane juice also increases during evaporation and crystallization even though it 
is kept on the slightly acid side. 

In cane and beet processing, there are many variations in procedure for adding sulfur dioxide. 
There is cold sulfitation with S0 2 added to cold raw juice then limed; alkaline sulfitation where juice 
is limed then suLfited and again sulfite added to syrup prior to pan boiling. Hot sulfitation where juice 
is heated first then sulfited and limed, this method is used to reduce the solubility of calcium sulfite. 
Other modification of these procedures are used according to plant capabilities etc. In Northern 
Europe, a method of combining sulfitation with preliming of diffusion juice was developed. Small 
additions of S0 2 to an acidic(pH 5.5-6.0) diffusion juice improved filtration and sedimentation, as 
well as reduced juice color development (Dandar, et al., 1973) Effect on sucrose recovery was not 
discussed. Indonesian cane processors have developed a similar process using sulfitation with lime 
with the production of a high standard quality white consumption sugar for export (Marches, 1 953). 
This plantation white sugar is the result of two sulfitation procedures, first at original clarifier when 
added with lime and second as syrup sulfitation prior to vacuum pan. 

Sulfitation in Louisiana is a very old process, possibly originating with French or English 
settlers (Spencer, et al.,1945). Cold raw juice was pumped through a sulfur tower with a 
countercurrent of sulfur dioxide to produce a fairly good, irregular, near or off-white sugar. By the 
late 1 930's use of sulfur dioxide was on the decline and was then mainly used for production of direct 
consumption molasses. 

This study was undertaken to determine the effect of sulphur dioxide on model and real cane 
process streams. This work is part of SPRI's continuing research on determining the effect of invert 
and pH on sucrose recovery and color formation. 

MATERIALS AND METHODS 

Sugar Solutions : 1 5 brix pure sucrose, clarified cane juice and mixed raw cane juice. 

Sulfitation : Sugar systems were brought to a pH of 8.00 with milk of lime (cold lime). The pH was 
then adjusted with either sulphur dioxide (S0 2 ) or hydrochloric acid(HCl), as a control, to 
approximate cane juice pH of 5-6. Sulphur dioxide was bubbled through the sugar system using a 
micro valve controller. Samples were taken as pH dropped from 8 to 5. 

Processing : The pure sucrose solution was then processed in a gyratory shaker for up to 60 min at 
85°C. Clarified juice and mixed juice were treated for up to 120 min. Time was extended for juice 
samples due to lack of significant reactions at 60 min. 

Analyses : Samples were analyzed for pH, S0 2 by ICUMSA rosaniline colorimetric method, calcium 
by HPIC, color by ICUMSA method, invert by HPIC. 



92 



U^ 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

HPIC Calcium: DX 500 with IonPac CS12 column with CSRS Suppressor, isometric 1.0 
ml/min 20mM H 2 S0 4 , and conductivity detection. 

HPIC Invert: DX 500 with CarboPac PA1 column, gradient 1 ml/min 100-200 raM NaOH 
and amperometric detection. 

RESULTS AND DISCUSSION 

In order to achieve a similar pH among the three sugar systems, it was necessary to use 
different amounts of sulphur dioxide. Figure 1 shows the relative sensitivity of the pure sucrose 
solution compared to either of the factory process streams. Both juice streams demonstrated a huge 
buffering capacity that was not present in the pure sucrose solution. 



Sucrose 



i Clar Juice 



Mixed Juice 



5000 



- 4000 
Co 

CO 

o 



3000 



<D 



2= 2000 



CO 

E 

Q. 



1000 



Amount of S02 needed to reduce 
pH of pure sucrose solution 



£« A 

§32 

i 

o24 

o 16 

W 

E 8 



laAJfllB^ 



7.5 6.8 5.9 
pH 



Z~7| 



yh^^^h^ V~7 



w 



/IA 



Z. 



7.5 



6.8 



5.8 



pH 



Figure 1. The amount of S0 2 required to adjust the pH of pure sucrose solution, clarified juice and 
mixed juice from pH 8.0. Insert: Amount of S0 2 required to lower pH of pure sucrose 
solution. 



93 






Andrews and Godshall: Comparing the Effects of Sulphur Dioxide on Model Sucrose and Cane Juice Systems 

Tables 1-3 summarize the results of treating the various solutions with sulfur dioxide. 

The pure sucrose model system responded to minimal amounts of sulphur dioxide (2-29 ppm) 
with a rapid reduction in pH (Table 1). Processing times up to 60 minutes with pH below 6.1 also 
indicated rapid deterioration in sucrose as evident by the increase in glucose. When sucrose loss is 
calculated as 2 X the relative increase in glucose (DeBruin, 1998), in this model system, glucose 
increased by as much as 8000 ppm on solids after 60 minutes of processing at a beginning pH of 5.9. 
This calculated to loss of 1 .6% sucrose based on solids. In contrast, under the same conditions, the 
HC1 control system had rninimal sucrose loss (.03% on solids) which was directly attributable to acid 
hydrolysis. No changes occurred in color or calcium residuals with either of these process systems. 
After heat treatment no residual S0 2 remained. 

The clarified juice results (Table 2) were very different from those of the model sucrose 
system. The observation time was increased to 120 min because no significant changes were noted 
at 60 min. The juices were treated with 0-1700 ppm S0 2 . These high levels were needed to bring 
the pH down to the desired level. The S0 2 treated samples generally showed a decrease in color over 
time, with more color decrease (up to 1 5 %) in the highest treatment level. These results were similar 
to those reported by Kort (1995) who showed a 15% reduction in color with >200ppm S0 2 . 
However, some earlier papers reported a somewhat better color reduction of 25-35% with 250-500 
ppm S0 2 (Onna and Sloan, 1978; Fort and Walton, 1932). The HCl-treated samples showed some 
color increase. Glucose formation was insignificant throughout, indicating little or no sucrose 
hydrolysis with either S02 or HC1. No residual S0 2 remained when initial treatment was <500 ppm. 

The mixed raw juice results (Table 3) were also different from those of the model sucrose 
system. As with the clarified juice, the process time was increased to 1 20 min because few significant 
changes were noted at 60 min. These juices were treated with up to 4700 ppm S0 2 to achieve the 
same pH range as with the model system. The rate of clearance of S0 2 from the juice systems during 
processing is noted on the table. Calcium levels (data not shown) dropped an average of 100-400 
ppm with the lower pH and greater S0 2 concentrations. This in effect was a sulfo-defecation or 
clarification process induced by liming, reduction to acid pH, and heat processing. The calcium likely 
becoming bound up in colorant and/or polysaccharide and was precipitated. There was a small but 
consistent drop in glucose in both S0 2 -treated and HCl-treated samples. There was also a significant 
color drop in both S0 2 -treated and HCl-treated samples. Silva and Zarpelon (1977) reported a 
similar drop in color using mixed juice systems through the sulfo-defecation process. 

CONCLUSIONS 

There is renewed interest in the United States to produce a high quality food grade sugar at 
the raw sugar mill. Several means for achieving high quality, low color sugar exist, one of which is 
sulfitation. The USFDA currently has a 10 ppm limit on residual sulphur dioxide allowed in food 
products. If sulphitation is being considered for white sugar production, the manufacturer must take 
caution to keep residuals below this limit. 

It is apparent through these studies that attempting to predict juice stream behaviors by model 
sucrose solutions is not a valid hypothesis for S0 2 treatment. However, a positive result gained from 

94 



*. 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

this study was that with minimal application of sulphur dioxide, color can be reduced by at least 10- 
20%. Currently in Louisiana during late season, raw sugar quality meets all the criteria for Blanco- 
Directo (Bennett and Ross, 1988) except for color and turbidity (Table 4). The authors feel that by 
using a color minimizer, such as sulphur dioxide or other, Louisiana raw sugar could meet the quality 
standards for food ingredient sugar such as the Blanco-Directo sold to soft drink processors in some 
Caribbean countries, or other locations where sugar is used to sweeten food ingredients. 

ACKNOWLEDGMENTS 

The authors thank Sara Moore and Ron Triche for their technical assistance. 

REFERENCES 

1. Anonymous. 1996. Sulfur Dioxide. Food Chemicals Codex, 4 th edition. National Academy 
Press. 

2. Bennett, M.C. and Ross, B.G. 1988. Blanco-Directo production at Hawaiian-Philippines 
Company. Proceeding of Workshop on White Sugar Quality, Viewpoint of producers and 
users. SPRI, pp 3-6. 

3. de Bruijn, J.M., Struijs, J.L., and Bout-Diederen, M.E. 1998. Sugar degradation and colour 
formation. Proceedings on Sugar Processing Research, SPRI Conference. Savannah, GA., 
ppl27-143. 

4. Clarke, M.A. and Godshall, M.A, eds. Chemistry and Processing of Sugarbeet and 
Sugarcane. Chapter 13, The nature of colorants in sugarcane and beet sugar manufacture. 
Elsevier Science Publishers, Amsterdam 

5. Dandar, A., Basatko, J. and Rajinakova, A. 1973. Influence of sulphitation of beet juice 
before progressive preliming according to Dedek and Vasatko on the purification effect. 
Zucker 26(1 1)593-597. 

6. El-Kadar, A. A. El-Kadar, Mansour and Yassin, A. A. 1 983 . Influence of clarification on sugar 
cane juices by the sulphitation and phosphatation processes. Proceedings ISSCT, XVIII 
Congress, pp 507-530, Havana, Cuba. 

7. Fort, C.A. and Walton, C.F. 1932. Effect of clarification on quality of raw and plantation 
white sugars. Industrial and Engineering Chemistry, Vol.25, No 6:675-681. 

8. Hodge, J.E. 1953. Dehydrated foods: Chemistry of browning reactions in model systems. 
Agri. and Food Chem., Vol. 1, No 15:928-943. 

9. Kort, MJ. 1995. Sulphitation of mixed juice. Sugar Processing Research Institute, Annual 
Report. Dalbridge, South Aftica. 



95 






Andrews and Godshall: Comparing the Effects of Sulphur Dioxide on Model Sucrose and Cane Juice Systems 

1 0. Marches, J. 1 953. Clarification of cane juices by means of the sulphitation process. Principles 
of Sugar Technology, Chapter 15, edited by P. Honig. Elsevier Publishing Company. 

11. McGinnis, R.A. 1982. Beet Sugar Technology, 3 rd edition. Sulfitation pp 265-274. 

1 2. McWeeny, D.J. 1 98 1 . Sulfur dioxide and the Maillard reaction in food. Prog. Fd. Nutr. Sci., 
Vol.5, pp. 395-404. 

13. Onna, K. And Sloane, G.E. 1978. 1977 juice sulfitation test at Puna Sugar Company. 
Reports, Hawaiian Sugar Technologists, Vol 36:26-28. 

14. Silva, J.F. and Zarpelon, F. 1977. Color and ash levels in process streams at three factories 
producing raw, sulfitation white and high pol raw sugars. Processing:2787-2795. 

15. Shore, M., Broughton, N.W., Dutton, J.V. and Sissons, A. 1984. Factors affecting white 
sugar colour. Sugar Technology Reviews, 12:1-99. 

1 6. Spencer, G.L. Meade,G.P., and Wiley, J. 1 945. Cane Sugar Handbook, 8 th edition, ppl 09- 
110. 

1 7. Zerban, F. W. 1 947. The color problem in sucrose manufacture. Technical Report Series No. 
2, Sugar Research Foundation, Inc. New York. 



96 



iflfe^ 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 1: Effect of S0 2 on 15.2 Brix model sucrose solutions. Solution initially brought to pH 8.0 
with milk of lime. 



Minutes at 
85°C 


Initial and 
residual 
SO. . ppm i 


Final pH 
with SO, 


Glucose * 
with S0 2 
ppm solids 


Final pH 
with HCl 


Glucose * 
with HCl 
ppm solids 








7.9 


35 | 


7.9 


45 


15 





7.5 


27 


7.3 


49 


30 





7.4 


33 


7.1 


50 


60 | 





7.3 


48 


7.0 


65 





2 


7.6 


28 


7.3 


37 


15 





6.9 


37 


6.85 


43 


30 





6.6 


76 


6.75 


32 


60 





6.5 


78 


6.5 


79 





5.4 


7.0 


28 


6.8 


28 


15 





6.3 


65 


6.6 


64 


30 





6.2 


80 


6.3 


71 


60 





6.1 


132 


6.15 


130 





12.6 


6.5 


27 


6.5 


30 


15 





6.0 


565 


6.3 


44 


30 





5.9 


1073 


6.1 


78 


60 





5.6 


1406 


5.9 


121 





29 


5.9 


27 


6.0 


28 


15 





5.1 


2166 


5.9 


66 


30 





4.9 


2983 


5.8 


87 


60 





4.6 


8193 


5.7 


152 



*Fructose showed near identical values to glucose, indicating the acid hydrolysis of sucrose. 
No color formation was observed in any of the treated solutions 



97 



Andrews and Godshail: Comparing the Effects of Sulphur Dioxide on Model Sucrose and Cane Juice Systems 

Table 2: Effect of S0 2 on 13.3 Brix clarified juice. Solution initially brought to pH 8.0 with milk 
of lime. 



Minutes 
at 85°C 


Initial 
and 

residual 
SO, 


Final 
pH 
with 
SO, 


Glucose 
with S0 2 
% solids 


Color ICU 


Final pH 

with 

HC1 


Glucose 
withHCl 
% solids 


Color 
ICU 








6.7 


2.63 


11,100 


6.6 


2.63 


10,902 


30 





6.6 


2.70 


11,346 


6.6 


2.70 


11,686 


60 





6.5 


2.66 


11,494 


6.5 


2.55 


11,095 


120 





6.3 


2.75 


10,924 


6.2 


2.61 


11,627 





83 


6.0 


2.65 


10,581 


6.2 


2.56 


10,744 


30 





6.0 


2.66 


10,399 


6.2 


2.55 


10,819 


60 





5.9 


2.76 


10,636 


6.1 


2.62 


11,465 


120 





5.8 


2.83 


10,769 


6.0 


2.86 


11,781 





487 


5.6 


2.74 


10,414 


5.8 


2.54 


10,824 


30 


294 


5.5 


2.75 


9,615 


5.7 


2.40 


11,557 


60 


194 


5.4 


2.78 


9,527 


5.7 


2.68 


11,435 


120 


1 


5.4 


2.91 


9,406 


5.7 


2.81 


11,496 





943 


5.2 


2.67 


10,203 


5.4 


2.66 


10,411 


30 


825 


5.2 


2.53 


9,677 


5.4 


2.58 


10,830 


60 


644 


5.1 


2.82 


8,956 


5.4 


2.48 


10,954 


120 


247 


5.1 


2.82 


9,166 


5.3 


2.73 


11,466 





1677 


5.0 


2.68 


9,767 


5.0 


2.53 


10,205 


30 


1554 


4.9 


2.67 


9,121 


5.0 


2.62 


10,584 


60 


1423 


4.9 


2.78 


8,670 


5.0 


2.71 


10,489 


120 


1185 


4.8 


3.12 


8,490 


5.0 


2.89 


10,536 



98 



. 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 3: Effect of S0 2 on 13.3 Brix mixed raw juice. Solution initially brought to pH 8.0 with milk 
of lime. 



Minutes 
at 85°C ! 


Initial 
and 

residual 
SO, 


Final 
pH 
with 
SO, 


Glucose 
with S0 2 

% solids 


Color ICU 


Final pH 

with 

HCl 


Glucose 
withHCl 
% solids 


Color 
ICU 








8.0 


4.24 


27,167 


8.1 


4.34 


25,333 


30 





7.7 


3.38 


26,500 


7.8 


3.83 


21,667 


60 





7.6 


3.43 


26,500 


7.6 


3.82 


18,973 | 


120 





7.2 


3.36 


22,825 


7.2 


3.97 


19,116 





271 


7.5 


3.58 


27,167 


7.5 


4.18 


25,333 


30 


122 


7.4 


3.26 


25,000 


7.5 


3.70 


21,667 


60 


5 


7.4 


3.25 


26,333 


7.4 


3.77 


18,260 


120 





6.9 


3.31 


22,682 


6.9 


3.86 


19,116 





1291 


6.8 


3.86 


25,833 


6.8 


4.60 


25,833 


30 


848 


6.8 


3.19 


23,333 


6.8 


3.63 


21,000 


60 | 


579 


6.7 


3.28 


24,500 


6.5 


3.81 


17,689 


120 





6.6 


3.35 


21,398 


6.4 


3.78 


17,974 





2009 


6.2 


3.99 


26,500 


6.3 


4.56 


25,500 


30 


1900 


6.2 


3.25 


23,667 


6.2 


3.81 


22,167 


60 


1549 


6.1 


3.25 


23,833 


6.0 


3.88 


18,117 


120 


1479 


5.9 


3.40 


20,970 


6.0 


4.02 


18,545 





4746 


5.7 


4.43 


28,000 


5.9 


4.62 


25,333 


30 


4653 


5.6 


3.61 


24,333 


5.8 


4.31 


20,167 


60 


4423 


5.6 


3.79 


24,667 


5.6 


3.73 


17,404 


120 


3962 


5.5 


3.87 


19,971 


5.4 


3.79 


17,404 



99 



Andrews and Godshall: Comparing the Effects of Sulphur Dioxide on Model Sucrose and Cane Juice Systems 

Table 4. Quality comparison of Blanco Directo and Louisiana raw sugars. 






Specification 


Blanco Directo 


Louisiana Raw 


Pol 


99.7 


99.8 


Color (natural) 


150 


484 


Turbidity 


50 


100 


Ash 


0.5 


0.06 


Invert % solids 


0.2 


0.05 


S0 2 residual 


5 ppm 


not treated 



100 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

THE EFFECT OF TWO LOUISIANA SOILS ON CANE JUICE QUALITY 



Mary An Godshall*, Scott K. Spear**, and Richard M. Johnson 



*** 



* Sugar Processing Research Institute, New Orleans, LA. 

**Center for Green Manufacturing, The University of Alabama, Tuscaloosa, AL 

*** Southern Regional Research Center, ARS, USD A, New Orleans, LA 



ABSTRACT 

As part of ongoing investigations on the effect of various field practices on the quality of cane 
juice in Louisiana, we noted that cane juice color decreased significantly when soil was added to 
assess the effect of soil on cane juice quality. In a study of the 1999/00 crop in Louisiana, with 
addition of 5% and 10% soil to the cane juice, it was noted that polysaccharide was also removed, 
the first time this had been reported. These observations run contrary to expectations that soil will 
degrade the quality of cane juice. Raw juice from green cane, which had been topped, but still 
retained side leaves, was treated with 10% added soil. Two soils from the Louisiana cane growing 
area, Sharkey clay and Norwood silty clay loam were tested. The juice was treated for 30 minutes 
in a shaker either at room temperature (25°C) or heated (80°C). Changes in pH, color, total 
polysaccharide, ash and filtration rate were noted. Both soils decreased color and total 
polysaccharide and increased the filtration rate. pH and ash were not significantly changed. 

INTRODUCTION 

The goal of cane harvesting is to obtain the highest quality cane juice possible in order to 
facilitate production of raw sugar, and to obtain the highest yield, in order to maximize raw sugar 
production. The quality of cane juice is affected by many factors ~ the variety and maturity of the 
cane, weather conditions, diseases, harvesting conditions, cut-to-crush delays, and the amount of 
trash incorporated into the crushed cane. 

The 12 th Edition of the Cane Sugar Handbook (Chen and Chou, 1993) defines field trash as 
leaves, tops, dead stalks, roots, soil, etc., delivered together with cane. 

In South Africa (Chen, 1 985) it was reported that for each 1 % addition of tops to clean cane, 
the color of clear juice was increased by 1.3%, while with each 1% addition of mud to clean cane, 
the color of clear juice was increased by 3.6%. Purchase, et ah, (1991) confirmed the deleterious 
effect of leafy trash on the color and turbidity of juice. Ivin and Doyle (1989) in Australia, 
documented the harmful effect of leafy trash on cane juice quality. Legendre, et ah, (1996) showed 
a 1.6% decrease in raw juice color for each 1% added increment of a silty clay loam (Mhoon) from 
Louisiana, and a 1 3% increase in juice color for every 1 % leafy cane trash added, up to the 1 0% level. 
When mixtures of leafy trash and soil were added to juice, the competing effects of the mud (removed 
color) and the leafy trash (added color) were clearly evident. Godshall, et ah, (2000) studied the 
effects of various harvest practices in Louisiana on the color and polysaccharide concentration in cane 



101 



Godshall et al.: The Effect of Two Louisianl Soils on Cane Juice Quality 

juice. The presence of green leaves, especially tops, significantly increased both color and 
polysaccharides in cane juice. 

Figures 1 and 2 show the results of a previously unpublished study conducted on samples for 
the American Sugar Cane League. Addition of 5% Sharkey clay to cane juice from topped cane with 
side leaves decreased color to the level of hand stripped clean cane juice. Addition of 10% Sharkey 
clay to the same juice decreased polysaccharide to the level of hand stripped clean cane juice, 
representing a decrease of 20% color and 30% polysaccharide. 



Figure 1. Effect of 5% and 10% Sharkey clay on juice color 



o 
o 
O 

* 
o 



15000 



12000' 



0000 



6000 ■ 



3000 ■ 




BCD 

Treatment 



Figure 2. Effect of 5% and 10% Sharkey clay on juice polysaccharide level. 



E 

Q. 

a 

C© 

a> 
tj 

'C 
at 
.c 
o 
o 

CO 
CO 

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o 
a. 

© 
o 

"5 




102 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Polysaccharides in Cane Juice 

Polysaccharides are naturally present in milled cane juice. They include starch and soluble 
cell wall polysaccharides that are released when cane is crushed and the cells disrupted. Sugarcane 
polysaccharides are associated with high molecular weight color in cane juice, may increase viscosity, 
and contribute to increased color and turbidity in raw sugar. The levels of polysaccharides in cane 
juice range from 0.4-0.8% dissolved solids, with leaves and tops contributing to the higher levels 
(Godshall, et al., 2000). The concentration of polysaccharide in cane juice is also influenced by the 
cane variety, but not as much as whether or not green leaves are included in the crush. 

Louisiana Soils 

Sugarcane in mainly grown in the soil areas known as the Subtropical Mississippi Valley 
Alluvium, with the dominant soils being Sharkey, Mhoon and Commerce. Some cane is also grown 
in the extreme southern part of the Red River Valley Alluvium in Norwood soil. Commerce and 
Mhoon soils are friable silt loams and silty clay loams. Sharkey soil is clayey. The Sharkey series 
consists of very deep, poorly drained, very slowly permeable soils that formed in clayey alluvium. 
These soils are on flood plains and low terraces of the Mississippi River. Norwood soils occupy low 
natural levees at the highest elevations of the flood plains. The reddish-brown color of Norwood is 
a characteristic of the geological sediments of the Permian Red Bed deposits on the eastern slope of 
the Rocky Mountains which were carried into Louisiana by the Red and other rivers. Norwood is 
a silty loam soil (Lytle). 

MATERIALS AND METHODS 

Norwood (fine-silty, mixed, superactive, hyperthermic Fluventic Eutrudept) and Sharkey 
(very-fine, smectitic, thermic Chromic Epiaquerts) soils were provided by Chris Finger at the USDA 
Sugarcane Research Unit in Houma, Louisiana. The soils were washed and decanted of trash and 
dried and sieved ( <2 mm) before using. 

Raw cane juice consisted of 6 samples from green cane, topped, with side leaves, left on a 
heap for 1, 2 or 3 days (2 samples of each), provided by the American Sugar Cane League. Samples 
had been kept deep frozen prior to use and were microwave defrosted. 

To test the effect of the soil, 5 g of soil was added to 50 ml of cane juice, then placed on a 
gyratory shaker for 30 min. Experiments were conducted at 25°C and 80°C. Treated juice was 
analyzed for pH, color, total polysaccharides (TPS), ash and filtration rate. Color and conductivity 
ash were measured using standard ICUMS A methods (ICUMS A 1 998). Total polysaccharides were 
determined by the SPRI method (Roberts, 1 980). Filtration rate was determined as ml cane juice that 
passed through a 47 mm diameter, 0.45 \i pore-size membrane in 5 minutes, using vacuum at 30 in 
Hg, and reported as ml/min. 

Soil chemical analysis was done by the Soil Testing Laboratory at Louisiana State University. 
Organic matter was determined by Walkley-Black wet oxidation (Nelson and Sommers, 1982), soil 



103 



Godshall et al.: The Effect of Two Louisianl Soils on Cane Juice Quality 

pH by a 1 : 1 soil: water ratio in deionized water, and ions were extracted with 1M ammonium acetate, 
pH 7.0, and analyzed by ICP. Soil texture was determined by the hydrometer method (Day 1965). 



RESULTS AND DISCUSSION 



Properties of the Soils 



Tables la and lb show the properties of the two soils under test. The cation exchange 
capacity (CEC) is the sum of the basic cations present on the soil matrix. It is used as an index of the 
total exchange capacity of the soil. The magnitude of the CEC is strongly correlated to the soil's 
content of clay and organic matter. The greater CEC for the Sharkey soil is associated with this soil's 
higher clay content and the predominance of smectite (principally montmorillonite) minerals in the 
clay fraction. Montmorillonite, and other smectite clay minerals, are expansible layer silicates. They 
possess a high CEC, large surface area and due to their ability to adsorb large quantities of water have 
a significant shrink-swell potential (Borchardt, 1977). 



Table la. Chemical pro 


perties of Louisiana soils 












Soil 


pH 


CEC* 

meq/100 g 


P 


Na 


K 


Ca 


Mg 


m 


g/kg soil (ppm) 


Sharkey 


6.0 


30.5 


162 


68 


325 


4215 


1007 


Norwood 


7.5 


9.4 


175 


31 


201 


1307 


269 



Table lb. Physical properties of Louisiana soils 








Soil 


Organic Matter, % 


Sand, % 


Silt, % 


Clay,% 


Texture & Color 


Sharkey 


0.51 


28.5 


22.2 


49.3 


Clay, brown 


Norwood 


0.98 


46.8 


39.6 


13.6 


Loam, red 



*CEC = Cation Exchange Capacity. 

Effect of Heat on Cane Juice 

Table 2 reports the composition of the cane juice at room temperature, and Table 3 shows 
the composition of the juice after 30 min at 80°C. Heat decreased the juice color by 4.33% and total 
polysaccharide concentration by 6.05%. Ash increased 4.69% and filtration rate increased 14.9%. 
There was essentially no change in pH (0.02 pH unit decrease at 80°C). The data are summarized 
in Table 4. 

Note should be made of the fact that the total polysaccharide concentration did not change 
during the 3 days the green cane stalks were on the heap. An earlier study had shown that whole, 
green stalks, piled in a small heap in cool weather remained stable for 3 days (Godshall, et al., 2000). 



104 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 2. Analytical results on cane juice before soil treatment. (Control, 25°C) 



Juice 


pH 


Color, ICU 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


G-33, 34 (Day 1) 


5.64 


11,091 


4717 


2.72 


0.98 


G-36, 37 (Day 1) 


5.68 


9,281 


5795 


2.52 


0.70 


G-49, 50 (Day 2) 


5.60 


12,150 


5688 


2.69 


0.78 


G-51,55(Day2) 


5.66 


9,372 


5463 


2.35 


0.94 


G-81,83(Day3) 


5.62 


9,127 


4814 


2.51 


0.95 


G-82, 84 (Day 3) 


5.50 


9,752 


5184 


2.59 


0.88 


Mean 


5.62 


10,129 


5277 


2.56 


0.87 



ICU = ICUMSA Color Units 
TPS = Total polysaccharide 



Table 3. Analytical results on heated cane juice 
(Control, 80°C, shaken 30 min) 


before soil treatment. 




Juice 


pH 


Color, ICU 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


G-33, 34 (Day 1) 


5.41 


11,170 


4569 


2.77 


1.1 


G-36, 37 (Day 1) 


5.66 


9,098 


5474 


2.66 


0.74 


G-49, 50 (Day 2) 


5.58 


11,015 


5359 


2.80 


0.95 


G-51,55(Day2) 


5.66 


8,666 


4796 


2.50 


1.0 


G-81,83(Day3) 


5.62 


9,072 


4473 


2.65 


1.1 


G-82, 84 (Day 3) 


5.58 


9,118 


5076 


2.67 


1.1 


Mean 


5.59 


9,690 


4958 


2.68 


1.0 



Table 4. Summary of cane juice, heated and not heated. (The effect of heat on cane juice.) 



Sample 


pH 


Color, ICU 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


25°C 


5.62 


10,129 


5277 


2.56 


0.87 


80°C 


5.59 


9,690 


4958 


2.68 


1.0 


% change in heated 


-0.53% 


-4.33% 


-6.05% 


+4.69% 


+14.9% 



105 



Godshall et al.: The Effect of Two Louisianl Soils on Cane Juice Quality 

Effect of Soil on Cane Juice 

Tables 5 and 6 report the effect of Sharkey clay on cane juice at 25 °C and 80°C. 
Table 5. Analytical results on cane juice after treatment at 25°C with Sharkey clay 



Juice 


pH 


Color, ICU 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


G-33, 34 (Day 1) 


5.67 


10,222 


4731 


2.57 


2.8 


G-36, 37 (Day 1) 


5.67 


7,585 


4012 


2.34 


1.8 


G-49, 50 (Day 2) 


5.62 


10,080 


4204 


2.49 


2.8 


G-51,55(Day2) 


5.68 


8,028 


3780 


2.35 


2.4 


G-81,83(Day3) 


5.62 


7,726 


3135 


2.38 


3.4 


G-82, 84 (Day 3) 


5.54 


8,578 


4019 


2.44 


2.8 


Mean 


5.63 


8,703 


3980 


2.43 


2.67 



Table 6. Analytical results on cane juice after treatment at 80°C with Sharkey clay 



Juice 


pH 


Color, ICU 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


G-33, 34 (Day 1) 


5.56 


10,139 


3534 


2.64 


1.1 


G-36, 37 (Day 1) 


5.59 


7,891 


4531 


2.53 


0.74 


G-49, 50 (Day 2) 


5.52 


10,254 


4305 


2.68 


0.94 


G-51,55(Day2) 


5.59 


7,991 


4014 


2.44 


1.1 


G-81,83(Day3) 


5.53 


9,420 


3911 


2.55 


1.2 


G-82, 84 (Day 3) 


5.49 


9,439 


4188 


2.59 


1.1 


Mean 


5.55 


9,189 


4081 


2.57 


1.03 



The effect of Sharkey on cane juice color in each sample at 80° C is shown in Figure 3 and 
on polysaccharides in Figure 4. In Figure 3, It is noted that samples 5 and 6 had a slight increase in 
color compared to the controls. Since this was cane juice from cane left on the heap row for 3 days, 
it is possible that changes in the type of colorant in the cane had occurred over that period of time. 
The same effect was noted with the Norwood soil on the day 3 samples. The removal of 
polysaccharides, however, was not affected in samples 5 and 6. 



106 



. 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Figure 3. Effect of Sharkey clay on juice color at 80°C. 



Control 



EZI Sharkey 



O 
O 

o 



12000 
9700 
7400 
5100 
2800 
500 



1 




F 


r 


/ 


i 


-52% 



3 4 S 6 Avg 

Sample, 80 C 



Figure 4. Effect of Sharkey clay on juice polysaccharides at 80°C. 



CO 

2 
1 



a 
a 

w 

* 



o 
o 

s 

O 

Q. 



Control 



Sharkey 



6000 



4900 



3900 



2700 



1600 



500 




6 Avg 



Sample, 80 C 



107 



Godshall et al : The Effect of Two Louisianl Soils on Cane Juice Quality 

Tables 7 and 8 report the effect of Norwood on cane juice at 25°C and 80°C. 



Table 7. Analytical results on cane juice after treatment at 25°C with Norwood clay loam 


Juice 


PH 


Color, ICU 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


G-33,34(Dayl) 


5.68 


10,790 


3911 


2.71 


1.2 


G-36, 37 (Day 1) 


5.86 


8,488 


4896 


2.63 


0.7 


G-49, 50 (Day 2) 


5.80 


10,932 


4587 


2.77 


1.0 


G-51,55(Day2) 


5.85 


8,459 


4246 


2.53 


1.2 


G-81,83(Day3) 


5.78 


9,150 


3810 


2.60 


1.3 


G-82, 84 (Day 3) 


5.74 


9,887 


4327 


2.51 


1.3 


Mean 


5.79 


9,618 


4296 


2.63 


1.1 



Table 8. Analytical results on cane juice after treatment at 80°C with Norwood clay loam 


Juice 


PH 


Color, ICU 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


G-33, 34 (Day 1) 


5.51 


10,828 


3455 


2.74 


1.4 


G-36, 37 (Day 1) 


5.71 


8,611 


4509 


2.61 


1.0 


G-49, 50 (Day 2) 


5.65 


10,415 


4019 


2.82 


1.5 


G-51,55(Day2) 


5.72 


8,329 


3888 


2.51 


1.4 


G-81,83(Day3) 


5.61 


9,173 


3529 


2.62 


1.4 


G-82, 84 (Day 3) 


5.54 


9,209 


4063 


2.68 


1.4 


Mean 


5.62 


9,428 


3911 


2.66 


1.35 



Table 9a compares the mean results of all treatments. Table 9b shows the percentage changes 
with soils treatment; comparisons are made for the same temperature of treatment. 



108 



. 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 9a. Summary of means of treated and untreated samples 



Treatment 


pH 


Color, ICU 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


Control, 25°C 


5.62 


10,129 


5277 


2.56 


0.87 


Control, 80°C 


5.59 


9,690 


4958 


2.68 


1.0 


Sharkey, 25°C 


5.63 


8,703 


3980 


2.43 


2.67 


Sharkey, 80°C 


5.55 


9,189 


4081 


2.57 


1.03 


Norwood, 25°C 


5.79 


9,618 


4296 


2.63 


1.1 


Norwood, 80°C 


5.62 


9,428 


3911 


2.66 


1.35 



Table 9b. Summary of changes in tr 
cane juice at their respective heatin^ 


eated cane juice samples. Treatments are co 
2 regime. 


mpared to untreated 


Treatment 


PH 


Color 


TPS, ppm 


Ash,% 


Filtration rate 
(ml/min) 


Sharkey, 25°C 


+0.18% 


-14.1% 


-24.6% 


-5.08% 


+207% 


Sharkey, 80°C 


-0.72% 


-5.2% 


-17.7% 


-4.10% 


+3.0% 


Norwood, 25°C 


+3.02% 


-5.0% 


-18.6% 


+2.73% 


+26.4% 


Norwood, 80°C 


+0.54% 


-2.7% 


-21.1% 


-0.75% 


+35.0% 



pH. pH showed no significant change for either soil or either temperature. There was a 3% increase 
in pH in the Norwood treated juice at 25°C. 

Color. Sharkey clay removed 14.1% color at 25°C but only 5.2%at80°C. Norwood removed 5.0% 
at 25°C and 2.7% at 80°C . Both soils take out more color at 25°C than at 80°C, indicating a release 
of color at the higher temperature. The higher color retention by Sharkey clay is a function of its 
higher ion exchange capacity for the charged colorants in cane juice. As previously stated, this 
retention is probably associated with the montmorillonite present in the clay fraction. 

Total Polysaccharides. Both soils removed significant amounts of polysaccharides. Sharkey clay 
removed 24.6% polysaccharides at 25°C and 17.7% at 80°C . These results are similar to those 
previously encountered with the Sharkey clay (unpublished results mentioned in the Introduction). 
Norwood removed 18.6% at 25°C and 21.1% 80°C . 



109 



Godshall et a).: The Effect of Two Louisianl Soils on Cane Juice Quality 

Ash. Sharkey clay gave a 4-5% decrease in ash, which was contrary to what might have been 
expected. Both soils had been washed, so ash solubilized from the soils was probably already 
removed. The decrease in ash caused by Sharkey clay may also be a function of the exchange 
capacity of the Sharkey clay. Whether these soils contribute to the ash load in juice in the field still 
needs to be investigated. Norwood clay loam caused a small increase of ash, 2.73% at 25°C and a 
very slight decrease of 0.75%, at 80°C. 

Filtration rate. Norwood increased the filtration rate 26.4% at 25°C and 35.0% at 80°C. Sharkey 
clay doubled the filtration rate at 25°C (207%), but showed no change at 80°C. This result is 
probably anomalous, as many filtrations with Sharkey clay in cane juice had shown as much as a 10- 
fold increase in filtration rate at room temperature. However, with this series, the clay was allowed 
to settle for only a few minutes, and it is possible that the fines clogged the filter membrane. It 
should be noted that this filtration test is very stringent, as sample is filtered through a very tight 
medium of 0.45 u, and a different filtration medium may show different results. 

CONCLUSIONS 

This study has shown that two soils, Norwood and Sharkey, found in the Louisiana cane 
growing area have the ability to remove a small amount of color and a significant amount of 
polysaccharide from cane juice, while improving filterability. At the same time, the ash level of the 
juice is not changed, or is slightly decreased, and there is no deleterious effect on pH. Sharkey soil, 
because of its clay content and greater ion exchange capacity, removes slighly more color, but both 
Norwood and Sharkey remove about the same amount of polysaccharide. 

The larger color removal by Sharkey clay in earlier studies is attributed to the fact that the 
samples had stayed in contact with the soil over a long storage period prior to analysis, whereas the 
samples in the current study had been exposed to the soil for only 30 min. However, the removal of 
polysaccharides was not affected by storage. 

These results are of interest because they are contrary to the reports from South Africa and 
Australia, which indicate large color increases in cane juice in the presence of soils. 

This work is not intended to advocate or recommend bringing soil in with harvested cane. 
The cleaner the juice, the better in the long run. Soil has destructive effects on the mills, increases 
the burden to the clarifier, and contributes to disposal costs. The results are of considerable interest 
because they can help explain some anomalous behavior in cane juice quality when there is a lot of 
mud brought into the mill. It may be possible, in the future, to consider how to exploit the beneficial 
effects of the soils in the cane growing area of Louisiana. 



110 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

REFERENCES 

1. Chen, J.C.P., and Chou, C.C.. (1993) Cane Sugar Handbook, 12 th Edition, John Wiley & 
Sons, Inc., New York, 55, 563, 886-903. 

2. Chen, J.C.P. ( 1 985) Meade-Chen Cane Sugar handbook, 1 1 * Edition, John Wiley & Sons, 
Inc., New York, 59. 

3. Day, P.R. (1965) Particle fractionation and particle-size analysis. Pages 545-567, In C.A. 
Black (ed.) Methods of Soil Analysis - Part 1 . Agronomy Society of America, Inc., Madison, 
WI. 

4. Fors, A., and Arias, R. (1997) The effects of trash components in factory performance. 
Sugar J., Dec. 1997,25-26. 

5. Godshall, M.A., Legendre, B.L., Richard, C, and Triche, R (2000) Effect of harvest 
system on cane juice quality. Proc. Sugar Processing Research Conf, 222-236. 

6. ICUMSA Methods, 1994/ First Supplement, 1998. Methods of the International 
Commission for Uniform Methods of Sugar Analysis, ICUMSA Publications, Norwich 
England. Method GS1-7, Raw Sugar Solution Colour; Method GS 1/3/4/7/8- 13, 
Conductivity Ash in Raw Sugar. 

7. Ivin, P.C., and Doyle, CD. (1989) Some measurements on the effect of tops and trash on 
cane quality. Proc. Australian Soc. Sugar Cane Technol, 1-7. 

8. Legendre, B.L., Godshall, M. A. and Miranda, X.M. (1996) A preliminary study on the 
effect of sugarcane leaves and mud on color in sugarcane juice. Proc. Sugar Processing 
Research Conf., 447-452. 

9. Lytle, S.A. The morphological characteristics and relief relationships of representative 
soils in Louisiana, http://www.agctr.lsu.edu/hudnall/4058/32.pdf 

10. Nelson, D.W. and L.E. Sommers. (1982) Total carbon, organic carbon and organic 
matter. Pages 539-577. In Methods of Soil Analysis. Agronomy No. 9, Part 2, American 
Society of Agronomy, Madison, WI 

11. Purchase, B.S., Lionnet, G.R.E., Reid, M.J., Wienese, A., and DeBeer, A.G. (1991) 
Options for and implications of increasing the supply of bagasse by including tops in trash 
with cane. Proc. Sugar Processing Research Conf, 229-243. 

12. Roberts, E.J. ( 1 980) Estimation of the soluble polysaccharides in sugar: A rapid test for 
total polysaccharides. Proc. Technical Session Cane Sugar Refining Research, 130-133. 



Ill 



Singleton et al.: A New Polarimetric Method for the Analysis of Dextran and Sucrose 

A NEW POLARIMETRIC METHOD FOR THE ANALYSIS OF DEXTRAN 

AND SUCROSE 

Victoria Singleton 1,2 , Dr. Jennifer Horn 1 , Prof. Chris Bucke 2 and Dr. Max Adlard 2 

1 . Optical Activity Ltd. Cambridgeshire, England. 
2. University of Westminster, London, England. 

ABSTRACT 

A new method for dextran quantification has been developed and field-trialled in Jamaica, 
in association with the Sugar Industry Research Institute. The method uses a near infrared (NIR) 
polarimeter and a specific dextranase. The dextranase selectively breaks down the dextran into 
sugars of lesser specific rotations without affecting any other substance present in the juice. The 
initial dextran concentration is derived from the calibration curve of the change in observed optical 
rotation (OR) due to enzymatic hydrolysis and output automatically by the polarimeter. Readings 
are not affected by the molecular weight of the dextrans, the entire procedure takes less than 10 
minutes to perform and it is semi-automated. Use of a NIR polarimeter negates the need for lead 
acetate clarification. The method is suitable for both juice and raw sugar samples. 

Keywords: Dextranase, Near Infrared (NIR) polarimeter, Polysaccharides. 



INTRODUCTION 

Dextran is produced by microorganisms which infect the cane and feed on the sucrose; 
therefore, the presence of dextran immediately indicates lost sugar. The bacteria are mainly 
Leuconostoc species and are ubiquitous in the soil. They enter the cane at places of exposed tissue 
caused by machine harvesting, cutting, burning, growth, freezing, disease and pests. Any delay in 
the kill-to-mill time allows the bacteria to proliferate and the dextran levels to soar, especially in 
wet muddy cane. 

The name dextran refers to a large family of glucose polymers whose structures and 
subsequent properties can vary widely. Technically the molecular weight (M r ) can range between 
1500 and several million; therefore, a dextran of say 1 million M r has potentially thousands of 
possible structures due to its branched nature. This massive variation in structure poses a huge 
challenge for any analyst trying to detect the molecules especially against a substantial background 
of saccharides with similar structures and properties. 

Consequences of Dextran 

Dextran is highly dextrorotatory, approximately three times that of sucrose, and, since the 
farmer is largely paid on the basis of the polarimeter reading, there is an obvious need for assaying 
for dextran in the core lab. This would allow correction of the falsified reading and identification of 
the sources of dextran contamination entering the factory. The problems associated with dextran 
contamination in both the factory and the refinery are well documented in the literature and so are 
briefly summarised below in Table 1 . 



112 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 



Table 1. Summary of the detrimental effects of dextran in terms of the resulting losses. 



Production losses 


Sucrose losses 


Direct financial losses 


Increased viscosity leads to 


As dextran formed in cane 


False pol reading leads 


reduced throughput due to: 




to overpayment to 


-poor filterability 


To molasses (melassigenic effect) 


farmer 


-reduced evaporation rate 






-reduced flocculation rate 




In trade of raw sugar as 


-slow mud settling 




part of dextran penalty 
system using unreliable 


Poor crystallization (elongation) 




tests 



Most dextrans are insoluble in alcohol making sugars and syrups containing it unsuitable for 
the production of alcoholic beverages. The two most important factors in the purchase of raw sugar 
are the polarisation and the crystal size distribution. Both of these are dramatically affected by the 
presence of dextran. The affination rate (removal of molasses from the crystal surfaces) is greatly 
reduced, leading to further losses of sucrose to the molasses. It is for this reason that high penalties 
are imposed on dextran contamination when importing raw sugar for refining. 

Typically, the problem is treated in retrospect by the addition of crude dextranase enzyme. 
The enzyme works by hydrolysing the large dextran molecules into smaller oligosaccharide 
products which do not affect the viscosity as much. This is an expensive treatment largely because 
of the cost of the enzyme. Without accurate knowledge of the dextran levels in the process, it is 
impossible to gauge the correct amount of dextranase required. 

Dextran detection is and long has been dominated by two equally questionable techniques, 
namely the haze test (Keniry et al., 1969) and the Roberts test (Roberts, 1983). Both tests exploit 
dextran's tendency to precipitate out of solution in alcohol. This approach has long been proved 
unreliable and inaccurate as well as non-specific, costly and time-consuming (Kubik et al.; 1994, 
DeStefano and Irey, 1986; Curtin and McCowage, 1986; and Brown and Inkerman, 1992). 

Many alternative tests have been proposed and investigated, often as modifications on the 
theme of alcohol precipitation with various chemical and/or enzymatic inclusions. Although these 
tests are often arguably more accurate and reproducible, they are generally expensive and labor- 
intensive to perform. Hence, they are unattractive to the majority of sugar technologists. There is a 
longstanding need for a fast, accurate, simple and inexpensive method for the detection and 
quantification of dextran. 

The Optical Activity Dextran Kit 

Until recently, most polarimeters used the sodium wavelength of 589nm, which is yellow 
light. To achieve accurate results sugar samples had to be clarified and largely decolourised using 
lead subacetate. Now multi-wavelength instruments are readily available. Measurements of the 
sucrose content of cane juices by NIR polarimetry at 880nm are not affected by the yellow/brown 



113 



Singleton et al.: A New Polarimetric Method for the Analysis of Dextran and Sucrose 

color remaining after conventional filtration using a filteraid. Readings obtained using NIR 
polarimetry in comparison to those at the sodium wavelength have been previously shown to be 
more reproducible and more sensitive to interference by high dextran concentrations (Wilson, 
1996). 

Not only does the poisonous and environmentally unsound lead subacetate treatment 
damage enzymes; it also removes an unknown portion of the dextrans, making it an unsuitable 
clarifier in both this and other dextran methods. This latter point, of dextran removal, is also the 
case with a number of the more recent commercial clarifiers. In this method a conventional filter- 
aid is employed which successfully clarifies the juice or sugar solution without removing dextran. 
This filter-aid is paramount to the successful clarification of the juice sample. 

This procedure is centered on the use of a NTR polarimeter manufactured by Optical 
Activity Ltd. in conjunction with a specific dextranase totally free of invertase activity. The dextran 
is hydrolysed into smaller dextrans and constituting smaller units such as isomaltotriose, isomaltose 
and glucose, each of which is less optically active than dextran. The hydrolytic reactions are rapid 
when the enzyme is used in excess. The change in rotation between that of the original sample and 
that observed at a predetermined time after the addition of dextranase can be calibrated to the 
original concentration of dextran present in the sample. 

MATERIALS AND METHODS 

The NCR polarimeter used was a SacchAAr 880, manufactured by Optical Activity Ltd. The 
polarimeter sample tube (also manufactured by Optical Activity Ltd.) was an A2 with a bore of 
4mm and 200mm path length. The tube is jacketed and the temperature maintained at 20°C using 
an Index Instruments Ltd. thermocirculator. 

The enzyme concentration in the sample and the total sample volume were previously 
optimised for this procedure and are 1 ml enzyme solution (see below) added to 19 ml sample. A 
selected pure dextranase preparation with activity of 30,400 units/ml is diluted 1:5 in distilled 
water. It is always used at this dilution, except for those experiments that involve the use of 
impregnated filter papers. In order to assist the user and prevent any error in measuring quantities of 
liquid, the enzyme will be available commercially in this form. These papers will consistently carry 
the required amount of dextranase to carry out the reaction within the desired time limit and have 
already been tested in field trials during the work with the Sugar Industry Research Institute of 
Jamaica. 

RESULTS 

Effect of Molecular Weight 

It was necessary to determine if the extent of the change in rotation due to hydrolysis is 
influenced by molecular weight. The following different molecular weight range dextrans were 
dried for a week in a desiccator containing P2O5 and then made up to 4000ppm in distilled water: 

-9,5kDa (Sigma Cat. No. D-9260) 

-71.4kDa (Sigma Cat. No. D-3759) 

-2,000kDa (Sigma Cat. No. D-5376) 



114 









Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

After quantifying the control readings, 1ml of dextranase solution was added to 19ml of 
dextran solution, rapidly shaken and injected into the sample tube. The results (Table 2) were 
recorded when the readings had reached a stable minimum. It can be observed that there is no 
systematic or significant effect of M r on the change in OR due to enzymatic hydrolysis. The 
variability in the results is thought to be due to structural and preparative differences between the 
commercially available dextrans reflected by differences in appearance (powders / flakes). 

Table 2. The change in OR due to enzyme action for three different molecular weight dextrans. 



Mr of Dextran (Daltons) 


Change in OR °Z due to enzyme action 


9.500 


1.26 


71 400 


1 1Q 


9.000.000 


1.34 



Confirmation of Enzymatic Specificity 

Many commercial enzyme preparations contain several enzyme activities in addition to the 
major activity that is purchased. It was necessary to ensure that the dextranase preparation was 
unable to hydrolyse sucrose and non-dextran polysaccharides. 

A selection of possible alternative saccharides were chosen and 5% solutions made up in 
distilled water. 1ml of dextranase solution was added to 19ml of the analyte solution and the OR 
observed for 20 minutes. Little or no change in the reading over time (other than that accounted for 
by the controls and the accuracy of the instrument) indicates no reaction (Table 3). 

Table 3. The effect of dextranase on other possible analytes. 



Analvte 


Result 


Sucrose 


No reaction 


Dextrin 


No reaction 


Xvlan 


No reaction 


Pectin 


No reaction 



Although the above list is non-exhaustive, there are no apparent reactions with these substances, 
which form the majority of dissolved carbohydrates constituent in sugar samples. 

Calibration Curve Constructed in 15% Sucrose 

Using the calibration curve and the preloaded filter papers, it becomes possible to transform 
the assay from a fairly technical laboratory assay into a kit for use by unskilled workers. The 
calibration data will be incorporated into the software of the polarimeter negating the need for 
lengthy calculations and reducing the chances of operator error. 

Using an 188kDa dextran (Sigma Cat No, D4876), solutions of 8000ppm, 4000ppm, 
2000ppm, 800ppm, 400ppm and 200ppm were made up in 15% sucrose (since sucrose is known to 
mildly retard the rate of the reaction with dextran via non-competitive inhibition). 



115 



Singleton et al.: A New Polarimetric Method for the Analysis of Dextran and Sucrose 

The dextranase solution was added to the dextran just prior to injection into the polarimeter 
and the OR followed for 15 minutes. The readings were recorded at 5-second intervals by a data 
collection program. 



Calibration Curve in 15% Sucrose 



Thousands 
Dextran (ppm) 



Figure 1 . The relationship between dextran concentration and change in OR due to hydrolysis by 
dextanase enzyme. 

The relationship shown in Figure 1 is clearly linear in character but has a slight curve 
(which in this data is a 39.5% change in x/y). This relationship is reproducible on a day-to-day basis 
and has been curve-fitted and the algorithm incorporated into the instrument's software to allow 
accurate automatic readings of dextran concentration to be instantly generated. 

Detecting Spiked Dextran in Cane Juice 

"Dextran-free" cane juice was obtained and subjected to standard addition with a known 
mass of dextran to demonstrate that dextran could be detected and quantified in the cane juice as 
effectively and accurately as in distilled water. 

A 2000ppm solution of dextran (71.4kDa) was made up in distilled water and the OR 
determined. 200ml of cane juice were vacuum filtered with fllteraid (2g/100ml) and the OR 
determined. O.lg dextran was weighed into a 50ml flask, which was filled to the mark with cane 
juice and the OR determined. All three samples where then subjected to the new dextran method 
(Table 4). 



116 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Table 4. Change in OR (°Z) due to enzyme treatment in spiked samples of water and cane juice. 



Sample 


OR °Z before enzyme 
treatment 


OR °Z after enzyme 
treatment 


Change in OR 
°Z 


Water 4- dextran 


?..n 


1.52 


061 


Juice 


50.47 


50.47 


0.00 


Juice + dextran 


52.60 


52.00 


0.60 



The assay behaves the same in cane juice as in water as shown by the essentially identical 
values of change in rotation due to dextranase addition. 

Confirmation of the Analytical Precision and Reliability 

Using a 40% raw cane sugar solution high in natural dextran the assay was performed 1 
times on the same sample to demonstrate the precision of the test and therefore the reliability of a 
single measurement approach. 

The results showed absolutely no variance within the accuracy range of the instrument, 
which is +/- 0.02°Z. This indicates the measurements are entirely repeatable under standard 
laboratory conditions. 

Observation of Dextran Growth Over Time 

The following work was carried out during field trial work in association with SIRI at their 
Central Laboratory, Mandeville, Jamaica. Using green cane deliberately contaminated with dextran- 
producing bacteria, the test was performed repeatedly over a 4-day period to demonstrate the 
growth of dextran over time. 

Enough cane was crushed from the pile to collect 500ml of raw juice. Filter-aid was added 
in the concentration of 2g/ 100ml and after stirring, the mixture was vacuum filtered through a 
Millipore AP20 prefilter (as before). The OR of the clear cane juice was determined on the 
polarimeter. 60ml of juice were incubated on a shaker for 7 minutes with 1 dextranase- 
impregnated filter / 30ml and the OR determined at 10 minutes (after addition of impregnated 
filters). 

The increase of dextran levels is clearly seen in the rising values of the difference between 
the control and test readings (Table 5). The dextran is calculated by using the quadratic equation 
fitted to the calibration curve. The lack of exposure of the cane to mud and rain during the test 
period would explain why the increase of dextran is less than that expected in an average cane yard. 



117 



Singleton et al.: A New Polarimetric Method for the Analysis of Dextran and Sucrose 

Table 5. Increase in dextran over time. The dextran is calculated by using the quadratic equation 
fitted to the calibration curve. 



Day 


Control (OR°Z) 


Test 
OR(°Z) 


Difference 
OR(°Z) 


Dextran 
(ppm) 


Corrected 
OR(°Z) 


1 


60.35 


59.61 


0.74 


1431.72 


58.80 


2 


59.43 


58.57 


0.86 


2279.23 


56.97 


3 


61.80 


60.85 


0.95 


2551.58 


59.04 


4 


60.12 


59.00 


1.12 


3064.16 


56.81 



SUMMARY 

From the above set of experiments, it is evident that the theoretical basis of the assay 
remains sound when put into practice. The enzyme selected for this work appears to be specific for 
a single substrate, namely dextrans. The calibration curve has been previously shown to be 
unaffected by factors such as molecular weight of the substrate and the pH of the medium in which 
measurements are made with detection limits that cover the entire range of market requirements. 
This assay procedure is robust, rapid, simple to perform and through subsequent development of the 
instrument is now semi-automated. The presence of dextran in sugar represents financial losses at 
almost every stage of the process from cane to cube. It is hoped that this new analytical method will 
now make it possible for both the factory and the refinery to identify dextran sources and take an 
informed approach to employing the correct remedial actions in both the short and long term. 

ACKNOWLEDGEMENTS 

The author wishes to acknowledge the invaluable assistance of the Sugar Industry Research 
Institute, Jamaica. 

REFERENCES 

1. Brown, C. F. and Inkerman, P. A. 1992. Specific method for quantitative measurement of 
the total dextran content of raw sugar. J. Agric. Food Chem. 40:227-233. 

2. Curtin, J. H. and McCowage, R. J. 1986. Dextran measurement in cane products. Proc. 
ISSCT. 19:755-764. 

3. DeStefano, R. P. and Irey, M. S. 1986. Measuring dextran in raw sugars - historical 
perspective and state of the art. J. Am. Soc. Sugar Cane Technol. 6:1 12-120. 

4. Imrie F. K. E. and Tilbury R. H. 1972. Polysaccharides in sugar cane and its products. Sugar 
Technol. Rev. 1:291-361. 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

5. Keniry, J.S., Lee, J. B. and Mahoney, V.C. 1969. Improvements in the dextran assay of 
sugar cane materials. Int. Sugar J. 71 :230-233. 

6. Kubik, C, Galas, E. and Sikoro, B. 1994. Determination of dextran in raw beet juices by the 
haze / enzymatic method. Int. Sugar J. 96(1 149):358-360. 

7. Muller, E.G. 1981. Dextran. Tate and Lyle's SIA. 43(5):147-148. 

8. Roberts, E. J. 1983. A quantitative method for dextran analysis. Int. Sugar J. 85:10-13. 

9. Wilson, T. E. 1996. A comparison of raw sugar polarisation methods. Int. Sugar J. 
98(1 168): 169- 174. 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

AGRICULTURAL ABSTRACTS 

The Louisiana Basic Breeding Program-Past, Present, and Future 

Thomas L. Tew 

USDA-ARS Sugarcane Research Center 
Houma, LA 

With the extraordinary success of LCP85-384, a Saccharum spontaneum BC4 derivative, 
released in 1993, and the release of HoCP85-845, also a S. spontaneum BC4 derivative, it is 
obvious that the USDA-ARS Basic Breeding Program at Houma, LA has provided tremendous 
dividends to the Louisiana sugar industry. Both clones were bred during the year 1980, and both 
involved S. spontaneum clone, US56-15-8. Some questions we need to address now are "What 
has happened during the past 20 years of crossing with basic germplasm that would give us 
reason to believe that further benefits can be expected from the basic breeding program?" 
"Where are we today in our basic breeding program?" "What must we do to maximize the 
likelihood of success in the future?" A review of our own program along with other breeding 
programs, particularly in Argentina, indicate that, with an intensified effort and some 
modifications in our breeding and selection approach based on lessons learned from the past, we 
should expect to see further substantial genetic improvement through basic breeding. Topics 
discussed will include: 1) number of BC generations needed to obtain commercial cultivars, 2) 
years needed between BC generations, 3) need for recombination between BC generations to 
exploit desirable recessive traits, 4) use of marker-assisted selection, 5) formation of complex S. 
spontaneum crosses, and 6) greater focus on populations rather than individuals. 

Assessment of Stalk Cold Tolerance of Louisiana Varieties During the 2000-2001 Crop 

Year 

Benjamin L. Legendre 

Division of Plant Science 

Louisiana Cooperative Extension Service 

LSU Agricultural Center, Baton Rouge, Louisiana 

Harold Birkett and Jeanie Stein 

Audubon Sugar Institute 
LSU Agricultural Center, Baton Rouge, Louisiana 

The exposure of sugarcane to damaging frosts occurs in over 20 of the 79 sugarcane- 
producing countries of the world, but is most frequent on the mainland of the United States. The 
frequent winter freezes in the sugarcane area of Louisiana forced the industry to adapt to a short 
growing season (7-9 months) and a short milling season (about 3 months). Field experiments 
consisting of 3-row plots (18 ft) by 45 ft long are routinely planted at the Ardoyne Farm of the 
USDA-ARS, SRRC at Houma, Louisiana, for the estimating stalk cold tolerance of commercial 
and candidate varieties. For the 2000-2001 crop-year study, two commercial varieties, CP 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

70-321 and CP 79-318, with known cold tolerance were planted in the test as controls. Other 
commercial varieties included LHo 83-153, LCP 85-384, HoCP 85-845 and HoCP 91-555. 

Freezing temperatures that affected the Louisiana Sugar Industry during the 2000-2001 
crop-year occurred on December 20, 2000, when the minimum temperature recorded in the field 
at the Ardoyne Farm was 24°F, and again on December 21, December 30 through January 5, 
2001 and January 9 and 10. The lowest temperature of 22 °F was recorded on January 4. 
Freezing conditions prevailed for 8-15 hours during each freeze incident. Stalks of all varieties 
were frozen to the ground following the initial freeze with freeze cracks evident only after the 
January 4 freeze. 

Samples were taken the date of the first freeze and again at 7, 14, 22 and 30 days after the 
first freeze. Criteria used to measure overall stalk cold tolerance included changes in Brix, 
sucrose, purity, yield of theoretical recoverable sugar per ton of cane, pH, titratable acidity, 
dextran by both the Rapid Haze and ASI II Methods and fiber content of juice and/or cane and 
mean stalk weight. On each date of harvest, 15-stalk samples were collected from each of the 
four replications of all varieties and were divided into two sub-samples on four of the five 
sampling dates to compare the analyses of juice extracted by the conventional 3-roller mill (10 
stalks) and the pre-breaker/press method (5 stalks). On the remaining sampling date, juice was 
extracted from all 15 stalks by the 3-roller mill. Significant changes were noted in all criteria for 
all varieties, with the exception of mean stalk weight, at 22 and 30 days after the first freeze. 
Further, significant differences were also noted between varieties on each sampling date. 
Overall, the ranking of varieties for stalk cold tolerance, from best to worse, when considering 
all criteria was as follows: CP 70-321, LHo 83-153, LCP 85-384, HoCP 85-845, HoCP 91-555 
and CP 79-318. Accordingly, the classification of stalk cold tolerance (post- freeze resistance) 
for these varieties based on the results obtained during the 2000-2001 crop year is as follows: 
Very Good - CP 70-321; Good - LHo 83-153; Good to Moderate - LCP 85-384; Moderate - 
HoCP 85-845; Moderate to Poor - HoCP 91-555; and Poor - CP 79-318. The stalk cold 
tolerance for both CP 70-321 and CP 79-318 is well documented from previous studies. There 
were only slight differences in the pH and titratable acidity of the juice when comparing 
extraction methods. Although the concentration of dextran in the juice as an average of all 
varieties and all dates of sampling was considerably different between the two methods of 
analyses (1,592 and 4,102 ppm for the Rapid Haze and ASI II Methods, respectively), the 
ranking amongst varieties was similar when comparing the two methods (r = 0.98). 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Post-Freeze Performance of 16 Sugarcane Cultivars Following the December 31, 2000 

Freeze Event in Florida 

J. M. Shine, Jr. 

Sugar Cane Growers Cooperative of Florida 
Belle Glade, FL 33430 

R. A. Gilbert 

University of Florida 

Everglades Research and Education Center 

Belle Glade, FL 33430 

J. D. Miller 

USDA-ARS Sugarcane Field Station 
Canal Point, Florida 33438 

Freezing temperatures occurred for an extended period of time on the night of December 
31, 2001 and morning of January 1, 2000. Temperatures below -2°C occurred for more than 
four hours in much of the Everglades Agricultural Area. The performance of 16 cultivars 
planted in six experiments planted at five locations was characterized by determining sugar 
content per gross ton of cane. Replicated variety trials at five locations were sampled serially on 
two-week intervals following the freeze event until March 20, 2000 and ground for sugar yield. 
Four of the five locations were exposed to freezing temperatures for more than 10 hours while 
one location received no freeze injury. Sucrose content of the 16 cultivars occurring at least at 
two of the freeze damaged experiments were contrast with sucrose content at the freeze 
protected location. CP89-2143 had the highest sugar per ton of cane at 80-days post-freeze and 
demonstrated relative losses comparable to CP72-2086, a known "freeze-tolerant" cultivar. 
CP85-1308 showed the greatest relative losses following the freeze event. CP80-1743, CP84- 
1198, CP85-1382 and CP88-1762 demonstrated relative losses similar to CP70-1133, a known 
"freeze-susceptible" cultivar. 

Sugarcane Tissue Phosphorus Concentration as Affected by P Rates Applied to a Florida 

Histosol 

Y. Luo and Rosa M. Muchovej 

University of Florida 

Southwest Florida Research and Education Center 

Immokalee, Florida 

Approximately 85% of the sugarcane {Saccharum officinarum L) acreage in Florida are 
located in the Everglades Agricultural Area, where soils are typically organic in nature. 
Phosphorus, K, and several micronutrients are commonly applied to histosols to produce 
acceptable yields. Because of increasing environment concerns, P application to all agricultural 
crops has been receiving increased attention. Though many studies on sugarcane response to P 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

fertilizer have been carried out worldwide, little information is available on the effects of P 
fertilization, especially with respect to seasonal tissue P concentration, for sugarcane grown on 
Florida's histosols. The objective of this field study was to assess tissue P concentration of 
sugarcane varieties at the different growth stages in response to increasing P rates. Five P rates 
(0, 34, 67, 101, 135 kg P 2 5 kg' 1 ) and four sugarcane varieties (CP70-1133, CP72-2086, CP78- 
1628, and CP80-1827) were evaluated in a randomized complete block design (RCBD), in six 
replications at two sites. Top visible dewlap (TVD) leaf samples were collected at the early, 
grand growth, and late crop stages. Results indicated increases in tissue P concentration as P 
rate increased, especially in the early stages of crop growth. Phosphorus concentration was also 
highest in the early stages and lowest in late stages, nearing harvest date. First year, i.e., plant, 
sugarcane had higher tissue P concentration than first ratoon cane. Variety CP80-1827 presented 
the highest tissue P concentration in all the samplings. Interpretation and utilization of sugarcane 
tissue P concentrations for determining plant nutritional status and fertilizer recommendation 
should take into account time of sampling, P rate applied, and variety planted. 



Sugarcane Root and Soil Microbial Responses to Intermittent Flooding 

D.R. Morris and B. Glaz 

USD A, ARS, Sugarcane Field Station 
Canal Point, FL 33438 

S. Daroub 

Univ. Florida EREC 
Belle Glade, FL 33430 

Sugarcane is one of the most environmental friendly agricultural crops grown in the 
Everglades Agricultural Area because it can tolerate short periods of flooding and has been 
reported to have less soil organic matter oxidation compared to other agricultural crops. Soil 
oxidation results primarily from aerobic microbial activity. Since flooding reduces soil oxygen 
levels, flooding as well as growing sugarcane may reduce soil organic matter oxidation. One 
concern regarding flooding of sugarcane is that mechanical harvesters would reduce yields of 
subsequent ratoons by pulling entire stools from the soil due to weakened root systems caused by 
the flooding. An experiment was conducted to determine the combined effect of water-table 
depth and intermittent flooding on soil organic matter oxidation potential and sugarcane root 
growth. Sugarcane was grown in 1.5 X 2.6 X 0.6 (wide, long, and deep, respectively) m 
polyethylene lysimeters out doors. Lysimeters were filled with a Pahokee muck soil. After 
plants reached an 8-cm height, intermittent flooding treatments were imposed consisting of 7 
days flooding followed by 14 days drained to 16, 33, and 50-cm depths. A continuous 50-cm 
water table was used as a control. Starting July 10, soil samples were taken during the drain 
period on day 0, 3, 7, and 14 and analyzed for oxidation potential. Soil sampling continued over 
5 consecutive cycles. On Jan. 19, 2001 sugarcane was harvested and shortly afterwards, root 
samples were taken. Root samples were extracted by taking four-6.4-cm cores to to 15-, 15 to 
30-, and 30 to 45-cm depths at a distance about 5 cm from the rows of sugarcane. Roots were 
washed and analyzed for dry wt, length, volume, surface area, and diameter. Soil organic matter 



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oxidation potential averaged over 5 drain cycles indicated that soil oxidation started increasing 
immediately after drainage and reached its maximum activity about one week later. Also, there 
appeared to be a residual effect of flooding as the oxidation potential of the flooding treatments 
was less than the continuously drained treatment over the 14-day drain cycle. The 16-cm water 
table had soil oxidation potentials that were less than half those of the other flooding treatments. 
Average root dry wt, length, surface area, and volume from high water table treatments in the 
sampled area were about twice those from continuously drained treatment. It appears that with 
intermittent flooding, roots around the sugarcane stool can compensate for unfavorable root 
environments by developing more roots in the less aerated soil compared to continuously drained 
soil. Combining raised water tables with intermittent flooding should improve both soil 
conservation and sugarcane root growth. 



Effect of Nitrogen Fertilizer Rates on Producer Economic Returns of Variety LCP 85-384 

on a Heavy-Textured Soil in Louisiana 

W. B. Hallmark and G. J. Williams 

Iberia Research Station 
Louisiana State University Agricultural Center 

G. L. Hawkins 

Sugar Research Station 
Louisiana State University Agricultural Center 

M. E. Salassi 

Department of Agricultural Economics and Agribusiness 
Louisiana State University Agricultural Center 



Recommended nitrogen fertilizer rates for "strong" stands of sugarcane {Saccharum spp.) 
on heavy-textured soils in Louisiana are 112 to 135 kg N/ha for plant cane, and 157 to 179 kg 
N/ha for stubble cane. The high sugar yields (20% higher than the next best variety) obtained 
with variety LCP 85-384 raise questions about whether this variety has different nitrogen 
fertilizer requirements than other recommended varieties grown in Louisiana. To answer this 
question, twelve site-years of yield data from nitrogen rate studies with LCP 85-384 on a 
Baldwin silty-clay loam (thermic Vertic Ochraqualf) soil were used to determine economic 
returns (based on $0.42/kg of sugar, $0.66/kg of N, and the producer giving half of his crop to 
the sugar mill and landlord) to producers. The best economic returns for plant cane in five 
studies were at 0, 56, 67, 135, and 157 kg N/ha, respectively, compared to the recommended 
nitrogen application rate of 112 to 135 kg/ha. The highest economic returns for first-stubble 
cane in five studies were 67, 112, 112, 112, and 135 kg N/ha compared to the recommended rate 
of 157 to 179 kg N/ha. Consequently, the recommended N application rate for LCP 85-384 
first-stubble cane appears to be too high and better economic yield responses could be obtained 
if it were fertilized like plant cane. There was only one site-year of data for second- and 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

third-stubble cane. In both cases, highest economic returns were obtained at 202 kg N/ha 
compared to the 135 kg N/ha rate. 



Production Trends of the Major Cane Sugar Producing Countries in the World 

Chen-Jian Hu 

United States Sugar Corp. 
Clewiston, Florida 33440 

Over 130 countries produce sugar about 134 million Mg sugar in 1999 to 2000 crop, of 
which 27 of them produced over one Mg sugar. Six countries, Brazil, India, China, USA, 
Australia, and Thailand generated 61% of the word cane-sugar production (97 million Mg) in 
1999 to 2000. Total cane-sugar production from these six countries plus South Africa, the major 
cane sugar producer in Africa, has significantly increased in recent decades. Approximately 
60% of the increase was due to expanded growing area. 

The highest sugar production per area in the world is and has been in Hawaii with 
average production over 11 Mg sugar ha" 1 . Thailand and Louisiana demonstrated the largest 
increases in total sugar production (244% and 145% Mg sugar) and per area production (145% 
and 87% Mg sugar ha" 1 ) in the last 20 years. Australia has maintained without significant change 
the highest average sucrose content (14 sucrose %cane) in the world since the 1920s. In the last 
12 years sugar production per area (Mg sugar ha" 1 ) increases have been due mostly to 
improvements in cane yield production with little to no change in sucrose content. Perhaps we 
have reached a genetic plateau for sucrose content. 



Potential Effect of Yellow Leaf Syndrome on the Louisiana Sugarcane Industry 

M. P. Grisham, Y. B. Pan, and W. H. White 

USD A, ARS, Southern Regional Research Center 
Sugarcane Research Unit, Houma, LA 

M. A. Godshall 

Sugar Processing Research Institute, Inc., New Orleans, LA 

B. L. Legendre 

Louisiana State University Agricultural Center, Research and Extension 
Plant Sciences Division, Baton Rouge, LA 

J. C. Comstock 

USD A, ARS, Sugarcane Field Station, Canal Point, FL. 

A three-year field study was conducted to determine the effect of sugarcane yellow leaf 
virus (SCYLV) on two cultivars of sugarcane (LCP 82-89 and LHo 83-153). Yield loss (sugar 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

per unit area) was observed in LCP 82-89, with the greatest loss in the second-ratoon crop 
(23%). Quality components, % Brix, % sucrose, % purity, and starch concentration, of the stalks 
did not differ between SCYLV-infected and uninfected; however, in the tops, leaves and the 
immature portion of the stalk, % Brix, % sucrose, % purity, and starch concentration were higher 
in SCYLV-infected plants of both cultivars. Dextran content was inconsistent. Tops of stalks 
are normally removed by the mechanical harvester; however, they may not be removed if the 
cane is lodged and/or during wet weather harvesting. Green leaves and immature tissue 
containing elevated levels of starch delivered to the mill may reduce processing efficiency. 

A collection of 407 parental sugarcane clones grown at Canal Point, Florida and used for 
making crosses for the Louisiana Industry were assayed for infection by SCYLV. As a result of 
natural spread, SCYLV infection was found in approximately 50% of the cultivars, indicating a 
high level of susceptibility to infection within the Louisiana germplasm. 

Although visible symptoms of yellow leaf syndrome (YLS) caused by SCYLV are rarely 
observed in Louisiana, yield loss was observed in SCYLV-infected LCP 82-89 in the absence of 
symptoms and the virus in both cultivars affected quality components in leaves. With the recent 
discovery of Melanaphis saccharalis in Louisiana, a demonstrated vector of SCYLV, and the 
demonstration of yield and quality effects on sugarcane even in the absence of symptoms, YLS 
is a potential problem to the Louisiana industry. 



Feeding Effects of Yellow Sugarcane Aphid on Sugarcane 

Gregg Nuessly and Matthew Hentz 

Everglades Research and Education Center 
University of Florida, Belle Glade, Florida 

Feeding by yellow sugarcane aphid, Sipha flava (Forbes), can cause reddening, 
premature yellowing and death of sugarcane leaves. Prolonged feeding by large populations of 
this aphid can lead to plant death. We report here the results of experiments using a susceptible 
sugarcane cultivar (CP80-1827) to quantify the growth and yield effects of early season S. flava 
feeding. Two-month old plants grown from single-eye setts in 5-gallon buckets were first 
subjected to yellow sugarcane aphid feeding for 8 to 10 weeks. Plant damage was rated on the 
number of leaves (0, 1, 2, 3, and 4) below the TVD on the primary stalk with <50% S. flava 
damage symptoms. These ratings were used to group plants for comparison of growth and yield 
effects against plants grown without aphid exposure (controls). Aphids were then removed and 
the plants transplanted into the field where they were maintained aphid-free for 7 months until 
harvest. S. flava feeding resulted in the production of longer, faster growing leaves and 
internodes, but also thinner, lighter stalks compared to the controls. Each leaf and internode that 
was produced after aphids were removed from the plants expanded slightly less than the 
previous one and gradually approached the length of these structures on control plants, but node 
diameters remained thinner on previously infested stalks. Internode volumes were reduced an 
average of 21% on plants in the highest damage category. Aphid-damaged stalks with thin 
internodes at their bases were more likely to lodge from wind and rat damage than controls. 



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Apparent sucrose was lower in juice from plants previously infested by S. flava than from those 
not exposed to the aphids. When combined with the reductions in internode volume and weight, 
even light S. flava damage (i.e., two out of six leaves below TVD with >50% damage) resulted 
in a 6% reduction in sugar yield. Heavy damage (i.e., six out of six leaves below TVD with 
>50% damage) to sugarcane plants from yellow sugarcane aphid feeding early in the season 
reduced sugar yield by 19%. 

Relative Abundance and Diversity of Aphid Species Collected in Traps Adjacent to 

Sugarcane Fields in Florida 



R. N. Raid, G. S. Nuessly, and R. H. Cherry 

University of Florida, IF AS 

Everglades Research and Education Center 

P. O. Box 8003 

Belle Glade, FL 33430 

Even with the rapid expansion of the state's sugarcane industry during the 1960s, 
sugarcane mosaic, caused by the sugarcane mosaic virus potyvirus (SCMV), remained a disease 
of minor importance in Florida for nearly four decades. Although detected in sugarcane and 
weeds, disease incidence rarely exceeded several percent. Since the late 1990s, however, 
observers have noted a marked increase in SCMV incidence, particularly in the variety CP72- 
2086. A mainstay of the Florida industry, presence of SCMV in this variety could have serious 
repercussions. For even though CP72-2086 has demonstrated yield tolerance, it could serve as a 
significant pathogen reservoir, facilitating the spread of SCMV to other susceptible, but less 
tolerant varieties. In nature, SCMV is transmitted mechanically (i.e. planting of infected seed 
pieces) and by aphid species in a semi-persistent manner. With a paucity of baseline information 
on aphid diversity and populations in the Everglades Agricultural Area, investigations were 
conducted using standard yellow sticky traps to monitor aphid activity adjacent to sugarcane 
fields. Five traps were positioned for a 14-day period at monthly intervals along transects 
paralleling sugarcane fields located in areas representative of the western, central, and eastern 
cane-growing areas of the EAA. Cumulative numbers of aphids trapped peaked in March and 
then again in November. A total of 23 identifiable species were collected, representing 12 
genera. Two of these species, Rhopalosiphum maidis and Schizaphis graminium, have been 
demonstrated to be capable of transmitting SCMV in nature. Two aphid species that commonly 
colonize sugarcane, Sipha flava and Melanaphis sacchari, were trapped relatively infrequently. 
Possible associations of the recent surge in SCMV in Florida and aphid populations will be 
discussed. 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Fifteen Years of Recurrent Selection for Sugarcane Borer Resistance 

W. H. White and T. L. Tew 

USDA-ARS, SRRC, Sugarcane Research Unit, Houma, LA; 

J. D. Miller 

USDA, ARS, Sugarcane Field Station, Canal Point, FL 

The sugarcane borer, Diatraea saccharalis (F.), is an important insect pest of sugarcane 
in the Americas and the key insect pest of sugarcane in Louisiana. Long managed in Louisiana 
using an IPM program primarily relying on insecticides, there is increasing economic and 
environmental pressures to reduce the management program's dependency on insecticides. Plant 
resistance is an attractive alternative to insecticides. 

In 1986 we began a satellite recurrent selection program to increase levels of borer 
resistance among parental lines used in the Louisiana Commercial Breeding Program. Following 
the initial crosses in 1985 among resistant parents identified from the USDA's 1983 Series, 
approximately 75,000 seedlings have been evaluated. Fifty-one selections were given the in- 
house designation RSB (recurrent selection borer). Of these 51 selections, 33 were assigned 
permanent numbers (US) and 18 were identified as having commercial potential. A total of 17 
selections were registered with the Crop Science Society of America as germplasm clones. 
Biparental crosses have been made among these resistant clones and selections are being made 
to advance a new generation of recurrent selection. 



Mexican Rice Borer on Sugarcane and Rice: 
Significance to Louisiana and Texas Industries 



M. O. Way 

Texas A&M Research and Extension Center 
Beaumont, TX 

T. E. Reagan and F. R. Posey 

Department of Entomology 

LSU AgCenter 

Baton Rouge, LA 

The sugarcane borer Diatraea saccharalis (F.) is the most common stem borer in the 
upper Texas rice belt, but the Mexican rice borer (MRB) Eoreuma loftini is becoming an 
increasing problem, particularly in the southern region of the Texas Rice Belt - Calhoun, 
Jackson, Victoria, and Matagorda Counties. The MRB was introduced prior to 1980 from 
Mexico into the Lower Rio Grande Valley where it immediately became a serious pest of 
sugarcane. In 1987, the MRB was first detected in the Texas Rice Belt in Jackson and Victoria 
Counties. In 2000, pheromone traps were set out in most Texas Rice Belt counties around 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

sugarcane in East Texas, and in Southwestern Louisiana sugarcane producing parishes to 
determine the spread of this insect since 1987. County Extension Agents , farmers, and Texas 
and Louisiana Agricultural Experiment Station scientists helped monitor the traps. In addition, 
personnel from both state departments of agriculture participated. The traps used were baited 
with synthetically produced MRB pheromone. Results of the 2000 trapping program showed the 
MRB had moved north into five new Texas Rice Belt counties - Wharton, Brazoria, Colorado, 
Waller, and Fort Bend. No MRB were collected in counties east of Harris where Houston is 
located. 

About 1000 acres of sugarcane are now grown in Texas east of Houston near Beaumont, 
which is the eastern region of the Texas Rice Belt. Based on pheromone trapping, sugarcane 
grown in this area is free of MRB. Sugarcane farmers in Southeast Texas and Southwest 
Louisiana are concerned about the possible introduction of the MRB, which could become a 
serious pest of sugarcane in these regions. In the Lower Rio Grande Valley, the MRB is the 
number 1 pest of sugarcane; in fact, some fields are not harvested due to heavy damage. 
Consequently, the MRB has the potential to become a threat to rice and sugarcane in Southeast 
Texas and Southwest Louisiana. 

Data from the Lower Rio Grande Valley suggest that drought stresses sugarcane is far 
more susceptible to MRB damage than healthy sugarcane. Thus, the pest potential in irrigated 
sugarcane is less compared to rain fed sugarcane, which represents over 95% of sugarcane in 
Louisiana. 

Data from 1999 and 2000 indicate MRB is the predominant borer attacking rice in 
Jackson County (and possibly Calhoun and Matagorda Counties). MRB damage is similar to 
that of the sugarcane borer. The larvae cause deadhearts and whiteheads. Replicated small plot 
studies in Jackson County in 1999 showed that a combination of MRB and a small percentage of 
sugarcane borers reduced rice yields 3000 lb/acre. These are exceedingly high yield losses 
which may not be representative of the entire area but do show the potential for damage. 
Research by Texas A&M and LSU AgCenter scientists is currently being conducted to 
determine rice and sugarcane varietal susceptibility to MRB, gain additional biological 
knowledge of the MRB in order to better time control tactics, and evaluate selected insecticides 
using an integrated pest management approach. This research is partially funded by grants from 
the USDA CSREES Critical Issues, Rice Research Foundation, and the American Sugarcane 
League. 



Economically Optimal Crop Cycle Length for Major Sugarcane Varieties in Louisiana 

Michael £. Salassi and Janis Breaux 

Department of Agricultural Economics and Agribusiness 
Louisiana Agricultural Experiment Station 
LSU Agricultural Center, Baton Rouge, LA 

The widespread adoption of the high-yielding variety LCP85-384 has resulted in two 
significant changes in the production sector of the Louisiana sugarcane industry. Plant 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

characteristics of this variety make it very suitable for combine harvesting and helped to promote 
the conversion from whole stalk harvesting to combine harvesting in the state. Secondly, the 
variety is also an excellent Stubbling variety, resulting in the expansion of standard sugarcane 
crop cycles beyond harvest of second stubble. Outfield trials yield data over the 1996-2000 
period for major sugarcane varieties produced in Louisiana was used to determine the optimal 
crop cycle length, which would maximize the net present value of producer returns. Cane yield 
and sugar per ton data for plant cane through third stubble was used to estimate the annualized 
net return of crop cycles through harvest of second and third stubble and to determine the 
breakeven level of fourth stubble yields which would justify production and harvest. Analysis of 
yield and net return data for the varieties CP 70-321, LCP 85-384, and HoCP 85-845 indicated 
that minimum yield levels necessary to keep older stubble in production for harvest depend 
directly upon the yields of the prior crop cycle phases and differ significantly across varieties. 



Optimum Maturity of CP Sugarcane Clones for Harvest Scheduling in Florida 

R. A. Gilbert 

University of Florida 

Everglades Research and Education Center 

Belle Glade, FL 33430 

J. M. Shine, Jr. 

Sugar Cane Growers Cooperative of Florida 
Belle Glade, FL 33430 

J. D. Miller 

USDA-ARS Sugarcane Field Station 
Canal Point, Florida 33438 

Variety maturity tests were conducted on 16 Canal Point (CP) clones at 5 locations over 
3 years in the Everglades Agricultural Area in Florida. Cane sugar quality was measured at 
biweekly intervals during the October to March harvest season in each year. A quadratic 
response function of lbs. sucrose per gross ton of cane (SPT) vs. sampling date was calculated 
for each clone using the entire 3 -year data set, and date and magnitude of maximum SPT 
calculated. CP89-2143 and CP72-2086 had the highest predicted SPT at 305 and 285 on Feb 9 
and Feb 13, respectively. Model fit varied greatly between clones, with R 2 values ranging from 
0.23 - 0.72. In general, clones with higher R 2 values tended to have maximum SPT after 
February 1 . The SPT data was then divided into "early", "middle", and "late" maturity classes 
and the CP clones ranked based on average SPT within a given class. Results of this analysis 
will be discussed in terms of a harvest scheduling aid for Florida growers. 






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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Protox Inhibitor Herbicide Effects on Pythium and Root Rot of Sugarcane 

J. H. Daugrois 

Cirad-ca, Sugarcane Program 
Station de Roujol, Guadeloupe, 97170 Petit Bourg, FWI 

J. W. Hoy and J. L. Griffin 

Department of Plant Pathology and Crop Physiology 
LSU AgCenter, Baton Rouge, LA 70803 

A complex of root pathogens contributes to yield decline of sugarcane. Pythium root rot, 
caused by P. arrhenomanes, is one component of the disease complex. Root rot control would 
increase yield and could allow additional ratoons to be obtained. Herbicides can have non-target 
effects, such as enhancing or reducing root disease severity. Protoporphyrinogen oxidase 
(protox) inhibitor herbicides may reduce fungal disease severity in other crops by inducing host 
resistance. In addition, visual growth increases in sugarcane early growth following application 
of one protox inhibitor herbicide have been observed. Therefore, lab and greenhouse 
experiments were conducted to determine protox inhibitor herbicide effects on Pythium, root rot 
severity, and sugarcane growth. 

Three protox inhibitor herbicides, Milestone (azafeniden), Spartan (sulfentrazone), and 
Valor (flumioxazin) were evaluated for their effects on in vitro mycelial growth rate of P. 
arrhenomanes, P. ultimum, and P. aphanidermatum and Pythium root rot and growth of 
sugarcane in two greenhouse experiments. Effects on sugarcane growth and root rot were 
evaluated after herbicide leaf or soil application at the recommended rate and 1/10 and 1/20 the 
recommended rate. Three types of soil were used, field soil (FS), sterilized field soil (SFS), and 
sterilized field soil infested with P. arrhenomanes (SFS+P). 

All three herbicides strongly reduced Pythium mycelial growth in vitro. No growth of P. 
arrhenomanes occurred when rate one or above was applied in the growth medium. Mycelial 
growth inhibition still occurred at a 200-fold dilution of the recommended rate. Milestone had 
the strongest effect followed by Spartan and Valor. In the greenhouse, all three herbicides 
reduced P. arrhenomanes root colonization in some cases, but results were erratic between 
experiments. Milestone and Valor were phytotoxic in sterile and nonsterile soils, and with a 
short duration experiment, the damage may have made it difficult to detect effects on root rot 
severity and plant growth. No treatment clearly reduced visual root rot symptoms. Only 1/10 rate 
Spartan applied to leaves significantly reduced P. arrhenomanes colonization in SFS+P and 
increased plant growth. In field soil, more treatments reduced Pythium root colonization, but 
only leaf-applied Spartan at rate one and 1/10 rate Valor increased some component of 
sugarcane growth. 

No consistent effects on disease severity and plant growth were shown. However, the 
greenhouse experimental system may not have been sufficient to clearly demonstrate the effects 
of the protox inhibitor herbicides on sugarcane root rot. Although variable, the results suggest 
these herbicides may be capable of reducing P. arrhenomanes infection and increasing plant 
growth through reduced root rot severity. The slight increases in plant growth following leaf 
application of herbicide suggest an indirect effect through induced resistance. 



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Irrigation of Sugarcane on Clay in a High-Rainfall Environment 

Howard P. Viator 

Iberia Research Station 
LSU AgCenter 

Variable yield responses to irrigation of sugarcane, Saccharum spp., in Louisiana's 
humid climate have made it difficult to evaluate its economic soundness. Nevertheless, the 
occurrence of several droughts during the past decade in southern Louisiana has intensified the 
interest in supplemental irrigation. During the severe drought of 2000, a study to evaluate the 
response of LCP 85-384 plant cane to irrigation was conducted on an Alligator clay soil (thermic 
Vertic Haplaquept), a soil textural class that tends to restrict root development under drought 
conditions. Irrigation was scheduled when stalks elongated 5 cm or less per week. 
Supplemental water was supplied in furrows on May 5, May 25, July 21 and August 28 for a 
cumulative total of 1130 m^ . The experimental site received a total of only 50.5 cm of rain 
from May through October, a rainfall deficit of 38.4 cm when compared to a 25-yr average for 
the same period. Height difference at harvest between the irrigated and non-irrigated plots was 
50 cm. Yields mirrored the plant height disparity, with irrigated plots producing 44% higher 
cane (P = .06) and sugar (P = .08) yields than the control plots. The magnitude of the yield 
responses to irrigation in this experiment, 22.6 Mg ha-1 of cane and 2.41 Mg ha-1 of sugar, was 
comparable to that observed elsewhere under similar dry conditions. 



Effect of Tissue Culture Method on Sugarcane Yield Compnents 

J. W. Hoy 

Department of Plant Pathology and Crop Physiology 
LSU AgCenter, Baton Rouge, LA 70803 

K. P. Bischoff and K. A. Gravois 

Sugar Research Station 
LSU AgCenter, St. Gabriel, LA 70776 

S. B. Milligan 

United States Sugar Corporation 
Clewiston, FL 33440 

Vegetative propagation is conducive to the spread of systemic sugarcane diseases, such 
as ratoon stunting disease (RSD). This important disease is now controlled in Louisiana largely 
by planting commercial seed-cane initially produced through tissue culture. Kleentek® 
seed-cane has been available to farmers since the late 1980s. In the early years, farmers 
sometimes noted that tissue culture derived plants had smaller stalk diameter and weight and a 
higher stalk population. The tissue culture method used at that time was leaf roll callus culture. 
Since then, the method has been changed to direct regeneration from the apical meristem to 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

attempt to reduce or eliminate differences between tissue culture derived plants and the original 
varieties. 

To determine whether tissue culture method affects yield or its components, three 
varieties, CP 70-321, LCP 85-384, and HoCP 85-845, were compared in three successive crops, 
plant cane through second ratoon, at three locations. Experiments were planted with stalks from 
three sources: Kleentek plants derived from callus (undifferentiated cells) produced from the leaf 
roll above the apical meristem, Kleentek plants directly regenerated from an apical meristem, 
and original plants from conventional bud propagation. Stalks of plants derived from both tissue 
culture methods were typical of Kleentek seed-cane farmers would purchase for planting that 
had been rogued for phenotypic variants (off-types) and increased by bud propagation. Yield 
components compared included stalk diameter, length, weight, sucrose content, and population; 
cane tonnage; and sugar yield. Plants were visually inspected for off-types in May, August, and 
at harvest. 

Differences in yield components between the two tissue culture methods and bud- 
propagated cane only occurred in CP 70-321. Stalk diameter and stalk weight were lower and 
stalk population was higher for plants derived from leaf roll callus compared to bud propagated 
cane. However, all yield components were similar for plants derived from apical meristem and 
bud propagation. Individual plant off-types were not observed in cane produced by either tissue 
culture method. In summary, variety and tissue culture method affected persistent, uniform 
variation in plant growth habit resulting from tissue culture that changed some yield 
components. However, apical meristem culture was suitable for production of seed-cane, as 
sugarcane derived by meristem culture of all three varieties did not differ significantly from the 
original germplasm for any measured trait. 



Genes Expressed During Regeneration in Tissue Culture 

Robin Rowe 

University of New Orleans 

Candace Timple and Sarah Lingle 

USDA-ARS-SRRC 

Regeneration from tissue culture by way of somatic embryogencis is common in many 
varieties of sugarcane, but many economically important varieties of sugarcane are recalcitrant. 
Better understanding of the genetic control of embryogenesis could lead to the ability to transfer 
this trait to important varieties lacking it. This could assist in the rapid progation of these 
varieties and in the construction of beneficial transgenic varieties. We used differential display 
techniques to compare genes expressed in mRNA samples from non-cmbryogenic, 
proembryogenic, and embryogenic callus from variety CP 72-1210 and from non-embryogenic 
callus from the recalcitrant variety TCP 87-3388. Several novel sequences were identified. One 
codes for a hypothetical protein containing several phosphorylation sites. Another codes for a 
hypothetical protein with a glycosylation site and a camp controlled phosphorylation site. The 



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third codes for a hypothetical protein with a 37% homology to extension in canola. The last 
codes for a hypothetical protein that has a 93% homology to a putative glucose-6- 
phosphate/phosphate translocator in rice. Whether these sequences are unique to a specific 
tissue type is still under investigation. 



A Technique to Breed for Ratoon Stunting Disease in Sugarcane 

J. D. Miller, J. C. Comstock, P.Y. P. Tai, and B. Glaz 

USDA-ARS Sugarcane Research Station 
Canal Point, Florida 

Ratoon stunting disease (RSD) caused by Clavibacter xyli subsp. xyli is one of the most 
important sugarcane (interspecific hybrids ofSaccharum spp.) diseases in Florida. The 
objective of this study was to evaluate the effectiveness of stubble inoculation and determine if it 
could be used in a program to breed for RSD resistance. Field grown seedling sugarcane plants 
were inoculated at maturity by cutting with knives dipped in juice infected with ratoon stunting 
disease bacteria (RSD). The regrowth from these stools was sampled at the base of the mature 
stalks and RSD susceptibility was based on the number of colonized vascular bundles 
determined using the tissue blot immunoassay. After selection based on vegetative 
characteristics in Seedlings, the average RSD rating of 12 crosses with 658 selections was 1.52. 
When resampled as mature plants in Stage I, the average rating was 4. 1 5. The plants were 
reinoculated and replanted into a Stage I sized plot. There were 67 clones selected for 
advancement to Stage n. They had an average RSD rating of 1.75. One major advantage of this 
system is that it requires no special planting in which to evaluate RSD resistance. The major 
disadvantage of this system from our standpoint in Florida is that it requires that seedling 
selection be done in the ratoon crop and that all clones in the breeding program would 
potentially be infected with RSD. In all probability very high yielding susceptible clones would 
be dropped with this selection scheme. Growers in Florida now manage RSD with a 
combination of genetic resistance and clean seed cane. Therefore, our industry is not willing to 
lose those potentially high yielding clones that are susceptible but could be profitable when 
grown without RSD. 



Progress in the Development of Transgenic Disease-Resistant Sugarcane 

Z. Ying and M. J. Davis 

University of Florida, Tropical Research and Education Center 
Homestead, Florida 

Efforts are underway to develop sugarcane with transgenic resistance to the sugarcane 
yellow leaf luteo virus (SCYLV), leaf scald disease (LSD), and ratoon stunting disease (RSD). 
Genetic constructs containing the SCYLV coat protein in the sense (pFM395) and antisense 
(pFM396) orientations were obtain from T. E. Mirkov (Texas A&M, Weslaco). A genetic 
construct (pMBP39-22) containing a modified cecropin gene (MB39) was obtained from Lowell 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Owens (USDA, Beltsville, MD). In vitro growth inhibition assays indicated that MB39 should 
be highly active against the RSD and LSD pathogens, Clavibacter xyli subsp. xyli and 
Xanthomonas albilineans, respectively. A number of other DNA constructs were made 
including those with the cecropin gene under control of the maize ubiquitan promoter (pZY-C), 
and the antisense SCYLV gene fused with the cecropin gene both under control of the ubiquitan 
promoter (pZY-CSA). Sugarcane callus cultures were co-bombarded with the individual 
constructs and another construct containing the NPT II gene as a selectable marker. Genetically 
transformed plants were regenerated from these materials and are being tested further. 

Potential Impact of DNA Marker Technology on Sugarcane Breeding 

Yong-Bao Pan 

USDA-ARS, Southern Regional Research Center, Sugarcane Research Unit, 
5883 USDA Road, Houma, LA 70360, U.S.A. 

At the turn of the new millennium, breeders have begun to realize how DNA marker 
technology may potentially impact traditional sugarcane breeding programs. Sugarcane is a 
tropical grass with both male and female organs within each tiny flower. Self-pollination may 
occur even after a male-sterility treatment such as the immersion of tassels in hot water or 
alcohol. The use of DNA marker technology may allow breeders to eliminate progeny from 
unwanted selfs early in the basic and commercial programs. At least five classes of DNA 
markers are available to use, each having its strong and weak points. These are restriction 
fragment length polymorphism (RFLP), random amplified polymorphic DNA (RAPD), 
polymerase chain reaction (PCR), simple sequence repeat (SSR) or microsatellites, and 
amplified fragment length polymorphism (AFLP). Unlike the morphological traits, DNA 
fingerprints constructed with these classes of markers are quite reliable and not influenced by the 
environment. A few PCR {Eri3IEri4 and GigllPII), RAPD (OPA 11-366), and SSR (SMC334BS, 
SMC336BS and MCSA068G08) markers, that prove to be species-specific, have been developed 
to assist in the basic selection program at the Sugarcane Research Unit at Houma, Louisiana. 
Multi-disciplinary studies are underway to identify and clone RAPD or AFLP markers that are 
tightly linked to genes contributing to important agronomic traits. Multi-institutional 
collaborations are also being sought to construct microsatellite linkage maps from several 
genetic populations (Fl, F2, BC1) of sugarcane. 



In Vivo Viability Assay of Sugarcane Pollen Stored at Ultra Low Temperature Following 

Preservation Treatments 

P. Y. P. Tai and J. D. Miller 

USDA-ARS Sugarcane Field Station 
Canal Point, Florida 

Storage of sugarcane pollen is desirable for enhancing germplasm because of the 
different flowering time. The viability of Saccharum spontaneum pollen can be significantly 
prolonged under low temperature after being properly air dried to reduce its moisture content. 

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The information on pollen viability of commercial cultivars (CP 70-1133, CP 98-1301, and CP 
98-1654) were used to examine their viability after being stored at low temperature. Pollen 
samples were collected in the early morning after anthesis and divided into two sets: the first 
was dried in a cool dehumidified room for three hours and the second set was treated with 
cryoprotectants. Both sets of pollen were stored immediately at -80°C for 1 to 4 months. 
Cryoprotectants included 0.25 - 0.5 M solutions in various combinations of dimenthyl sulfoxide, 
glycerol, sorbitol, and sucrose. An in vivo assay was used to measure the pollen viability. 
Pollen was applied onto the tassels of green canes, CP 65-357 and Green German (S. 
officinarum), in the morning during the flowering season. Fuzz was harvested about 30 days 
after pollination for germination test. Seedlings were transplanted to field. Seedlings from 
crosses derived from stored S. officinarum pollen were classified based on the gross plant 
morphology at 4-month-old while seedlings derived from crosses with stored pollen of 
commercial cultivars were classified based on stalk colors. Stalk color was determined by one 
internode from each of 12-month-old seedlings that was cut and dipped vertically in 5% 
sulfurous acid solution for 3-4 days to eliminate chlorophyll pigment. Loss of pollen viability 
(%) due to preservation treatments was estimated by [ 1 - (seed set from stored pollen)/(seed set 
from fresh pollen)] 100. Results showed that pollen of neither S. spontaneum nor commercial 
cultivars produced viable seedlings when they were stored at -80°C after being treated with 
cryoprotectants. After being exposed to air drying, pollen of both S. spontaneum and 
commercial cultivars produced viable seedlings ranging from poor to good seed set when the 
stored pollen was used to cross with CP 65-357 or Green German. Average losses of pollen 
viability were 50% (1997/98) and 88% (1999/00) for CP 98-1654. In addition to the use of the 
pollen storage for germplasm enhancement, this study suggests that stored pollen with genetic 
marker may be used to help identify hybrids for genetic and breeding investigations. 






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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

MANUFACTURING ABSTRACTS 

The Freeze of 2001-A "New Book is Written" 

John A. Fan jul 

Atlantic Sugar Associations, Inc. 
Belle Glade, Florida 

Atlantic Sugar Associations, Inc. developed an organizational plan, which involved 
pooling its R&D/Harvesting, Operations/Mill, and Cane Bank, to handle the freeze in 2001. 
Atlantic Sugar Associations, Inc. had successful and record-breaking results across the board. 



The Breakage in Sugarcane Mill Rolls 

Jorge Okhuysen 

Mexico 

The causes of failure involving the design, materials selection, methods of 
manufacturing, and the influence of operating conditions in sugarcane mill rolls will be 
discussed. 



Material Balance and Equipment Requirements of a Typical Sugar Mill 

Eduardo Samour, P.E. and William Easdale 

United States Sugar Corporation 
Clewiston, FL 

Traditionally, to reduce production costs or for other reasons, most sugar mills have 
increased their grinding rate over the years, after they were designed and built for certain 
capacity, and conditions. When an expansion project is conceived in a sugar mill, the focus 
generally is, on cane grinding capacity and steam production. Even though these are extremely 
important factors, a proper evaluation of the rest of the equipment in the factory is often 
neglected. This, bring about unnecessary bottlenecks that will defeat the purpose of the 
expansion, or even worse, a reduction of efficiency. With a properly conducted survey of 
equipment capacities, an engineer can determine, with the new operating conditions, the proper 
capacity required in each station of the process. 

This paper describes, calculations of material and steam balance performed for a typical 
sugar mill. It is based on a grinding rate of 1000 tons of cane per day, using the double magma 
system, and quadruple effect evaporation, with first effect vapor bleeding for secondary heaters 
and clarified juice heaters and second effect vapor bleeding for primary heaters and vacuum 
pans. 



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The results are presented in various charts. These were developed, to illustrate different 
volumes of materials that can be expected in the boiling house, under different cane quality 
conditions. Other charts are also presented such as: heating surface required for Juice heaters on 
the various stages, evaporation rates necessary to satisfy the demands of vacuum pans, and 
heaters. These figures are useful for sizing the proper equipment required under different 
conditions and grinding rate. 

Properly planning an expansion project, after evaluating all the areas of the mill, will 
help mill managers spend their investment dollars in the areas were equipment is most needed. 
A properly balanced factory, provides a smooth operation that enable the mill engineers to focus 
their attention on increasing efficiency, rather than coping with the added material they have to 
process. 



Reducing Equipment Cost/Best Equipment Management Practices 

Neal Hahn 

Nortrax Equipment Company - South 
Baton Rouge, Louisiana 

The owning and operating cost of mobile equipment can have an adverse effect on a 
mill's profitability. Cost control is important. The core business of the mill is grinding cane, 
rather than mobile equipment management. Many managers do not take the time to consider this 
key area of operation. The productivity of equipment is directly proportional to the effectiveness 
of an equipment management strategy. Equipment that stays idle during productive times is a 
substantial cost to the mill. Utilization tracking can be used to determine if added equipment is 
required. Downtime can be an indicator both of equipment and maintenance problems. A good 
program of maintenance for high-tech equipment must include oil sampling, repair option 
management, preventative maintenance, and life cycle planning. A good record keeping system 
should also include an effort to make historical comparisons of cost per hour. The equipment 
division of each mill should also have a Standard Operating Procedures guide, which would 
address the key areas of equipment operation and maintenance. This paper will provide ideas on 
better equipment management and review specific examples key to lowering the operating cost 
of equipment. 



What You Should Learn from Your Chemical Supplier 

Stephen J. Clarke 

Florida Crystals Corporation 

This paper surveys the issues of selection, use and fate of chemicals used as processing 
aids in sugar production and in equipment cleaning. The chemical sales business is extremely 
competitive and it is essential that the sugar technologist (chemical user) be aware of the 
benefits, costs, and possible unforeseen consequences of each chemical used. The chemical 
supplier who should be familiar with the scientific basis for the application must provide this 
information - there is no magic in this business. Chemical use should be minimal but is 

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unavoidable, and factory personnel must have the information required to avoid unnecessary use. 
Examples of cases where problems and new consumer issues have arisen will be presented, 
along with some suggestions of new chemical applications. 



The Effect of Two Louisiana Soils on Cane Juice Quality 

Mary An Godshall 

Sugar Processing Research Institute 
New Orleans, LA. 

Scott S. Spear 

University of Alabama 

Center for Green Manufacturing 

Tuscaloosa, AL 

Richard M Johnson 

Southern Regional Research Center, ARS, USDA 
New Orleans, LA 

As part of a large-scale investigation on the effect of various field practices on the quality 
of cane juice in Louisiana, it was noted that when soil was added to the cane juice to assess the 
effect of soil on cane juice quality, the juice color lightened. In a study during the 1998/99 crop 
in Louisiana, with addition of 5% and 10% soil, it was noted that polysaccharide was also 
removed, the first time this had been reported. These observations run contrary to expectations 
that soil would degrade the quality of cane juice. Two soils from the Louisiana cane growing 
area, Sharkey clay and Norwood silty clay loam from Bunkie, were tested on raw juice from 
green cane, topped, with side leaves, at a 10% add-on to juice. The juice was treated for 30 
minutes in a shaker either at room temperature (25 °C) or heated (80°C). Changes in pH, color, 
and total polysaccharide, ash and filtration rate were noted. Both soils caused significant 
decreases in color and total polysaccharide and increased the filtration rate. Ash and pH were 
not significantly changed. 



Mill House Operation: Composition of Juice from Individual Mills 

Khalid Iqbal, Mary An Godshall, and Linda Andrews 

Sugar Processing Research Institute 
New Orleans, LA. 

Although a lot of work has been done to study and improve sucrose extraction by 
individual mills in the factory, little information is available about the nature and composition of 
the juice exiting each mill. The type and concentration of the impurities entering into the 
process with the extra sucrose may affect processing and the quality of sugar, a subject that has 
not been addressed to the fullest extent. From a processing point of view, it is useful to have 
detailed knowledge of every sugar-bearing stream within a sugar factory. Samples of individual 
mill juices were collected from mills at a local factory during the 2000 grinding season. Juice 

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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

samples were analyzed for purity, invert, color, total polysaccharides, conductivity ash, cations, 
anions, and nitrogen content. The level of extraction of non-sucrose components generally 
increased across the mills, while the sucrose content decreased. Purity drop was in the range of 
3 to 10 degrees while color, total polysaccharides and nitrogen content increased 2 to 4 times 
from mill #1 to #6. Among cations, sodium and potassium increased, phosphate plateaued at 
mill #3 or #4, and chloride did not change very much. Potential application of this information 
will be discussed. 



A New Polarimetric Method for the Analysis of Dextran and Sucrose 

Victoria Singleton 

Optical Activity Ltd. 
Cambridgeshire, England. 

A new method for dextran quantification has been developed and field-trialled in 
Jamaica, in association with the Sugar Industry Research Institute. The method uses a near 
infrared (NIR) polarimeter and a specific dextranase. The dextranase selectively breaks-down 
the dextran into sugars of lesser specific rotations without affecting any other substance present 
in the juice. The initial dextran concentration is derived from the calibration curve of the change 
in observed optical rotation (OR) due to enzymatic hydrolysis and outputted automatically by the 
polarimeter. Readings are not affected by the molecular weight of the dextrans, the entire 
procedure takes less than 10 minutes to perform and it is semi-automated. Use of a NIR 
polarimeter negates the need for lead clarification. The method is suitable for both juice and raw 
sugar samples. 



Comparative Performance of Hot, Cold, and Intermediate Lime Clarification at Cora 

Texas Factory 

Gillian Eggleston and Blaine E. Ogier 

USDA-ARS-Southern Regional Research Center 
1 100 Robert E. Lee Blvd 
New Orleans, LA 70124 

Adrian Monge 

Cora Texas Manufacturing Co. 
Res. 32540 B Texas Rd 
White Castle, LA 70788 

Since 1996, Cora Texas factory in Louisiana has been operating intermediate lime 
clarification and was, therefore, one of the few U.S. factories that did not operate cold lime 
clarification. In an attempt to further improve clarification performance, the factory made the 
decision to convert to hot lime clarification during the 2000-grinding season. This comparative 
investigation of hot versus intermediate and cold lime clarification was undertaken to 
quantitative performance. In cold liming, mixed juice (MJ) was incubated and then limed in a 
lime tank (4min), both at ambient temperature (~105°F). For intermediate liming, 50% of the 

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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

MJ was heated (180-200°F) before incubation, then limed in a lime tank (4min) at ~150°F. Hot 
liming was configured very similar to intermediate liming except that lime was added 
immediately after flash heating (215°F; 30sec). Hourly samples across each of the three 
processes were collected over a six-hour sampling period, on three consecutive days 
respectively, and these were repeated three times across the 2000-grinding season. For most 
clarification parameters investigated, both hot and intermediate liming performed much better 
than cold liming, and hot liming offered some extra advantages over intermediate liming. 
Markedly less sucrose was lost to inversion reactions across both hot (season av. 0.79%) and 
intermediate (0.97%) lime processes than across cold liming (1.48%). Increasing the factory 
target pH of the final evaporator syrup (FES) from -6.0 to 6.3, in sampling period 3, caused a 
marked reduction in sucrose inversion losses in both hot and intermediate liming. Less lime was 
added in hot liming compared to either cold or intermediate liming, with the factory consuming, 
on season average, only 1.01 lbs lime/ton cane compared to 1.28 for the 1 999-grinding season 
when intermediate rather than hot liming was operated. Pre-heating 50% of the MJ in both 
intermediate and hot liming markedly removed color, dextran, and starch. Approximately 2.1% 
(season av.) more turbidity removal (MJ to CJ) occurred in intermediate and hot liming 
compared to cold liming, with better CJ turbidity control. Subsequent FES turbidity values and 
control were better in hot liming. Significantly less color (-2.5%) formed on hot liming because 
of the alkaline degradation of invert compared to -17% color formation in cold and intermediate 
lime clarification. Dextran removal was best across hot liming and, as expected, dextran formed 
in the cold lime tanks. 



Advanced Report on the Use of Lime Saccharate in the Alkalinization of Sugarcane Juices 

Miguel Lama, Jr. and Raul O. Rodriguez 

Atlantic Sugar Associations, Inc. 
Belle Glade, Florida 

A factory scale trail on the use of lime "Saccharate" at Atlantic Sugar Association in 
Florida is described. The methods of application, using existing equipment and facilities, are 
shown, and some modifications proposed. Results obtained are discussed, within possibilities, 
and proposals formulated for a continuance of the study. 



The Re-introduction of Formal Sugar Engineering Courses at LSU 

Peter W Rein 

Audubon Sugar Institute 
LSU Agricultural Center 
Baton Rouge, Louisiana 

The need for adequately trained people in the sugar industry is discussed. In response to 
the need for better-qualified people in the Louisiana sugar mills, it has been decided to introduce 
formal courses in Sugar Process Engineering and Sugar Factory Design, in the Department of 
Biological Engineering. These courses will form part of the curriculum of students studying 
Chemical, Mechanical or Biological Engineering who wish to earn a Minor in Sugar 

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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 



Engineering. In addition, options for Masters students in engineering to take the sugar courses 
exist, aimed at producing graduate students with a comprehensive knowledge of sugar. The 
benefits to the industry, to Audubon Sugar Institute, and the University are highlighted. 



SAT Process for Production of White Sugar from Sugar Mills 

Chung Chi Chou 

Chou Technologies, Inc. 
New Orleans, LA 

Due to the uncertainty in the government's sugar program and the threat of global 
competition, the US domestic sugar industry is under pressure to develop a new strategy for the 
new millennium. One of the potential solution is to produce white sugar directly from sugar 
mills with minimal / nominal capital cost. With this vision in mind, the SAT process was 
developed at Sugar Processing Research Institute under the direction of its former managing 
director, Dr. Chung Chi Chou and is the subject of this paper. 

For the cane sugar industry, sugar is extracted from sugar cane, processed to produce raw 
sugar in a sugar factory and then further purified to refined white sugar in a sugar refinery. 
However, beet sugar does not require a two-stage process to achieve white sugar in a beet sugar 
factory. By studying the basic differences in the nature of colorants and various composition of 
sugar streams from both sugar cane and sugar beet, the SAT process is developed successfully to 
produce white sugar using clarified juice from sugar mills with color ranging from 80 to 150 
ICUMSA. In this paper, the SAT process itself and its benefit to sugar mills will be presented. 



The Biorefinery Concept 

Willem H. Kampen and Henry Njapau 

Audubon Sugar Institute 
LSU Agricultural Center 
Baton Rouge, Louisiana 

In response to the present energy problems, global warming and the lack of a national 
energy policy, US Government agencies as USDA, EPA, DOE and others are presently 
preparing a strategic plan entitled: "Fostering The Biology Revolution... In Biobased Products 
and Biobased Energy". The national goal is to triple the U.S. use of biobased products and 
bioenergy by 2010. The biorefinery concept is based upon (cheap) sugars from which a diverse 
and flexible mix of energy, fuel, chemical and material products from biomass resources is 
produced; sugarcane should play a major role. 

R&D to reduce the cost of the sugar cane crop has to be part of this effort. It already has 
been demonstrated that betaine can improve the sucrose yield in Louisiana. Most of the 
blackstrap molasses produced in Louisiana is leaving the state. With a large biorefinery we can 
produce from molasses and waste sugars (as an example): bioethanol, carbon dioxide, inositol, 
glycerine, itaconic acid and succinic acid. Other value-added or co-products such as lactic acid 

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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

and thetins could be recovered as well. An example of a biorefmery with a modern waste 
treatment system based upon incineration and heat recovery is presented. These biorefineries can 
have much higher Return On Investments then (raw) sugar factories. 



Evaporator Scale-Minimization with Electro-Coagulation and Improved Cleaning with 

Chelates 

Henry Njapau and Willem H. Kampen 

Audubon Sugar Institute 
LSU Agricultural Center 
Baton Rouge, Louisiana 

Electro-coagulation of clarified juice resulted in the removal of essentially all the silicon 
dioxide & silicates plus from 1 to 40% of calcium, magnesium and (inorganic) phosphate. This 
may reduce scaling by up to 50%. Preliminary work on mixed juice indicates that it is likely that 
electro-coagulation can be effective before clarification also. 

The removal of scale is typically accomplished by boiling with an alkaline solution, a 
water wash and an acid solution. A new acid is being tested, which shows promise as a cleaning 
agent. However, in testing several BASF-chelate solutions we have identified two types of 
chelate solutions that show much improved cleaning over the standard method(s) and in a matter 
of two hours of boiling time. These chelates most likely can replace both the alkaline and acid 
boils, will be cost effective and save on downtime. 



Evaporator Performance During Crop 2000-2001 at Cajun Sugar Factory 

Walter Hauck 

Cajun Sugar Cooperative, INC. 
New Iberia, Louisiana 

During the crop 2000-2001 we tried at Cajun Sugar Cooperative a scale inhibitor. We 
could extend our grinding between the clean outs from 50,000 TC to 1 10,000 TC. We also used 
products in the cleaning solutions. To our caustic soda of 25 Be we added 5% of soda ash 
together with an activator and a dispersant. We observed that the juice heaters after the crop 
where cleaner then before we started the crop. In our acid boiling we used 1.5% HC1 together 
with 3% ammonium bifloride % diluted muriatic acid. We also used a new inhibitor, which 
allows us to boil the acid for 1.5 hours. The total cleaning cycle was done in approximately 10 
hours including a calandria test in 3 evaporators. The cleaning solutions we used helped us to 
obtain perfectly cleaned heating surfaces. In the original paper I will include more detailed facts 
and analysis from the scaling we could remove or not. 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Mixed Juice Clarifier Distribution at Clewiston 

Mike Damms and Carlos Bernhardt 

United States Sugar Corporation 
Clewiston Sugar Mill 

For the 2000/2001 crushing season, it was necessary to install a new mixed juice flash 
tank at the Clewiston milling facility. Along with the flash tank installation, a new mixed juice 
distribution system, feeding the clarifiers, was also commissioned. The distribution system is 
fully automatic and has several novel features that enhance the operation. 

This paper discusses the installation and its benefits as well as limitations after one 
season of operation. Overall the project was very successful and will lead the way to a reduction 
in the high retention times currently being experienced in the mixed juice clarifiers. Plans for 
the future are also listed. 



For several years we have been pursuing the development and commercialization of a 
rapid antibody-based kit for the quantitation of dextran in a diverse range of sugar streams. The 
report will detail the development process that finally resulted in the a rapid test for dextran. 



Comparing the Effects of Sulphur Dioxide on Model Sucrose and Cane Juice Systems 

L.S. Andrews and M.A. Godshall 

Sugar Processing Research Institute, Inc. 

1 100 Robert E. Lee Blvd 

New Orleans, LA 

Sulphur dioxide (SO2) has been used for centuries to minimize color in food processing 
and fruit and vegetable storage. In the sugar industry, sugar beet processors to reduce and 
prevent color formation in white refined sugar use it routinely. Sugarcane processors throughout 
the world use SO2 to produce plantation white sugars. This study was undertaken to determine 
the effect of SO2 on pure sucrose solutions in comparison to real factory sugarcane juice 
streams. Sugar systems included 15 brix pure sucrose, clarified juice and mixed juice from a 
Louisiana sugarcane mill. A pH of 8.0 was obtained by adding milk of lime then lowered to 

144 






Goats, Mice, and Dextran, the Road to a Monoclonal Antibody Test Kit 

Don F. Day and D. Sarkar 

Audubon Sugar Institute 
LSU Agricultural Center 
Baton Rouge, Louisiana 

J. Rauh 

Midland Research Laboratories, Inc. 
Lenexa, Kansas 






Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

approximately pH 5.0 with either SO2 or HC1 as the control. Several samples ranging from pH 5 
to 8 were processed at 0-120 min at 85^ C. Analyses included pH, SO2, color, calcium, and 
invert (as a measure of sucrose loss). Results indicated that the model system was much more 
sensitive to small levels of SO2 than real juice samples. The pH levels dropped rapidly and 
invert levels increased with time. There was 1.6 % loss of sucrose in the SO2 trial as compared 
with no sucrose loss with HC1. Clarified juice resisted changes in pH with both SO2 and HC1. 
Sucrose loss at 120 min of processing and a pH of 5.0 was only 0.88 %. There was a maximum 
color reduction of 10-15 % in the SO2 trial, whereas no color reduction or sucrose loss was 
observed in the HC1 trial. The mixed juice was very resistant to pH changes, and a minimum pH 
of 6.0 was achieved with 4800 ppm SO2. No sucrose loss was observed in either trial with mixed 
juice, and color reduction was the same in both the SO2 and HC1 trials. In real juice streams, 
SO2 reduced color by 10-15 % more than clarification alone but also induced some sucrose loss 
(0.88%) after a lengthy time. 



Advances in Technology of Boiler Treatment in Louisiana Sugarcane Mills 

Brent Weber, Brian Cochran, and Brian Kitchen 

ONDEO Nalco 

During the 2000 crop, two new technologies were introduced to improve boiler water 
treatment and control at a number of Louisiana sugar cane mills. This paper discusses these 
technologies, their application and overall improvements documented at these mills. Also 
reviewed are possible opportunities to utilize these technologies to improve overall mill 
operations and efficiencies in the future. 

The basis of these technologies is the adaptation of fluorescing bodies, detected via a 
fluorometer, and read as distinct wavelengths of light. These identifiable wavelengths of light 
are the core of our ability to control chemical feed and perform diagnostic control studies, which 
can dramatically improve the performance and reliability of mill steam generating equipment. 

Technology #1 is the introduction of a new internal treatment program for steam 
generating equipment. It is the first new product for this purpose introduced by the industry in 
over 15 years. It incorporates the fluorescing technology described previously and has been 
successfully utilized by several Louisiana mills during the 2000 grind. 

Technology #2 builds upon our knowledge of fluorescence by identifying the presence of 
sugar in return bodies such as pan and evaporative condensate. This is made possible by the 
detection of fluorescing bodies associated with the sucrose molecule. This technology was 
successfully evaluated during the 2000 grind at mills in both Florida and Louisiana for boiler, 
cooling water and once through waters. 



145 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Heat Transfer Devices 



Nell Swift 

Alfa Laval Inc. 

5400 International Drive 

Richmond, Virginia 

In the past 2 decades, great advances have been made in the use of lower cost and more 
efficient heat transfer devices. In the presentation, we will look at how the sugarcane industry in 
the USA can best take advantage of this technology. We will examine the origins of the plate 
heat exchanger and the latest developments up to the present day where we have plate 
evaporators playing an ever-larger role in sugar processing. We will cover the 4 major areas in 
which plates can be beneficial, namely raw juice heaters, clarified juice heaters, evaporators, and 
molasses coolers. 

Special attention will be paid to the installation and operation of plates with regard to the 
sugarcane process and its particular fouling issues. We will discuss key design points that 
should be taken into account before a plate heater or evaporator is installed and the importance 
of venting non condensable gases and maintaining minimum flows. All of these factors need to 
be taken into account by the plant engineer or designer when he/she is looking to use plate heat 
exchanger technology. 






146 



Ife 



IN MEMORIAM 



147 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

In Memoriam 
ENRIQUE R. ARIAS 

September 13, 1918 - January 1, 2002 



The sugar industry was deeply saddened by the loss of 
Enrique R. Arias on January 1, 2002. 

Mr. Arias was the Executive Vice President of the 
Sugar Cane Growers Cooperative of Florida before his 
retirement in June 1994. 

Born in Havana, Cuba in 1918, his expertise in the 
sugar business goes back to his roots. Following in his father's 
footsteps, Mr. Arias attended the University of Notre Dame 
where he earned a Bachelor of Science degree in 1 940 and later 
returned to Cuba where he studied sugar chemistry and sugar 
engineering at the University of Havana. His first work in the 
sugar industry was with the Arechabala group which owned 
and operated a sugar based industrial complex and two sugar 
mills in the Province of Matanzas, Cuba. 




In 1957, he founded the Industrial Service and Construction Company and led the field in 
the conversion of raw sugar handling from bags to bulk. 

Mr. Arias moved his family to the United States in October 1960. In 1961 he joined Farrel 
Birmingham Company of Ansonia, Connecticut and was moved to Florida to become the Resident 
Manager for the construction of Glades Sugar House owned by the Sugar Cane Growers 
Cooperative of Florida. 

Upon completion of the project he joined the National Sugar Refining Company as Director 
of Project Engineering and successively held the positions of Director of Planning, Vice President 
Planning and Vice President Operations. 

In 1970, Mr. Arias joined the staff of Sugar Cane Growers Cooperative of Florida as Vice 
President Planning and later became Executive Vice President. He managed the feasibility studies, 
engineering and construction functions to increase the capacity of Glades Sugar House in several 
steps from 10,000 tons per day to 13,000, 18,000 and 21,000 tons per day. 

At the Port of Palm Beach, Mr. Arias directed the design, construction and operation of the 
bulk sugar shipment facilities of the Florida Sugar Marketing and Terminal Association and the 
expansion of the molasses shipping facilities of the Florida Molasses Exchange. 

He was active in many professional and sugar-related organizations including chairing the 
Florida Sugar Cane League's Environmental Quality Technical Sub-Committee and the technical 
committee of the Florida Sugar Marketing & Terminal Association. He was past-president of the 



148 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Cuban Association of Sugar Technologists and of the Florida Division of the American Society of 
Sugar Cane Technologists and past chairman of the Finance Committee of the Sugar Industry 
Technologists (SIT) and of the Industrial Development Research Council, Inc. He was a member 
of the Board of Directors and sat on the Executive and Nominating Committees for the Sugar 
Association Inc. and was a member of the Cuban Association of Agronomical and Sugar Engineers, 
the International Society of Sugar Cane Technologists, and the U.S. National Committee of the 
International Commission for the Uniform Methods of Sugar Analysis. He was also the past- 
president of Sugar Processing Research Institute Inc. (SPRI). 

Mr. Arias received the Sugar Industry Technologists' Crystal Award for achievements in 
sugar technology in 1991. He was awarded an honorary lifetime membership of the American 
Society of Sugar Cane Technologists in 1988. 

The members of the American Society of Sugar Cane Technologists will long remember 
Mr. Arias with admiration for his contributions to the sugar industry. 



149 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

In Memoriam 

S.J.P. CHILTON 

February 3, 1909- April 2, 2001 

Dr. St. John Poindexter Chilton passed away on April 2, 2001 in Rapides Regional Medical 
Center in Alexandria, Louisiana. Probably very few of today's growers and processors in the 
Louisiana industry remember Dr. Chilton, although there are a few of us who remember him quite 
well. Dr. Chilton was 92 when he passed away and is survived by his wife, Alice Hunter Chilton 
of Bayou Rapides. The official notice of his death states that he was retired as a plant pathology 
professor and department head at Louisiana State University in Baton Rouge. He was also a former 
consultant for the Nicaragua Sugar Estates, director of LaPlace Enterprises, president of the local 
chapter of SAR, past president of the Louisiana Historical and Genealogical Society, president of 
the Historical Association of Central Louisiana, a Rotarian and was listed in Who's Who in the 
World. 

From a personal recollection, Dr. Chilton was bigger than all those things. He was most 
instrumental in establishing the sugarcane crossing and selection program at LSU. During the 1 950s, 
60s and early 70s, he and Elias Paliatseas were the individuals who led the crossing and selection 
program at LSU. Preston Dunckelman was also part of that team in the early years. It was 
demonstrated that sugarcane could be forced to flower in Louisiana using a photoperiod regime and 
that viable seed could be produced from these crosses. This work was done in the early 1 950s. The 
Grand Isle crossing facility was established, although it was used for flowering and crossing for only 
a couple of years and seed were planted in Baton Rouge for selection. The "L" selection program 
was established and high sugar content was a major objective in their selection effort. In fact, L60- 
25 was the first variety to come from that initiative and set a new high water mark in terms of sugar 
content in the industry. The variety lasted only a few years because of mosaic and RSD 
susceptibility, but definitely brought this industry into the era of high sugar varieties. 

Dr. Chilton, while known for his determination, aggressiveness and dedication toward the 
sugar industry, was also sometimes regarded as a "tough individual" and someone who could be 
quite combative. Those who crossed him soon learned how powerful he could be. He served on 
many a graduate student's committee, and from a personal standpoint, lived up to his reputation as 
"tough and spirited". He often kept the "fire lit" under people making sure they were always moving 
and he was always eager to share his sugarcane breeding philosophies with those interested in 
listening. He will always be remembered for his dedication, determination and the direction he 
brought to the LSU selection program. He will be sadly missed by his relatives and friends 
throughout the international sugar community. 






150 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

In Memoriam 

Jack L. Dean 

March 15, 1925-August 4, 2001 

Dr. Jack L. Dean, a retired USDA-ARS research plant pathologist, died on August 4, 2001 . 
Dr. Dean was born in Keota, Oklahoma on March 15, 1925. He served in the U. S. Navy during 
World War II and after the war, he obtained his BS in botany in 1949 and his MS degree in plant 
pathology in 1951 from Oklahoma State University. From 1951 to 1966, he was a USDA-ARS plant 
pathologist and then a research plant pathologist at Meridian, Mississippi. During this time he 
completed his PhD in plant pathology at Louisiana State University. In 1 966, Dr. Dean moved to 
the Sugarcane Field Station at Canal Point, Florida where he served as a Research Sugarcane 
Pathologist until he retired for the first time in 1987. Dr. Dean then became one of the oldest if not 
the most experienced of research associates at the University of Florida working with Dr. Mike 
Davis until he retired again in 1 993. During his career he authored and/or co-authored 1 00 research 
papers. He developed inoculation techniques for sugarcane mosaic and leaf scald to select resistant 
cultivars that are still used at Canal Point. During the 1970's and 1980's he addressed the threat of 
sugarcane rust and smut that were introduced on the US mainland. Dr. Dean understood the 
theoretical bases of statistics and stressed their practical impact on the selection of CP cultivars. 
During the last phase of Dr. Dean's career he helped determine the importance of ratoon stunting 
disease in Florida and helped develop techniques to screen for resistance. Dr. Dean was an Honorary 
member of the Joint Division of the American Society of Sugar Cane Technologists. 

Jack Dean was born to be a scientist. He may never have come across a biological problem 
that did not intrigue him. This quality, combined with his experience and knowledge, made him both 
a mentor and a youthful inspiration to his fellow scientists in his final years at Canal Point. Many 
will remember Dr. Dean's contributions to sugarcane pathology. Those of us who knew him 
personally will also remember him for his humor and his intense thought which at times could 
override the more trivial aspects on a person's mind. Jack probably entered more than one 
colleague's office forgetting why he was there. This was not a fault, it was how he was when he was 
thinking about research. For those fortunate enough to know him, we consider ourselves lucky. He 
was a good man. 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

AMERICAN SOCIETY OF SUGAR CANE TECHNOLOGISTS 

EDITORIAL POLICY 

Nature of papers to be published: 

Papers submitted must represent a significant technological or scientific contribution. Papers 
will be limited to the production and processing of sugarcane, or to subjects logically related. 
Authors may submit papers that represent a review, a new approach to field or factory problems, or 
new knowledge gained through experimentation. Papers promoting machinery or commercial 
products will not be acceptable. 

Frequency of publication: 

The Journal will appear at least once a year. At the direction of the Joint Executive 
Committee, the Journal may appear more frequently. Contributed papers not presented at a meeting 
may be reviewed, edited, and published if the editorial criteria are met. 

Editorial Committee: 



The Editorial Committee shall be composed of the Managing Editor, Technical Editor for 
the Agricultural Section, and Technical Editor for the Manufacturing Section. The Editorial 
Committee shall regulate the Journal content and assure its quality. It is charged with the authority 
necessary to achieve these goals. The Editorial Committee shall determine broad policy. Each editor 
will serve for three years; and may at the Joint Executive Committee's discretion, serve beyond the 
expiration of his or her term. 

Handling of manuscripts: 

Four copies of each manuscript are initially submitted to the Managing Editor. Manuscripts 
received by the Managing Editor will be assigned a registration number determined serially by the 
date of receipt. The Managing Editor writes to the one who submitted the paper to inform the author 
of the receipt of the paper and the registration number which must be used in all correspondence 
regarding it. 

The Technical Editors obtain at least two reviews for each paper from qualified persons. The 
identities of reviewers must not be revealed to each other nor to the author during the review process. 
Instructions sent with the papers emphasize the necessity for promptness as well as thoroughness in 
making the review. Page charges will be assessed for the entire manuscript for non-members. 
Members will be assessed for those pages in excess often (10) double spaced Times New Roman 
(TT) 12 pt typed pages of 8 1/2" x 11" dimension with one (1) inch margins. 

When a paper is returned by reviewers, the Technical Editor evaluates the paper and the 
recommendations of the reviewers. If major revisions are recommended, the Technical Editor sends 
the paper to the author for this purpose, along with anonymous copies of reviewers' 
recommendations. When the paper is returned to the Technical Editor, he/she will judge the 
adequacy of the revision and may send the paper back to any reviewer for further review. When the 

152 






Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

paper has been revised satisfactorily, it is sent to the Managing Editor for publishing. A paper sent 
to its author for revision and held more than 6 months will be given a new date of receipt when 
returned. This date will determine the priority of publication of the paper. 

A paper rejected by one reviewer may be sent to additional reviewers until two reviewers 
either accept or reject the paper. If a paper is judged by two or more reviewers as not acceptable for 
the Journal, the Technical Editor returns it to the author along with a summary of the reasons given 
by the reviewers for the rejection. The registration form for the paper is filled out and returned to 
the Managing Editor along with copies of the reviewers' statements and a copy of the Technical 
Editor's transmittal letter to the author. The names of all reviewers must be shown on the registration 
form transmitted to the Managing Editor. 

If the paper as received is recommended by two reviewers for publication in the Journal, it 
is read by the Technical Editor to correct typographical, grammatical, and style errors and to improve 
the writing where this seems possible and appropriate, with special care not to change the meaning. 
The paper is then sent by the Technical Editor to the Managing Editor who notifies the authors of 
the acceptance of the paper and of the probable dates of publication. At this time, the Managing 
Editor will request a final version in hardcopy and on diskette in WordPerfect format from the 
corresponding author. 

Preparation of papers for publication: 

Papers sent by the Technical Editor to the Managing Editor are prepared for printing 
according to their dates of original submittal and final approval and according to the space available 
in the next issue of the Journal. 

The paper is printed in the proper form for reproduction, and proofs are sent to the authors 
for final review. When the proofs are returned, all necessary corrections are made prior to 
reproduction. The author will be notified at the appropriate time to order reprints at cost. 

Any drawings and photographs for the figures in the paper are "scaled" according to their 
dimensions, the size of lettering, and other factors. They are then sent to the printer for camera work. 
Proofs of the illustrations are sent to the authors. Any changes requested at this stage would be 
expensive and authors will be expected to pay the cost of such changes. 

Reprinting in trade journals has the approval of the Editorial Committee provided: a) no 
article is reprinted before being accepted by the Journal; b) credit is given all authors, the author's 
institutions, and the ASSCT; and c) permission of all authors has been obtained. Summaries, 
condensations, or portions may be printed in advance of Journal publication provided the approval 
of the Editorial Committee has been obtained. 



153 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

RULES FOR PREPARING PAPERS TO BE PRINTED IN THE 
JOURNAL OF THE AMERICAN SOCIETY OF SUGAR CANE TECHNOLOGISTS 

Format 

Unless the nature of the manuscript prevents, it should include the following sections in the 
order listed: ABSTRACT, INTRODUCTION, MATERIALS and METHODS, RESULTS, 
DISCUSSION (OR RESULTS AND DISCUSSION), CONCLUSIONS, ACKNOWLEDGMENTS, 
and REFERENCES. Not all the sections listed above will be included in each paper, but each 
section should have an appropriate heading that is centered on the page with all letters capitalized. 
Scientific names shall be italicized. 

All material (including tables and figures) shall be submitted on 8V2 X 11 inch paper 
with one inch margins on all sides. If using WordPerfect, set the bottom margin at 0.5 inches. 
This will set the page number at 0.5 inches and the final line of text at 1 inch from the bottom 
margin. Exactness in reproduction can be insured if electronic copies of the final versions of 
manuscripts are submitted. Authors are encouraged to contact the managing editor for specifics 
regarding software and formatting software to achieve ease of electronic transfer. 

Authorship 

Name of the authors, institution or organization with which they are associated, and their 
locations should follow the title of the paper. 

Abstract 

The abstract should be placed at the beginning of the manuscript, immediately following the 
author's name, organization and location. The abstract should be limited to a single self-contained 
paragraph of about 250 words. State your rationale, objectives, methods, results, and their meaning 
or scope of application. Be specific. Identify the crops or organisms involved, as well as soil type, 
chemicals, or other details that figure in interpretation of the results. Do not cite tables, figures, or 
references. Avoid equations unless they are the focus of the paper. 

Tables 

Number the tables consecutively and refer to them in the text as Table 1 , Table 2, etc. Each 
table must have a heading or caption. Capitalize only the initial word and proper names in table 
headings. Headings and text of tables should be single spaced. Use TAB function rather than 
SPACE BAR to separate columns of a table. 

Figures 

Number the figures consecutively and refer to them in the text as Figure 1, Figure 2, etc. 
Each figure must have a legend. Figures must be of sufficient quality to reproduce legibly. 



154 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Drawings & Photographs 

Drawings and photographs must be provided separately from the text of the manuscript and 
identified on the back of each. Type figure numbers and legends on separate pieces of paper with 
proper identification. Drawings and photographs should be of sufficient quality that they will 
reproduce legibly. 

Reference Citations 

The heading for the literature cited should be REFERENCES. References should be arranged 
such that the literature cited will be numbered consecutively and placed in alphabetical order 
according to the surname of the senior author. In the text, references to literature cited should be 
made by name of author(s) and year of publication from list of references. Do not use capital letters 
in the titles of such articles except in initial words and proper names, but capitalize words in the titles 
of the periodicals or books. 

Format Example 

ITCHGRASS (ROTTBOELLIA COCHINCHINENSIS) CONTROL 
IN SUGARCANE WITH POSTEMERGENCE HERBICIDES 

Reed J. Lencse and James L. Griffin 

Department of Plant Pathology and Crop Physiology 

Louisiana Agricultural Experiment Station, LSU Agricultural Center 

Baton Rouge, LA 70803 

and 

Edward P. Richard, Jr. 

Sugarcane Research Unit, USDA-ARS, Houma, LA 70361 

ABSTRACT 

INTRODUCTION 

MATERIALS AND METHODS 

RESULTS AND DISCUSSION 

Table 1 . Visual itchgrass control and sugarcane injury as influenced by over-the-top herbicide 
application at Maringouin and Thibodaux, LA, 1989. 

CONCLUSIONS 

ACKNOWLEDGMENTS 

REFERENCES 

155 






Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

GUIDELINES FOR PREPARING PAPERS FOR JOURNAL OF ASSCT 

The following guidelines for WordPerfect software are intended to facilitate the production 
of this journal. Authors are strongly encouraged to prepare their final manuscripts with WordPerfect 
6.0 or a later version for Windows. Please contact the Managing Editor if you will not use one of 
those software packages. 

Paper & Margins : All material (including tables and figures) shall be submitted on 8V2 X 1 1 inch 
paper with one inch margins on all sides. To achieve this with WordPerfect, set the top, left, and 
right margins at one inch. However, set the bottom margin at 0.5 inches. This will place the page 
number at 0.5 inches and the final line of text at one inch. 

Fonts: Submit your document in the Times New Roman (TT) 12pt font. If you do not have this 
font, contact the Managing Editor. 

Ali gnment: Choose the full alignment option to prepare your manuscript. The use of SPACE BAR 
for alignment is not acceptable. As a general rule SPACE BAR should only be used for space 
between words and limited other uses. Do not use space bar to indent paragraphs, align and indent 
columns, or create tables. 

Do not use hard returns at the end of sentences within a paragraph. Hard returns are to be 
used when ending paragraphs or producing a short line. 

Place tables and figures within the text where you wish them to appear. Otherwise, all 
tables and figures will appear after your References section. 

Styles: Italicize scientific names. Do not use underline. 

Tables: Use Tab stops and the Graphics line draw option when constructing tables. Avoid the 
space bar to separate columns (see alignment). All lines should begin with the left most symbol in 
their left most column and should end with the right most symbol in their right most column. 

Citations: When producing Literature Citations, use the indent feature to produce text as below. 

1. Smith, I. M., H. P. Jones, C. W. Doe, 1991. The use of multidiscipline approaches to control 
rodent populations in plants. Journal of American Society of Plant Management. 10:383- 
394. 






156 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

CONSTITUTION OF THE 
AMERICAN SOCIETY OF SUGAR CANE TECHNOLOGISTS 

As Revised and Approved on June 21, 1991 
As Amended on June 23, 1994 
As Amended on June 15, 1995 

ARTICLE I 

Name, Object and Domicile 

Section 1 . The name of this Society shall be the American Society of Sugar Cane Technolo-gists. 

Section 2. The object of this society shall be the general study of the sugar industry in all its 
various branches and the dissemination of information to the members of the 
organization through meetings and publications. 

Section 3. The domicile of the Society shall be at the office of the General Secretary-Treasurer (as 
described in Article IV, Section 1). 

ARTICLE H 

Divisions 

The Society shall be composed of two divisions, the Louisiana Division and the Florida 
Division. Each division shall have its separate membership roster and separate officers and 
committees. Voting rights of active and honorary members shall be restricted to their respective 
divisions, except at the general annual and special meetings of the entire Society, hereinafter 
provided for, at which general meetings active and honorary members of both divisions shall have 
the right to vote. Officers and committee members shall be members of and serve the respective 
divisions from which elected or selected, except the General Secretary-Treasurer who shall serve the 
entire Society. 

ARTICLE m 



Section 1, 



Section 2. 



Section 3. 



Membership and Dues 

There shall be five classes of members: Active, Associate, Honorary, Off-shore or 
Foreign, and Supporting. 

Active members shall be individuals residing in the continental United States actually 
engaged in the production of sugar cane or the manufacture of cane sugar, or research 
or education pertaining to the industry, including employees of any corporation, firm 
or other organization which is so engaged. 

Associate members shall be individuals not actively engaged in the production of sugar 
cane or the manufacture of cane sugar or research pertaining to the industry, but who 
may be interested in the objects of the Society. 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

Section 4. Honorary membership shall be conferred on any individual who has distinguished 
himself or herself in the sugar industry, and has been elected by a majority vote of the 
Joint Executive Committee. Honorary membership shall be exempt from dues and 
entitled to all the privileges of active membership. Each Division may have up to 15 
living Honorary Members. In addition, there may be up to 5 living Honorary members 
assigned to the two Divisions jointly. 

Section 5. Off-shore or foreign members shall be individuals not residing in the continental 
United States who may be interested in the objects of the Society. 

Section 6. Supporting members shall be persons engaged in the manufacturing, production or 
distribution of equipment or supplies used in conjunction with production of sugar cane 
or cane sugar, or any corporation, firm or other organization engaged in the production 
of sugar cane or the manufacture of cane sugar, who may be interested in the objects 
of the Society. 

Section 7. Applicants for new membership shall make written application to the Secretary- 
Treasurer of the respective divisions, endorsed by two members of the division, and 
such applications shall be acted upon by the division membership committee. 

Section 8. Minimum charge for annual dues shall be as follows: 

Active Membership $10.00 

Associate Membership $25.00 

Honorary Membership NONE 

Off-shore or Foreign Membership $20.00 

Supporting Membership $50.00 

Each Division can assess charges for dues more than the above schedule as 
determined by the Division officers or by the membership at the discretion of the 
officers of each Division. 

Dues for each calendar year shall be paid not later than 3 months prior to the 
annual meeting of the member's division. New members shall pay the full amount 
of dues, irrespective of when they join. Any changes in dues will become 
effective in the subsequent calendar year. 









Section 9. Dues shall be collected by each of the Division's Secretary-Treasurer from the members 
in their respective divisions. Unless and until changed by action of the Joint Executive 
Committee, 50 percent of the minimum charge for annual dues, as described in Section 
8 for each membership class, shall be transmitted to the office of the General Secretary- 
Treasurer. 

Section 10. Members in arrears for dues for more than a year will be dropped from membership 
after thirty days notice to this effect from the Secretary-Treasurer. Members thus 
dropped may be reinstated only after payment of back dues and assessments. 

Section 1 1 . Only active members of the Society whose dues are not in arrears and honorary 
members shall have the privilege of voting and holding office. Only members (all 
classes) shall have the privilege of speaking at meetings of the Society. 



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Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

ARTICLE IV 

General Secretary-Treasurer and Joint Executive Committee 

Section 1. The General Secretary-Treasurer shall serve as Chief Administrative Officer of the 
Society and shall coordinate the activities of the divisions and the sections. He or she 
will serve as ex-officio Chairperson of the Joint Executive Committee and as General 
Chairperson of the General Society Meetings, and shall have such other duties as may 
be delegated to him or her by the Joint Executive Committee. The office of the 
General Secretary-Treasurer shall be the domicile of the Society. 

Section 2. The Joint Executive Committee shall be composed of the elected members of the two 
division Executive Committees, and is vested with full authority to conduct the 
business and affairs of the Society. 

ARTICLE V 

Division Officers and Executive Committee 

Section 1 . The officers of each division of the Society shall be: a President, a First Vice-President, 
a Second Vice-President, a Secretary-Treasurer or a Secretary and a Treasurer, and an 
Executive Committee composed of these officers and four other members, one from 
each section of the Division (as described in Section 3 of Article VII), one elected at 
large, and the President of the previous Executive Committee who shall serve as an Ex- 
Officio member of the Division Executive Committee. The office of the Secretary- 
Treasurer in this constitution indicates either the Secretary-Treasurer, or the Secretary 
and the Treasurer. 

Section 2. These officers, except Secretary-Treasurer, shall be nominated by a nominating 
committee and voted upon before the annual division meeting. Notices of such 
nominations shall be mailed to each member at least one month before such meeting. 
Ballots not received before the annually specified date will not be counted. 

Section 3. The Secretary-Treasurer shall be appointed by and serve as a non- voting member at the 
pleasure of the Division Executive Committee. The Secretary-Treasurer may not hold 
an elected office on the Executive Committee. 

Section 4. The duties of these officers shall be such as usually pertain to such officers in similar 
societies. 

Section 5. Each section as described in Article VII shall be represented in the offices of the 
President and Vice-President. 

Section 6. The President, First Vice-President, and Second Vice-President of each Division shall 
not hold the same office for two consecutive years. Either Section Chairperson (as 
described in Section 3 of Article VH) may hold the same office for up to two 
consecutive years. The terms of the other officers shall be unlimited. 

Section 7. The President shall be elected each year alternately from the two sections hereinafter 
provided for. In any given year, the Presidents of the two Divisions shall be nominated 
and elected from different sections. The President from the Louisiana Division for the 
year beginning February, 1 970, shall be nominated and elected from the Agricultural 
Section. The president from the Florida Division for the year beginning February, 



159 



Section 8. 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

1970, shall be nominated and elected from the Manufacturing Section. 

Vacancies occurring between meetings shall be filled by the Division Executive 
Committee. 



Section 9. The terms "year" and "consecutive year" as used in Articles V and VI shall be 
considered to be comprised of the elapsed time between one annual division meeting 
of the Society and the following annual division meeting of the Society. 

ARTICLE VI 

Division Committees 

Section 1. The President of each division shall appoint a committee of three to serve as a 
Membership Committee. It will be the duty of this committee to pass upon 
applications for membership in the division and report to the Secretary-Treasurer. 

Section 2. The President of each division shall appoint each year a committee of three to serve as 
a Nominating Committee. It will be the duty of the Secretary-Treasurer of the Division 
to notify all active and honorary members of the Division as to the personnel of this 
committee. It will be the duty of this committee to receive nominations and to prepare 
a list of nominees and mail this to each member of the Division at least a month before 
the annual meeting. 

ARTICLE VH 



Sections 
Section 1. There shall be two sections of each Division, to be designated as: 

1. Agricultural 

2. Manufacturing 

Section 2. Each active member shall designate whether he or she desires to be enrolled in the 
Agricultural Section or the Manufacturing Section. 

Section 3. There shall be a Chairperson for each section of each Division who will be the member 
from that Section elected to the Executive Committee. It will be the duty of the 
Chairperson of a section to arrange the program for the annual Division meeting. 

Section 4. The Executive Committee of each Division is empowered to elect one of their own 
number or to appoint another person to handle the details of printing, proofreading, 
etc., in connection with these programs and to authorize the Secretary-Treasurer to 
make whatever payments may be necessary for same. 

ARTICLE VIE 

Meetings 

Section 1 . The annual General Meeting of the members of the Society shall be held in June each 
year on a date and at a place to be determined, from time to time, by the Joint 
Executive Committee. At all meetings of the two Divisions of the Society, five percent 
of the active members shall constitute a quorum. The program for the annual meeting 









160 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

of the Society shall be arranged by the General Secretary-Treasurer in collaboration 
with the Joint Executive Committee. 

Section 2. The annual meeting of the Louisiana Division shall be held in February of each year, 
at such time as the Executive Committee of the Division shall decide. The annual 
meeting of the Florida Division shall be held in September or October of each year, at 
such time as the Executive Committee of that Division shall decide. Special meetings 
of a Division may be called by the Executive Committee of such Division. 

Section 3. Special meetings of a Section for the discussion of matters of particular interest to that 
Section may be called by the President upon request from the respective Chairperson 
of a Section. 

Section 4. At Division meetings, 10 percent of the active division members and the President or 
a Vice-President shall constitute a quorum. 

ARTICLE DC 

Management 

Section 1. The conduct and management of the affairs of the Society and of the Divisions 
including the direction of work of its special committees, shall be in the hands of the 
Joint Executive Committee and Division Executive Committees, respectively. 

Section 2. The Joint Executive Committee shall represent this Society in conferences with the 
American Sugar Cane League, the Florida Sugar Cane League, or any other association, 
and may make any rules or conduct any business not in conflict with this Constitution. 

Section 3. Four members of the Division Executive Committee shall constitute a quorum. The 
President, or in his or her absence one of the Vice-Presidents, shall chair this 
committee. 

Section 4. Two members of each Division Executive Committee shall constitute a quorum of all 
members of the Joint Executive Committee. Each member of the Joint Executive 
Committee, except the General Secretary-Treasurer, shall be entitled to one vote on all 
matters voted upon by the Joint Executive Committee. In case of a tie vote, the 
General Secretary-Treasurer shall cast the deciding vote. 

ARTICLE X 

Publications 

Section 1 . The name of the official journal of the Society shall be the "Journal of the American 
Society of Sugar Cane Technologists." This Journal shall be published at least once 
per calendar year. All articles, whether volunteered or invited, shall be subject to 
review as described in Section 4 of Article X. 

Section 2 . The Managing Editor of the Journal of the American Society of Sugar Cane 
Technologists shall be a member of either the Florida or Louisiana Divisions; however, 
he or she shall not be a member of both Divisions. The Division affiliation of 
Managing Editors shall alternate between the Divisions from term to term with the 
normal term being three years, unless the Division responsible for nominating the new 
Managing Editor reports that it has no suitable candidate. The Managing Editor shall 



161 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

be appointed by the Joint Executive Committee no later than 6 months prior to the 
beginning of his or her term. A term will coincide with the date of the annual Joint 
Meeting of the Society. No one shall serve two consecutive terms unless there is no 
suitable candidate from either Division willing to replace the current Managing Editor. 
If the Managing Editor serves less than one year of his or her three-year term, another 
candidate is nominated by the same Division, approved by the other Division, and 
appointed by the General Secretary-Treasurer to a full three-year term. If the appointed 
Managing Editor serves more than one year but less than the full three-year term, the 
Technical Editor from the same Division will fill the unexpired term of the departed 
Managing Editor. In the event that the Technical Editor declines the nomination, the 
General Secretary-Treasurer will appoint a Managing Editor from the same Division 
to serve the unexpired term. 

Section 3 . The "Journal of the American Society of Sugar Cane Technologists" shall have two 
Technical Editors, which are an Agricultural Editor and a Manufacturing Editor. The 
Managing Editor shall appoint the Technical Editors for terms not to exceed his or her 
term of office. Any Technical Editor shall be a member of either the Louisiana or 
Florida Division. Each Division will be represented by one technical editor at all times 
unless the Executive Committee of one Division and the Managing Editor agree that 
there is no suitable candidate willing to serve from that Division. 

Section 4 . Any member or nonmember wishing to contribute to the Journal of the American 
Society of Sugar Cane Technologists shall submit his or her manuscript to the 
Managing Editor. The Managing Editor shall then assign the manuscript to the 
appropriate Technical Editor. The Technical Editor shall solicit peer reviews until, in 
the opinion of the Technical Editor, two responsible reviews have been obtained that 
either accept (with or without major or minor revision) or reject the manuscript. For 
articles accepted with major revision, it shall be the responsibility of the Technical 
Editor to decide if the authors have satisfactorily completed the major revision(s). The 
Technical Editor may solicit the opinion of the reviewers when making this decision. 
The Technical Editors shall not divulge the identity of any reviewer. The Managing 
Editor shall serve as Technical Editor of any manuscript which includes a Technical 
Editor as an author. 

ARTICLE XI 

Amendments 



Section 1. Amendments to this Constitution may be made only at the annual meeting of the 
Society or at a special meeting of the Society. Written notices of such proposed 
amendments, accompanied by the signature of at least twenty (20) active or honorary 
members must be given to the General Secretary-Treasurer at least thirty (30) days 
before the date of the meeting, and he or she must notify each member of the proposed 
amendment before the date of the meeting. 

ARTICLE XH 

Dissolution 

Section 1 . All members must receive notification from the General Secretary-Treasurer of any 
meeting called for the purpose of terminating the Society at least thirty (30) days prior 
to the date of the meeting. After all members have been properly notified, this 
organization may be terminated at any time, at any regular or special meeting called for 






162 



B i 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

that purpose, by an affirmative vote of two-thirds of the total honorary and active 
members in good standing present at the meeting. Thereupon, the organization shall 
be dissolved by such legal proceedings as are provided by law. Upon dissolution of the 
Joint Society, its assets will be divided equally between the two Divisions of the 
Society. Dissolution of the Joint Society will not be cause for automatic dissolution 
of either Division. Upon dissolution of either Division, its assets will be divided in 
accordance with the wishes of its members and in conformity with existing IRS 
regulations and other laws applicable at the time of dissolution. 

ARTICLE Xm 

Assets 

Section 1. No member shall have any vested right, interest or privilege of, in, or to the assets, 
functions, affairs or franchises of the organization; nor any right, interest or privilege 
which may be transferable or inheritable. 



163 



Journal American Society of Sugarcane Technologists, Vol. 22, 2002 

AUTHOR INDEX 



Adland, Max 112 

Ande, B 9 

Ande, P 9 

Andrews, Linda S 90, 139, 144 

Bernhardt, Carlos 144 

Birkett, Harold 120 

Bischoff, K. P 42, 132 

Bocharnikova, E. A 9 

Breaux, Janis 53, 129 

Bucke, Chris 112 

Calvert, D. V 9, 21 

Champagne, Lonnie P 30 

Cherry, R. H 127 

Chou, Chung Chi 142 

Clarke, Stephen J 138 

Cochran, J. C 145 

Comstock, J. C 125, 134 

Damms, Mike 144 

Daroub, S 123 

Daugrois, J. H 131 

Davis, M. J 134 

Day, Don F 144 

Deren, Christopher W 73 

Easdale, William 137 

Eggleston, Gillian 140 

Fanjul, John A 137 

Gilbert, R. A 122,130 

Gill, Bikram S 73 

Glaz, Barry 73, 123, 134 

Godshall, Mary An. . 90, 101, 125, 139, 144 

Gravois, K. A 42, 132 

Griffin,! L 131 

Grigg, Brandon C 62 

Grisham, M. P 125 

Hahn,Neal 138 

Hallmark, W. B 124 

Hauck, Walter 143 

Hawkins, G. L 124 

Hentz, Matthew 126 

Horn, Jennifer 112 

Hoy, J. W 131,132 

Hou, Chen-Jian 125 

Iqbal, Khalid 139 

Johnson, Richard M 101, 139 



Kampen, Willem H 142, 143 

Kang, Manjit S 73 

Kitchen, Brian 145 

Lama Jr., Miguel 141 

Legendre, Benjamin L 30, 42, 120, 125 

Lingle, Sarah 133 

Luo, Y 122 

Lyrene, Paul M 73 

Matichenkov, V. V 9, 21 

Miller, J. D. 62, 73, 122, 128, 130, 134, 135 

Milligan, Scott B 132 

Monge, Adrian 140 

Morris, D. R 123 

Muchovej, Rosa M 122 

Njapou, Henry 142, 143 

Nuessly, Gregg 126, 127 

Ogier, Blaine E 140 

Okhuysen, Jorge 137 

Pan, Yong.-Bao 125, 135 

Posey, F. R 128 

Raid, R. N 127 

Rauh, J 144 

Reagan, T. E 128 

Rein, Peter W 141 

Rodriguez, Raul 141 

Rowe, Robin 133 

Samour, Eduardo 137 

Sarkar, D 144 

Selassi, M. E 30, 53, 124, 129 

Shine Jr., J. M 122, 130 

Singleton, Victoria 1 12, 140 

Snyder, George H 62 

Spear, Scott S 101, 139 

Stein, Jeanie 1 20 

Swift, Nell 146 

Tai,P.Y.P 134,135 

Tew, Thomas L 120, 128 

Timple, Candace 133 

Viator, Howard P 132 

Way, M. 128 

Weber, Brent 145 

White, W.H 125, 128 

Williams, G. J 124 

Ying,Z 134 









164 



LSU Libraries 







1*IK 



JOURNAL 



American Society 

of 

Sugar Cane Technologists 



Volume 23 

Florida and Louisiana Divisions 

June, 2003 



ASSCT 



[.-MAIN 
rCKS 



2002 JOINT EXECUTIVE COMMITTEE 
AMERICAN SOCIETY OF SUGAR CANE TECHNOLOGISTS 



General Secretary-Treasurer 

Denver T. Loupe 






Florida Division 



Office 



Louisiana Division 



John A. Fanjul 
James M. Shine 
Michael Damms 
John Dunckelman 
Tere Johnson 
Nael El-Hout 
David Hall 
Scott Milligan 



President 

First Vice-President 

Second Vice-President 

Chairman, Agricultural Section 

Chairman, Manufacturing Section 

Chairman at Large 

Past President 
Secretary-Treasurer 



Chris Mattingly 

Tony Parris 

Keith Bischoff 

Freddie Martin 

Juan Navarro 

Benjamin Legendre 

Will Legendre 

Denver T. Loupe 



EDITORS 

Journal American Society of Sugar Cane Technologists 
Volume 23 
June, 2003 

Managing Editor 

Ron DeStefano 

Agricultural Editor 

Nael El-Hout 

Manufacturing Editor 

Manolo Garcia 



PROGRAM CHAIRMAN 

32nd Annual Joint Meeting 

American Society of Sugar Cane Technologists 
Robert A. Gilbert 



Honorary membership shall be conferred on any individual who has distinguished himself 
or herself in the sugar industry, and has been elected by a majority vote of the Joint Executive 
Committee. Honorary membership shall be exempt from dues and entitled to all the privileges of 
active membership. Each Division may have up to 1 5 living Honorary Members. In addition, there 
may be up to 5 living Honorary members assigned to the two Divisions jointly. (Article IQ, Section 
4 of the Constitution of the American Society of Sugar Cane Technologists). 



As of May 2002, the following is the list of the living Honorary members of the American 
Society of Sugar Cane Technologists for Florida and Louisiana Divisions: 



Florida Division 


Joint Division 


Louisiana Division 


Guillermo Aleman 


Preston H. Dunckelman 


Felix "Gus" Blanchard 


Henry J. Andreis 


Lloyd L. Lauden 


Richard Breaux 


Pedro Arellano 


Denver T. Loupe 


P.J. "Pete" deGravelles 


Antonio Arvesu 


Harold A. Willett 


Gilbert Durbin 


John B. Boy 


Peter Tai 


Minus Granger 


David G. Holder 




Sess D. Hensley 


Arthur Kirstein HI 




James E. Irvine 


Jimmy D. Miller 




Dalton P. Landry 


Joseph Orsenigo 




Lowell L. McCormick 


Ed Rice 




Joe Polack 


Bias Rodriguez 




Charles Savoie 


George H. Wedgworth 






ytj i 1 4u*-v 






SfacJc* 












ss 












2002 DENVER T. LOUPE BEST PRESENTATION AWARDS 


> 







H. Waguespack, Jr., W. Jackson, B. Viator and C. Viator. The Effect of Combine Speed on Cane 
Quality at Alma Plantation in 2001 . 

Trevor D. Endres. Experiences with Unwashed Cane at Raceland. 

M. P. Grisham. Molecular Identification of Virus Isolates Causing Mosaic in Louisiana 
Sugarcane 

J. A. DaSilva. Development of Microsatellite Markers from Sugarcane Resistance Related 
Genes 



li 






TABLE OF CONTENTS 

President's Message - Florida Division 

John A. Fanjul 1 

President's Message - Louisiana Division 

Chris Mattingly 4 

PEER REFEREED JOURNAL ARTICLES Agricultural Section 7 



Laboratory Screening of Insecticides for Preventing Injury by the Wireworm 

Melanotus Communis (Coleoptera: Elateridae) to Germinating Sugarcane 8 

David G. Hall 

Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 20 

Collins A. Kimbeng and Mike C. Cox 

Repeatability Within and Between Selection Stages in a Sugarcane Breeding Program 40 

Jose A. Bressiani, Roland Vencovsky, and Jorge A. G. daSilva 

Enhanced Sugarcane Establishment Using Plant Growth Regulators 48 

Bob Wiedenfeld 

Estimating the Family Performance of Sugarcane Crosses Using Small Progeny Test 61 

P. Y. P. Tai, J. M. Shine, Jr., J. D. Miller, and S. J. Edme 

Incidence and Spread of Sugarcane Yellow Leaf Virus in Sugarcane Clones 

in the CP-Cultivar Development Program at Canal Point 71 

J. C. Comstock and J. D. Miller 

PEER REFEREED JOURNAL ARTICLES Manufacturing Section 79 

Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 80 

L. R. Madsen, II, B. E. White, and P. W. Rein 

AGRICULTURAL ABSTRACTS 93 

Green Cane Trash Blankets: Influence on Ratoon Crops in Louisiana 93 

E. P. Richard, Jr. and R. L. Johnson 

The Effect of Combine Speed on Cane Quality at Alma Plantation in 2001 93 

H. Waguespack, Jr., W. Jackson, B. Viator, and C. Viator 

Use of Cover Crops in Rotation with Sugarcane in a South Florida Mineral Soil 94 

R. M. Muchovej, J. J. Mullahey, T. A. Obreza, and P. R. Newman 



in 



Evaluation of Sorghum-Sudangrass Hybrids for Biomass Potential in 

Southern Louisiana 95 

T. L. Tew 

ENVOKE: A New Herbicide for Weed Control in U. S. Sugarcane 96 

E. K. Rawls, M. Johnson, S. Martin, L Glasgow, J. Shine, J Powell, 
B. Watson, and A. Bennett 

Experimental Products for Weed Control in Florida Sugarcane 96 

A. C. Bennett 

Effect of Calcitic Lime and Calcium Silicate Slag Rates and Placement on 

LCP 85-384 Plant Cane on a Light-Textured Soil 97 

W. B. Hallmark, G. J. Williams, G. L. Hawkins, and V. V. Matichenkov 

Sugarcane Leaf P Diagnosis in Organic Soils 97 

D. R. Morris, B. Glaz, G. Powell, C. W. Deren, 
G. H.Snyder, R. Perdomo, and M. F. Ulloa 

Wireworm Effects on Sugarcane Emergence After Short-Duration Flood 

Applied at Planting 98 

B. Glaz and R. Cherry 

Laboratory Screening of Insecticides for Preventing Injury by the Wireworm 

Melanotus communis (Coleoptera: Elateridae) to Germinating Sugarcane 99 

D.G.Hall 

Management Thresholds for the Sugarcane Borer on Louisiana Varieties 99 

F. R. Posey, C. D. McAllister, T. E. Reagan, and T. L. Bacon 

Yellow Sugarcane Aphid (Siphaflava) Colonization Strategy and its 

Effect on Development and Reproductive Rates on Sugarcane 100 

G. S. Nuessly and M. G. Hentz 

Field Trials of a Multiple-Pathogen Bioherbicide System with Potential 

to Manage Guineagrass in Florida Sugarcane 101 

S. Chandramohan, M. J. Duchrow, J. M. Shine, Jr., E. N. Rosskopf, 

and R. Charudattan 

Molecular Identification of Virus Isolates Causing Mosaic in Louisiana Sugarcane 102 

M. P. Grisham and Y.-B. Pan 

Incidence of Sugarcane Yellow Leaf Virus in Clones of Saccharum spp. in the World 

Collection at Miami and in the Collection at the Sugarcane Field Station, Canal Point 102 

J. C. Comstock, J. D. Miller, and R. J. Schnell 



IV 






Selection of Interspecific Sugarcane Hybrids Using Microsatellite DNA Markers 103 

Y.-B. Pan, T. Tew, M. P. Grisham, E. P. Richard, W. H. White, 
and J. Veremis 

Development of Microsatellite Markers from Sugarcane Resistence Related Genes 103 

J. daSilva 

The Effect of Temperature on Flowering and Seed Set in Sugarcane at Canal Point 104 

J. D. Miller and S. Edme 

Characterization of S. Spontaneum Collection for Juice Quality 105 

J. A. daSilva and J. A. Bressiani 

Family Selection in Sugarcane: Notes from Australia 105 

C. A. Kimbeng 

Assessment of Trends and Early Sampling Effects on Selection Efficiency 

in Sugarcane 106 

S. J. Edme, P. Y. P. Tai, and J. D. Miller 

Selection and Advancement of Sugarcane Clones in the Louisiana "L" Sugarcane 

Variety Development Program 106 

K. P. Bischoff and K. A. Gravois 

MANUFACTURING ABSTRACTS 108 

The Florida Sugar Industry: Trends and Technologies 108 

J. F. Alvarez and T. P. Johnson 

Versatility of the Antibody Dextran Test Method 108 

D. F. Day, J. Cuddihy, and J. Rauh 

Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 109 

L. R. Madsen H, B. E. White, and P. W. Rein 

Effect of pH and Time Between Wash-outs on the Performance of Evaporators 109 

G. Eggleston, A. Monge, and B. Ogier 

Maximize Throughput in a Sugar Milling Operation Using a Computerized 

Maintenence Management System (CMMS) 110 

K. A. Elliot 

Experiences with the First Full Scale Plate Evaporator in the North American 

Cane Sugar Industry Ill 

N. Swift, T. D. Endres, and F. Mendez 



Organic Acids in the Sugar Factory Environment Ill 

D. F. Day and W. H. Kampen 

Experiences with Unwashed Cane at Raceland Ill 

T. D. Endres 

POSTER SESSION 113 

Soil Erosion Research on Alluvial Soils Planted to Sugarcane: 

Experimental Approach and Preliminary Results 113 

T. S. Kornecki, B. C. Grigg, J. L. Fouss, and L. M. Southwick 

Laboratory Rearing of the Parasitoid Cotesia flavipes on Sugarcane Borer 

Diatraea saccharalis 113 

G. Hannig and D. G. Hall 

Disease Incidence and Yield Comparisons of KLEENTEK® Seedcane to 

Traditional Sources in Four Commercial Varieties in South Florida 114 

J. L. Flynn, K. Quebedaux, L. Baucum, and R. Waguespack 



VI 









Editorial Policy 115 

Rules for Preparing Papers to be Printed in the Journal of the 

American Society of Sugar Cane Technologists 117 

Guidelines for Preparing Papers for Journal of ASSCT 119 

Constitution of the American Society of Sugar Cane Technologists 120 

Author Index 127 



To order an extra copy of this volume, or a previous journal of American Society of Sugar Cane 
Technologists, write to: 

General Secretary-Treasurer 

American Society of Sugar Cane Technologists 

P.O. Box 25100 

Baton Rouge, LA 70894-5100 

Copies shipped within the USA are $10.00 (postage included) 

Copies shipped outside the USA are $10.00 (postage not included) 
Please add shipping costs as follows: 

Select method of delivery: 

surface mail (4-6 week delivery): add $5.00 per item 

air mail (7-10 day delivery): add $10 per item 



vn 



PRESIDENT'S MESSSAGE 
LOUISIANA DIVISION 

Chris Mattingly 

Lula-Westfield, LLC 

General Delivery 

Paincourtville, LA 70391 

On behalf of the membership of the Louisiana Division of the American Society of Sugar 
Cane Technologists, I would like to thank the Florida Division for hosting this year's annual joint 
meeting at Amelia Island Plantation. I look forward to this thirty-second annual meeting being as 
educational and enjoyable as the previous meetings have been. 

Let me begin by reviewing the 2000 crop and harvest report. The crop began with tremendous 
promise and the second largest acreage planted to cane in the state's history. With 491,109 acres in 
cane and a mild winter and spring, growers and mills were excited as well as a little nervous about 
the potential for a record crop. Good weather during April and May allowed quality fieldwork to be 
done in a timely manner and at lay-by the crop looked encouraging. Then in early June, tropical 
storm Allison came through dumping twelve to thirty-six inches of rain on Louisiana. Although the 
sugarcane crop did not experience the devastation that some row crops did, the damage to the cane 
crop was still significant. Many fields had standing water on them for several days and in some cases 
for over a week. To compound the problem, cloudy overcast skies and above normal rainfall for the 
remainder of the month of June placed additional stress on the crop in many areas. By late summer, 
most growers and mills had lowered their estimates somewhat but remained hopeful that the crop 
could overcome this weather related damage. However, shortly after the harvest began our fears were 
confirmed and our optimism over what might have been turned into disappointment. The 2001 crop 
would not be the record crop that the Louisiana industry had hoped it would be. The 45 1 ,820 acres 
harvested for sugar were only slightly less than the record acreage harvested in 2000. A yield of just 
over 33.1 tons of cane per acre resulted in a crop of 14,977,000 tons of cane ground. Although this 
was only about 88.5% of the predicted yield, this stands as the third largest cane crop ever produced 
in Louisiana. With a yield of 207 pounds of sugar per ton, the crop produced the second largest yield 
of sugar ever with 1 ,580,000 short tons of raw value sugar. This crop also yielded 86,368,000 gallons 
of 79.5 degree brix molasses. It took 117 days to grind the Louisiana crop this past year. The first 
mills began on September 17, 2001, and the last mill to grind finished on January 11, 2002. The 
closing of the Evan Hall mill after the 2000 crop left only seventeen mills in the state to grind this 
crop. The concerns of grinding a potential record crop with one less mill were unwarranted as ideal 
weather during harvest, good mill performance at most mills, and lower than expected tonnage 
allowed grinding to be completed earlier than expected. Most of the mills in the Bayou Lafourche 
and Mississippi River areas finished grinding before the end of December with a few mills in the 
northern and western parts of the belt running into January. 

All things considered, 2001 was a good year for the Louisiana sugar industry with many 
positive events taking place. The rebounding of the sugar price was one of the more significant 
changes of the past year. Although the increase was short-lived, the impact on last year's crop should 
be a little more than a one-cent per pound increase over the 2000 sugar price. Molasses prices were 
also up this year with an increase of about twenty cents per ton of cane. These price increases 

1 






represent a very positive economic impact on our industry. Dry weather during harvest allowed both 
growers and mills a chance to reduce costs and to maximize efficiency. One such example was that 
many mills were able to reduce or eliminate cane washing during good weather allowing more sugar 
recovery per ton of cane. 

The Louisiana sugar industry has the opportunity to use a special harvest permit, which 
allows cane haulers up to 100,000 pound gross vehicle weight. This privilege means a substantial 
cost savings to the whole industry, and it is important that we maintain this ability in spite of 
opposition from other groups. In an effort to combat abuse of this privilege, the industry made the 
decision to self-regulate its cane hauling this past harvest. With the State Legislature passing an 
industry-sponsored concurrent resolution that mandates all sugar mill scales be locked out at 1 00,000 
pounds, the incentive for overloading is removed since there is no payment for cane over the 1 00,000 
pound level. Complaints have been greatly reduced about overloaded trucks spilling cane and tearing 
up the highways. A similar success has been achieved with the cane burning issue by implementing 
a voluntary smoke and ash management program for the 2000 crop. There are numerous 
environmental and public issues associated with cane burning; therefore the state and the sugar 
industry have implemented this program to assist growers in addressing these types of issues. The 
significant reduction in the number of smoke- and ash-related complaints this past year attest to the 
success of this program. In both of these cases the industry has been praised for taking positive steps 
to solve its own problems. 

Another high point of the 2001 crop has been a record setting performance by a Louisiana 
mill grinding two million tons of cane in a single season. On January 8, the Enterprise mill of M.A. 
Patout & Son, Ltd. made Louisiana history by being the only mill in the state to ever grind two 
million tons of cane. Congratulations to M.A. Patout & Son, Ltd. along with all of the growers and 
employees of the Enterprise mill. 

No agricultural industry or commodity can bank on being successful or profitable every year. 
There are just too many variables and no guarantees. A couple of things such as hard work, 
dedication, and the willingness and ability to do what it takes will certainly improve chances for 
success. The Louisiana sugar industry has always realized the value of this philosophy and embraced 
it. It is no secret that increased production and improved efficiency of our factories and our farms 
are the best way to combat rising costs and depressed sugar prices. Dedicated scientists doing 
research and developing the technologies to keep our industry competitive and progressive 
accomplish these objectives. 

One of the most basic and important types of research work is the variety development 
program. This work is a cooperative effort by the USDA-ARS in Houma, the Sugar Research Station 
of the LSU Ag Center, and the American Sugar Cane League. Together they are responsible for the 
breeding, selection, and advancement of new varieties in Louisiana. The LSU Ag Center and USDA- 
ARS also provide valuable information to growers from research they conduct on all cultural 
practices from planting to harvest, crop protection, pest management, and economics. In addition, 
they team-up with the American Sugar Cane League and Audubon Sugar Institute to study cane 
quality issues affecting both growers and processors. Sugar mills in Louisiana look to Audubon 
Sugar Institute for new mill research along with help with processing problems and training of 
factory personnel. The American Sugar Cane League works with both growers and processors on 






a wide variety of issues. The League handles most of the political issues and the lobbying efforts for 
the industry. Through its network of local, state, and national committees, the Farm Bureau often 
assists the sugar industry on commodity and political issues. 

The information generated by the research and work of these groups is of vital importance 
to our industry. Various meetings, conferences, field days and our own society plays an integral part 
in disseminating this information. The American Society of Sugar Cane Technologists joint 
meeting as well as our respective division meetings provide excellent mediums for reporting results 
of research, new technologies, and product development. 

With the invaluable assistance of these support groups and the continued hard work and 
dedication of the growers and processors, our industry demonstrates its willingness and ability to 
succeed. Because the future holds no guarantees, we are poised to face its challenges. Our most 
immediate challenge is to assure the industry of a favorable sugar provision in the upcoming Farm 
Bill. Much hard work has gone into this effort and at this time (May 1) things look favorable. The 
problems with Mexico over NAFTA are ongoing, but it appears that the problem with importation 
of stuffed molasses from Canada is heading towards a permanent resolution thanks to the work of 
Senator Breaux. The industry faces a constant battle to market sugar at a fair price. Will the growers 
and mills in Louisiana own a refinery in the future? Less mills grinding more cane means longer 
grindings. Our researchers are challenged to develop varieties that mature earlier and have better cold 
tolerance and post freeze deterioration. Can we develop a cane ripener that works quickly and has 
no adverse affect on subsequent stubble crops? Will an equitable cane payment formula be 
developed that rewards growers for delivering quality cane and rewards mills for recovering more 
sugar from this cane? 

These and many other challenges will face our industry in the future, and we will be prepared 
to face them if we work together. No individual or group can do it alone. It has taken many people 
working together to make the Louisiana Sugar Industry the success that it is today, and it will take 
this continued cooperation to ensure our future. 



PRESIDENT'S MESSAGE 
FLORIDA DIVISION 

John A. Fan jul 

Atlantic Sugar Association 

P.O. Box 1570 

Belle Glade, FL 33430 

This past crop for Florida, in spite of freezes on January 1 and 6, 2001, the drought during 
the spring growth period, followed by flooding in late summer, early fall, managed to be very good. 
Looking back five years, this year was the third largest crop and had the second best yield to date. 
I think that the 2001-02 crop year presented a real revolution in the mainland cane sugar industry, 
especially in Florida. As of November, 2001, more than 80%, if not all of the Florida industry can 
be said to have become "vertically integrated," with the purchase of the Domino Sugar Refineries 
by The American Sugar Refining Company, formed by the growers of the Sugar Cane Growers 
Cooperative, Florida Crystals Corporation, and Atlantic Sugar Association. 

This venture brings together Okeelanta's refinery, R.S.I. Yonkers refinery, and Domino's 
Baltimore, New York, and New Orleans refineries, into one corporation, which together with U.S. 
Sugar's Clewiston refinery, means that for the first time in history, one can say that almost 50 
percent of all the refined sugar made from sugar cane is truly "From the Field to the Table." 

All of this presents and will present new challenges and opportunities for all of us. I think 
we will be more demanding of ourselves in every aspect of our industry, becoming a truly agri- 
industrial business. We are now responsible for our product way beyond our traditional boundaries; 
therefore, we have to be more conscientious of our bottom line, all the way up from agriculture 
research and development to quality control at the mill/sugar house, through our own refineries, to 
the ultimate consumer. 

The motto of the ASSCT is: "Organized for the Advancement of the Mainland Cane Sugar 
Industry." Never before has this ever been so important. I believe that to survive in the near and long 
term, we must be aware that on an ascending scale in our vertically integrated industry, all of us are 
responsible for improving efficiencies, which will increase productivity with cost effectiveness 
through positive accountability, in order to achieve maximum profitability. 

Today we are tied together into four major sections or divisions, each of which has their own 
subdivisions: 

I. Agriculture: with it's research and development working on developing new cane varieties through 
traditional genetic development, and using transengenics and bio-technology, must maintain this ever 
important work that helps us increase our sugar per acre production, which in my opinion, is, at our 
level, the true "bottom line" goal. We need optimum soil fertility working hand in hand with cane 
varieties to maintain high yields through recycling mill muds and preventing erosion. Soil 
conservation is of the highest priority, especially in Florida. Agronomy together with best farming 
practices, within our own ecosystem is everyone's concern. 

Farming and land preparation are of the utmost importance, and rotation guided by research 

4 






and development, hold the key to our economic future. Corn, rice and vegetables, all help farm 
profitability and soil conservation. Planting, cultivation, fertilization, and pest control are equally 
important to maintain productivity. Today with the advent of precision agriculture, farming can be 
very precise and cost effective, implementing all of the above, through G.P.S. cultivation and 
practices. 

II. Harvesting, in most cases in Florida, is a function of the mills, but in some cases, and in most of 
Louisiana, I understand, is a function of farming. Harvesting and hauling have their own important 
contributions. Burning, while thought to be on it's way out, is a function of harvesting. Cane 
freshness is essential to provide good juice quality to the mill. We at FCC try to keep it under 13 
hours, burn to scale. Advances in cane harvesting machines have improved billeted cane to a level 
of efficiency and cost that has surpassed all expectations. Infield hauling with the implementation 
of high dumps, can save money and time. We that use the transfer stations need to maintain efficient 
operations and quick turnarounds. Keeping good road conditions and proper trailer loading is 
especially important in feeding the mills. 

III. Mill: It is very important that field harvesting and hauling be coordinated and maintain good 
communications during the crop. Good yard management, including weighing and storing is of the 
utmost importance. Time in the yards should be held to a minimum and we strive to keep the cane 
no more that six to eight hours and feed the mill at a uniform rate. A mill is only as good as its cane 
quality, it cannot produce more than what it receives from the field. Grinding and extraction are two 
functions very important in holding down crop costs and increase profitability. You all know how 
much one crop day costs, and how much in earnings, one point in extraction can mean. Another 
factor is bagasse quality. The better the bagasse, the less fossil fuel is needed and the better the sugar 
house works. Proper mill settings to equal the grinding rate is essential. Fabrication has four 
functions that have to work in perfect coordination: clarification, evaporation, sugar 
boiling/crystallization, and sugar production. High standards of sugar quality, high Pol and low 
humidity, gives us a higher return. Keeping a good safety factor will help guarantee sugar quality at 
the refinery, and final molasses exhaustion helps to increase sugar output, the better we do our job, 
the easier and more profitable the refining of sugar should be. 

More and more pressure will be put upon us by the federal and state EPA's to keep us as 
environmentally friendly as possible. Up to now, it has been my experience that many environmental 
obligations have increased our efficiency. 

IV. At the top end of our scale is refined sugar production sales and marketing, from which the 
money flows down again in most cases in Florida, right back to the farmer/agriculture. 

Not only do we have to be efficient, we need to be "profitable" in each basic step of the scale by our 
own merits. In the case of the first three basic steps; milling, harvesting, and agriculture, we presently 
have to make this happen between 0. 1 8/0. 19.5a pound of raw sugar, or between $360.00 - $390.00 
FOB mill per ton of raw sugar. Sometimes we get lucky and it's more, but for the sake of present day 
economics, lets leave it at that. Within these parameters, all of our functions have to be paid for and 
provide for a healthy corporate profit. 

These days, the refinery does not have that much of a spread, and depending on whether it 
is bulk, commercial, or retail, I believe it oscillates anywhere between 3 and 9 cents a pound of 
refined sugar over the raw C.I.F. sugar price. The bottom line is that we need to be ever conscious 



of our goals in order to survive. The refining sector will, in all probability, demand a better quality 
of raw sugar from us and we have to get ready to do so on a consistent basis, in the near future. 

There are many other outside pressures that come and will come to bear on us in the future; 
NAFTA, federal, state and local politics, as well as environmental issues. We as technologists must 
become more pro-active in our industry in all aspects, especially in increasing productivity and 
efficiency, which at the end of the day, is our obligation. Also in the political and public relations 
area, I believe that if any of us have good scientific data that can be useful to our public relations 
department, we should let them know it. 

There are many misconceptions continuously expounded in the press against sugar, for 
example, the calorie count in a teaspoon of sugar is only 15, hardly an alarming number by any 
means. The press however, would like you to believe that sugar is one of the evils of life. 

Another is that we are a huge industry when the reality is this: Let's say in Texas, Louisiana, 
and Florida, we produce 4,000,000 tons of raw cane sugar a year, at $390.00 a ton. That's 
$ 1 ,560,000,000.00 total sales in one year. To put that in perspective, this is equal to two weeks sales 
of Albertsons Supermarkets or four days of General Motors sales! 

As you can see, in our country's economy, we are a very small fish in a huge pond, yet the 
perception is that we are exploiting the U.S. taxpayer. We aren't, and by the same token, we provide 
jobs and are responsible for over 40,000 families, pay taxes, and diligently cooperate with the state 
and federal agencies to protect our environment, feed our citizens and care for our nation. 

The message I want to get across today, is that we need to work together within and without 
each sector of our industry, in order to increase our efficiency, productivity, and profitability so our 
children and our children's children can continue this wonderful agri-industry, with over 200 years 
of tradition in the United States. 

This is our challenge; let's make it our opportunity! 



PEER 

REFEREED 

JOURNAL 

ARTICLES 

AGRICULTURAL 
SECTION 



Hall: Laboratory Screening of Insecticides for Preventing Injury by the Wireworm Melanotus Communis (Coleoptera : Elateridae) to 

Germinating Sugarcane 

LABORATORY SCREENING OF INSECTICIDES FOR PREVENTING INJURY BY 
THE WIREWORM MELANOTUS COMMUNIS (COLEOPTERA: ELATERIDAE) TO 

GERMINATING SUGARCANE 

David G. Hall 

Research Department 

United States Sugar Corporation 

P.O. Drawer 1207 

Clewiston, FL 33440 

ABSTRACT 

A laboratory bioassay was investigated for screening insecticides for preventing stand 
losses by the wireworm Melanotus communis (Gyllenhal) to germinating plant cane. For liquid 
materials, single-eye billets were dipped into different concentrations of a candidate insecticide 
and then planted in plastic containers of organic soil; wireworms were then introduced, airtight 
lids were placed onto the contafners, and wireworm survival and damage were assessed 4 wk 
later. Tests with granular materials were similar except the containers were partially filled with 
untreated soil; 30 cc of soil treated with granular material were then added to the container; an 
untreated single-eye billet was placed onto this treated soil; an additional 30 cc of treated soil 
was then placed on and around the billet; and finally untreated soil was added to fill the 
container. Conditions inside the bioassay containers were suitable for germination and early 
growth of most cultivars. The airtight lids were advantageous from the standpoint of 
maintaining soil moisture. 

Among six candidate insecticides studied, bifenthrin 2EC, thiamethoxam 25WG, 
thiamethoxam 2G, and tefluthrin 3G each reduced damage by wireworms to germinating eyes of 
seed cane planted in organic soils. Wireworms frequently survived in containers of seed-pieces 
treated with these materials yet did not damage eyes before germination, indicating the materials 
repelled wireworms. However, germinated shoots of billets treated with these materials were 
sometimes injured by the surviving wireworms. 



INTRODUCTION 

The wireworm Melanotus communis (Gyllenhal) (Coleoptera: Elateridae) is currently the 
single-most important insect pest of sugarcane in Florida based on economic damage potential, 
frequency of infestations, and money spent to prevent damage (Hall 2001). Preventing economic 
losses to M. communis using cultural tactics has historically been difficult particularly in a 
successive-plant situation, and biological control has offered little promise as a management 
tactic (Hall 2001). Two insecticides, ethoprop and phorate, are currently labeled and effective 
for reducing wireworm damage to newly-planted sugarcane. Additional insecticides for 
wireworm control in Florida sugarcane would be desirable, particularly since there is some 
concern that the sugarcane labels for ethoprop and phorate may eventually be cancelled. 

To find new wireworm insecticides, candidate materials can be initially screened for 
efficacy under a laboratory setting and the most promising materials can later be field-tested. 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Initial laboratory screenings of insecticides have traditionally involved topically applying 
technical grade materials directly to insects with subsequent assessments of mortality, the goal 
being to measure the relative toxicity of test compounds (e.g., Hall and Cherry 1985). 
Commercial pesticides available in liquid formulations can be substituted for technical grade 
materials in topical application assays on toxicity. A drawback to topical applications as an 
initial screening bioassay for wireworm pesticides is that such assays give no insight into how a 
material may perform in soil. 

As an alternative to topical applications for initial screening of materials, wireworms can 
be introduced into soil treated with candidate materials (e.g., Cherry 2001). This treated-soil 
approach to screening materials gives insight into the relative toxicity of materials in soil. A 
disadvantage to both topical application and treated-soil assays is that they are biased toward 
finding toxic materials. Some materials might have little or no toxicity to wireworms but could 
still have value as a tool for wireworm control if they repel wireworms or stop wireworms from 
feeding. For example, Villani and Gould (1985) found that extracts from some plant species 
provided significant levels of feeding deterrency by M. communis in tests with treated potatoes. 
To simultaneously study both toxicity and repellency, single-eye sugarcane billets could be 
treated with candidate materials (liquids) and planted into containers of soil, wireworms would 
then be introduced into the containers, and the efficacy of the materials for killing wireworms or 
preventing damage would later be assessed. To screen granular materials, single-eye sugarcane 
billets could be planted in a small pocket of soil treated with a material within a container of 
untreated soil. 

Presented here are the results of laboratory screenings on the efficacy of candidate 
materials for M. communis control in sugarcane using bioassays with single-eye billets planted in 
soil. 

METHODS AND MATERIALS 

The basic assay used to screen candidate materials for preventing wireworm injury to 
germinating cane was as follows. For bioassays involving liquid materials, single-eye billets 
were dipped into different parts-per-million (ppm) concentrations of a material in distilled water; 
allowed to air dry under a fume hood for aproximately 30 minutes; and then planted individually 
into 475 ml plastic containers (Fisherbrand #02-544-126, natural) partially filled with organic 
soil. Additional soil was then added to nearly fill each container; 2 - 3 ml of distilled water were 
pipetted onto the soil; and then an airtight lid was fitted onto each container. Bioassays with 
granular materials were similar except for the following. A bulk quantity (cc) of soil equal to 60 
cc times the number of containers to receive a specific rate of material was calculated; the 
specific rate of material per container was multiplied by the number of containers to receive the 
rate, and the total amount of material needed for all of the containers was mixed into the bulk 
soil sample. Containers were then partially filled with untreated soil; 30cc of treated soil was 
placed into each container; a single-eye billet was placed onto this treated soil; 30cc of additional 
treated soil was placed on and around the billet; and then additional untreated soil was added to 
nearly fill each container. The specific per-container rate of a granular material was therefore 
applied in a total of 60 cc of treated soil per container. Test rates of granular materials were 
based on mg ai (active ingredient) per m 2 and were calculated based on the surface area of soil in 



Hall: Laboratory Screening of Insecticides for Preventing Injury by the Wireworm Melanotus Communis (Coleoptera : Elateridae) to 

Germinating Sugarcane 

a container (9 cm diameter, 63.7 cm 2 surface area). 

After setting up containers for a trial, three field-collected M. communis wireworms were 
introduced onto the soil surface of each container. The lidded containers were then placed either 
into an environmental chamber or onto a lab bench and checked every 1-2 days to determine 
when shoots emerged. When a shoot emerged, the contents of the container were emptied to 
assess wireworm survival and damage to the shoot. The bioassays were terminated after 4 wk, at 
which time each of the remaining containers was emptied to assess wireworm survival, damage 
to non-germinated buds and damage to germinated shoots. A wireworm was considered dead if 
it displayed no movement when prodded. 

Most of the bioassays were conducted using sugarcane cultivar CL77-797, but other 
cultivars were utilized in some assays. Organic soil (55 to 80% organic matter, silica <5%, pH 
7.5-7.9) obtained from sugarcane fields infested by wireworms was used in all trials. The soil 
was stored in sealed plastic bags in an air-conditioned lab until employed for the assays. By 
storing the fresh soil in sealed plastic bags, percentage moisture of the field-collected organic 
soil was maintained (50 to 55% by weight for the soil used in these trials). Prior to using the soil 
in an assay, it was forced through a 4.75 mm sieve to destroy clods and remove unwanted 
material. Wireworms used in the bioassays were collected from sugarcane fields during 
November- January and maintained in plastic boxes containing organic soil and pieces of carrots. 
Lids were placed onto these boxes, but the lidded boxes were not airtight. New carrots were 
placed into the boxes every 2-3 weeks and water was periodically added. The individual 
wireworms used in the assays were mid- to late-instar larvae generally weighing around 50 to 80 
mg. M. communis wireworms in Florida sugarcane during December average 67.7 mg in weight 
(SEM 2.03, n=210) (Hall, unpublished). The bioassays were conducted at 20° to 24°C, as this 
range was representative of temperatures at planting during the fall in Florida. 

Bioassays Without Insecticides 

Two trials were conducted in which no wireworm control materials were tested. One of 
these was conducted during 2000 to evaluate germination of eight different sugarcane cultivars 
planted in the bioassay container (airtight lids, 55 day trial, no wireworms, 22°C, 9/12-11/6). 
Ten single-eye billets of each cultivar were studied, with 5 billets planted with the eye in an up 
position and 5 with the eye in a down position. The number of days from planting until 
emergence was recorded. At the end of the trial, all containers without emerged shoots were 
emptied and whether or not eyes had germinated was determined. Among plants which 
emerged, the average number of days from planting to emergence and percent emergence were 
determined for each cultivar. Also for each cultivar, the percentage of eyes which germinated 
was calculated. ANOVA was conducted to compare cultivars with respect to percent emergence 
and percent germination (percentages log-transformed); the ANOVA was based on two quasi 
replications, one for billets in an up position and one for billets in a down position, and mean 
comparisons were made using Duncan's multiple range test. In the second trial without 
insecticides, damage by wireworms newly-collected from a sugarcane field was compared to 
damage by wireworms which had been maintained in a laboratory for 50-54 wk (airtight lids, 
61-620, billets planted with the eye in a side position, 30 replications per wireworm type, 4 wk 
test, 1 wireworm per container, 22°C). 



10 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Bioassays with Candidate Insecticides for Preventing Damage by Wireworms 

Seven trials were conducted in which six candidate wireworm control materials were 
tested: bifenthrin 2 EC (Capture, 240 g ai/1, FMC), ethipriole 10EC (RPA 107382, 100 g ai/1, 
Aventis), tefluthrin 3G (Force, 3% ai, Zeneca), thiamethoxam 25WG (CGA293343, 25% ai, 
Syngenta), thiamethoxam 2G (CGA293343, 2% ai, Syngenta), and zeta-cypermethrin 0.8 EC 
(Fury, 96 g ai/1, FMC). Several of these compounds were screened simultaneously in some trials 
while other trials involved screening a single compound. The seven trials were conducted as 
follows. 

Trial 1 - Billets dipped in bifenthrin (24,000 ppm) or ethiprole (48,000 ppm), February 2001, 
wireworms collected 2-4 wk before the trial, CL6 1-620, 22°C. 

Trial 2 - Billets dipped in ethiprole (24,000 or 48,000 ppm) or bifenthrin (12,000 or 24,000 
ppm), February 2001, wireworms collected 6-10 wk before the trial, CL6 1-620, 22°C. 

Trial 3 - Billets dipped in bifenthrin (1,500, 3,000 or 6,000 ppm), ethiprole (1,500 or 12,000 
ppm), or thiamethoxam 25 WG (12,000 or 24,000 ppm), April 2001, wireworms collected 11-18 
wk before the trial, CP84-1 198, 22°C. 

Trial 4 - Billets dipped in ethiprole (12,000, 24,000 or 48,000 ppm) or thiamethoxam 25 WG 
(12,000, 24,000 or 48,000 ppm), January 2002, wireworms collected 2-8 wk before the trial, 
CL77-797, 23.7°C (SEM 0.02°C). 

Trial 5 - Billets dipped in zeta-cypermethrin (75, 100 or 125 ppm), March 2002, wireworms 
collected 8-12 wk before the trial, CL77-797, 23.2°C (SEM 0.01°C). 

Trial 6 - Billets planted in a pocket of soil treated with tefluthrin 3G (2.75, 5.5 or 1 1.0 g/m 2 ; 83, 
165 or 330 mg ai/m 2 ), January 2002, wireworms collected 4-6 wk before the trial, CL77-797, 
23.6°C(SEM0.01°C). 

Trial 7 - Billets planted in a pocket of soil treated with thiamethoxam 2G (2.75, 5.5 or 1 1.0 g/m 2 ; 
55, 110 or 220 mg ai/m 2 ), February 2002, wireworms collected 5-11 wk before the trial, CL77- 
797, 23.2°C (SEM 0.02°C). 

Billets were planted with eyes positioned to the side in all trials. Twenty containers were 
tested for each rate of each test material except in trial two, where ten containers were tested for 
each rate of each material. For each trial, the containers of each treatment were randomly 
assigned to one of four replications (5 containers per replication) (exception, trial two consisted 
of only two replications). At the end of each trial, numbers of wireworms surviving, 
percentages of eyes germinated, eyes damaged before germination, and shoots damaged after 
germination were determined. The percentages of plants damaged before and after germination 
were added to obtain a total index of damage per container. ANOVA was conducted for each 
trial (log-transformed data for percentages), and means among treatments were compared using 
Duncan's new multiple range test. 



11 



Hall: Laboratory Screening of Insecticides for Preventing Injury by the Wireworm Melanotus Communis (Coleoptera : Elateridae) to 

Germinating Sugarcane 

RESULTS 

Bioassays Without Insecticides 

Among the eight cultivars tested, percent germination of single-eye billets planted in 
airtight containers ranged from 20 to 100% (Table 1). From 80 to 100% germination occurred 
for six of the cultivars, and 100% germination occurred for three cultivars. Percent germination 
of one cultivar (CP73-1547) was mediocre (60%) and of another (CL78-1600) poor (20%). With 
respect to speed of germination and emergence under the bioassay conditions, CL6 1-620, CP78- 
1628 and CP84-1198 developed the fastest; CL83-4266 and CP80-1743 were slower; and CL77- 
797 and CP73-1547 were slowest. CL78-1600 showed little development over the 55-day 
period. With eyes positioned down, plant emergence was delayed by more than 33 days for 
CL77-797 and by from 17 to 21 days for CL61-620, CL83-4266 and CP80-1743 (Table 2). Less 
of a delay was observed for CP73-1547 and CP79-1628 (with buds positioned down, plant 
emergence was delayed by only about 5 days). In the second trial, wireworms held for 2-3 wk 
before being used in the bioassay damaged 47% of the eyes while wireworms held for 50-54 wk 
damaged 20% of the eyes. 

Bioassays with Candidate Insecticides for Preventing Damage by Wireworms 

Ethiprole (48,000 ppm solution) and bifenthrin (24,000 ppm solution) appeared 
moderately toxic to wireworms in the first trial, each material causing a significant reduction in 
wireworm survival (Table 3). Low percent germination of CL6 1-620 billets dipped into the 
ethiprole treatment indicated the material may have been phytotoxic. Percent germination of 
billets dipped into the bifenthrin treatment was lower than expected but better than under the 
infested-check treatment. Wireworms caused considerable damage to seed under the infested- 
check treatment and some damage to eyes of billets treated with ethiprole, but no damage by 
wireworms occurred to the eyes of billets treated with bifenthrin. Although bifenthrin provided 
good protection of eyes from damage, the treatment did not prevent damage to some germinated 
shoots. 



In the second trial, no significant reductions in numbers of live wireworms occurred in 
containers holding billets treated with 24,000 or 48,000 ppm solutions of ethiprole (Table 3). 
Billets of CL61-620 dipped into a 48,000 ppm solution of ethiprole had significantly poorer 
germination than billets dipped into a 24,000 ppm solution, but germination under the 48,000 
ppm ethiprole treatment was generally better than in the first trial with this variety. A significant 
reduction in numbers of live wireworms occurred in containers holding billets treated with a 
24,000 ppm solution of bifenthrin but not in containers holding billets treated with a 12,000 ppm 
solution. Good levels of germination occurred in containers holding billets treated with 
bifenthrin at each rate. No damage by wireworms was observed to eyes or germinated shoots 
under either bifenthrin treatment regardless of the presence of live wireworms. 






12 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

a 



Table 1. Germination of different cultivars in bioassay. 



Cultivar 


Mean (SEM) days 


Mean 


Mean percent 




to emergence 


percent emergence 


germination 


CL6 1-620 


18.4(4.57) 


70a 


90ab 


CL77-797 


33.3 (4.33) 


30b 


80ab 


CL78-1600 


- 


0c 


20c 


CL83-4266 


25.6 (4.32) 


100a 


100a 


CP73-1547 


29.8 (3.65) 


50ab 


60b 


CP78-1628 


15.6(1.38) 


90a 


100a 


CP80-1743 


24.9 (3.72) 


80a 


100a 


CP84-1198 


18.0(2.51) 


90a 


90ab 



a Means in the same column followed by the same letter are not significantly different (a=0.05), 
Duncan's test. 



Table 2. Germination of different cultivars in bioassay, billets planted with eyes in an up versus 
down position. 



Cultivar 



Eye position 



Mean (SEM) 

days to 

emergence 



Percent 
emergence 



Percent germination 



CL61-620 


Down 


29.3 (6.17) 


60 




Up 


10.3(1.44) 


80 


CL77-797 


Down 


- 







Up 


33.3 (4.33) 


60 


CL78-1600 


Down 


- 







Up 


- 





CL83-4266 


Down 


36.0 (5.39) 


100 




Up 


15.2(0.97) 


100 


CP73-1547 


Down 


32.5 (8.50) 


40 




Up 


28.0 (4.04) 


60 


CP78-1628 


Down 


18.3(1.31) 


80 




Up 


13.4(1.78) 


100 


CP80-1743 


Down 


35.7 (3.76) 


60 




Up 


18.4(2.54) 


100 


CP84-1198 


Down 


23.0 (2.53) 


100 




Up 


11.8(1.89) 


80 


Overall 


Down 


28.5 (2.20) 


55.0 




Up 


17.5(1.58) 


72.5 



80 

100 

80 

80 

20 

20 

100 

100 

40 

80 

100 

100 

100 

100 

100 

80 

77.5 
82.5 



13 



Hall: Laboratory Screening of Insecticides for Preventing Injury by the Wireworm Melanotus Communis (Coleoptera : Elateridae) to 

Germinating Sugarcane 

Table 3. Efficacy of different liquid treatments for preventing wireworm damage under the 
assay conditions. 3 











Mean 


Mean 












plants 


plants 


Mean 






Mean number 


Mean 


killed 


killed 


total 




Rate 


wireworms 


germ. 


before 


after 


stand loss 


Material 


(ppm) 


surviving 


(%) 


germ(%) 


germ(%) 


(%) 


Trial 1: cultivarCL6 1-620 


ethiprole 


48,000 


1.5b 


5.0b 


20.0b 


0.0a 


20.0ab 


bifenthrin 


24,000 


1.3b 


45.0a 


0.0c 


15.0a 


15.0b 


infested check 


- 


2.4a 


10.0b 


70.0a 


5.0a 


75.0a 


Trial 2: cultivar CL6 1-620 














ethiprole 


48,000 


1.9ab 


20.0b 


30.0a 


0.0a 


30.0a 


ethiprole 


24,000 


2.7a 


80.0a 


0.0b 


0.0a 


0.0b 


bifenthrin 


24,000 


1.1b 


90.0a 


0.0b 


0.0a 


0.0b 


bifenthrin 


12,000 


2.1a 


80.0a 


0.0b 


0.0a 


0.0b 


infested check 


- 


2.7a 


60.0a 


30.0a 


20.0a 


50.0a 


non-infested check 


- 


- 


90.0a 


0.0b 


0.0a 


0.0b 


Trial 3: cultivar CP84-1 198 














ethiprole 


12,000 


2.4a 


35.0b 


15.0ab 


5.0b 


20.0ab 


ethiprole 


1,500 


2.3ab 


65.0a 


5.0ab 


lO.Oab 


15.0ab 


bifenthrin 


6,000 


1.5c 


75.0a 


0.0b 


5.0b 


5.0b 


bifenthrin 


3,000 


1.9abc 


55.0ab 


0.0b 


5.0b 


5.0b 


bifenthrin 


1,500 


1.8bc 


80.0a 


0.0b 


5.0b 


5.0b 


thiamethoxam 


24,000 


2.0abc 


70.0a 


0.0b 


0.0b 


0.0b 


thiamethoxam 


12,000 


2.3ab 


65.0a 


5.0ab 


0.0b 


5.0b 


infested check 


- 


2.0abc 


65.0a 


20.0a 


25.0a 


45.0a 


non-infested check 


- 


- 


85.0a 


0.0b 


0.0b 


0.0b 


Trial 4: cultivar CL77-797 














thiamethoxam 


48,000 


2.5b 


70.0a 


0.0c 


0.0a 


O.Od 


thiamethoxam 


24,000 


2.9a 


85.0a 


0.0c 


0.0a 


O.Od 


thiamethoxam 


12,000 


2.8a 


90.0a 


0.0c 


0.0a 


O.Od 


ethiprole 


48,000 


2.8a 


0.0b 


20.0b 


0.0a 


20.0c 


ethiprole 


24,000 


2.8a 


0.0b 


35.0ab 


0.0a 


35.0bc 


ethiprole 


12,000 


2.9a 


0.0b 


40.0a 


0.0a 


40.0ab 


infested check 


- 


3.0a 


5.0b 


75.0a 


5.0a 


80.0a 


non-infested check 


- 


- 


80.0a 


0.0c 


0.0a 


O.Od 


non-infested ethiprole 


24,000 


- 


0.0b 


0.0c 


0.0a 


O.Od 


Trial 5: cultivar CL77-797 














zeta-cypermethrin 


125 


2.9a 


40.0a 


55.0a 


20.0ab 


75.0a 


zeta-cypermethrin 


100 


2.7a 


35.0a 


55.0a 


15.0ab 


70.0a 


zeta-cypermethrin 


75 


2.7a 


60.0a 


30.0b 


lO.Oab 


40.0b 


infested check 


- 


2.8a 


45.0a 


50.0ab 


30.0a 


80.0a 


non-infested check 


- 


- 


90.0a 


0.0c 


0.0b 


0.0c 






a For each trial, means in the same column followed by the same letter are not significantly different 
<a=0.051 Duncan's test. 



14 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

No significant wireworm mortality occurred in containers of billets treated with ethiprole 
at either 1,500 or 12,000 ppm in the third trial (Table 3). With respect to bifenthrin, significant 
wireworm mortality occurred in containers with billets dipped into a 6,000 ppm solution. No 
significant wireworm mortality occurred in containers with billets dipped into thiamethoxam 
25 WG at either 12,000 or 24,000 ppm. Respectable levels of CP84-1198 germination occurred 
under all treatments except 12,000 ppm solutions of ethiprole. A low level of damage to eyes 
was observed under the 12,000 ppm ethiprole treatment, but not enough to account for the 
reduced germination; this rate of ethiprole may have been phytotoxic to CP84-1 198. No damage 
to eyes occurred under any of the three bifenthrin treatments, but some young shoots were killed. 
A low percentage of eyes were damaged among billets dipped into a 12,000 ppm solution of 
thiamethoxam 25WG but not a 24,000 ppm solution. No young shoots were injured under either 
of the thiamethoxam treatments. 

A small but significant reduction in wireworm survival occurred in containers of billets 
dipped into a 48,000 ppm solution of thiamethoxam 25WG in the fourth trial (Table 3). No 
significant mortality of wireworms occurred in containers of billets dipped into 12,000 or 24,000 
ppm solutions of thiamethoxam 25 WG nor into 12,000, 24,000 or 48,000 ppm solutions of 
ethiprole (Table 3). In spite of wireworm survival under the thiamethoxam treatments, good 
levels of germination occurred with no damage to either eyes or young shoots. No germination 
of CL77-797 occurred among billets dipped into the ethiprole treatments. The ethiprole 
treatments did not prevent wireworms from attacking eyes, although the percentages attacked 
were lower than under the infested-check treatment. 

In the fifth trial, no significant wireworm mortality occurred in containers with billets 
treated with zeta-cypermethrin (Table 3). Significant percentages of eyes were damaged by 
wireworms before germination among billets treated with this material, and significant 
percentages of germinated shoots were injured by wireworms in spite of the zeta-cypermethrin 
treatments. For unknown reasons, damage by wireworms in containers of billets treated with 75 
ppm zeta-cypermethrin was generally less than when billets were treated with 100 or 125 ppm. 

No significant wireworm mortality occurred among containers in which billets were 
protected with tefluthrin 3G in the sixth trial (Table 4). A rate of 330 mg ai/m 2 provided good 
protection from wireworm injury to eyes before germination, but rates of 165 or 83 mg ai/m did 
not. Wireworms tended to cause less damage to young shoots in containers treated with these 
rates of tefluthrin than in containers not treated. 

Treating the soil around billets with thiamethoxam 2G at rates of 55, 110 or 220 mg ai/m 2 
resulted in no significant wireworm mortality during the seventh trial (Table 4). However, 
wireworms caused significantly less damage to eyes before germination under these treatments. 
The treatments did not prevent damage to shoots after germination. 

Because ethiprole appeared phytotoxic in a number of trials, especially to CL77-797, a 
separate trial was conducted in which single-eye billets were dipped into five ethiprole solutions 
ranging from 100 to 40,000 ppm (two replications of five containers per ethiprole concentration, 
CL77-797, March 2002). These billets were planted in containers filled with organic soil and 
maintained with an airtight lid for 4 wk (no wireworms were introduced). Good germination of 



15 



Hall: Laboratory Screening of Insecticides for Preventing Injury by the Wireworm Melanotus Communis (Coleoptera : Elateridae) to 

Germinating Sugarcane 

Table 4. Efficacy of different granular treatments for preventing wireworm damage under the 
assay conditions. 1 



Rate 



Mean 

number 

wireworms 



Material 



(mg ai/m ) surviving 



Mean 

percent 

germ. 



Mean 
percent 
plants 
killed 
before 
germ. 



Mean 

percent 

plants 

killed after 

germ. 



Mean 

total 

percent 

stand 

loss 



Trial 6: cultivar CL77-797 



tefluthrin 3G 
tefluthrin 3G 
tefluthrin 3G 
infested check 
non-infested 
check 



330 
165 
83 



2.6a 
2.9a 
2.8a 
2.9a 



30.0a 
50.0a 
20.0a 
20.0a 
70.0a 



10.0b 
25.0a 
45.0a 
65.0a 
0.0c 



0.0a 

5.0a 

0.0a 

15.0a 

0.0a 



10.0b 
30.0a 
45.0a 
80.0a 
0.0c 



Trial 7: cultivar CL77-797 



thiamethoxam 2G 
thiamethoxam 2G 
thiamethoxam 2G 
infested check 
non-infested 
check 



220 
110 
55 



3.0a 


75.0a 


0.0b 


3.0a 


80.0a 


15.0b 


2.9a 


70.0ab 


20.0b 


2.8a 


35.0b 


65.0a 


- 


85.0a 


0.0b 



15.0a 


15.0bc 


25.0a 


40.0ab 


25.0a 


45.0ab 


20.0a 


85.0a 


0.0a 


0.0c 



For each trial, means in the same column followed by the same letter are not significantly 
different (a=0.05), Duncan's test. 



root primordia and eyes occurred on billets dipped into solutions of 1,000 ppm or less but not at 
higher doses (Table 5). 



Table 5. Germination of single-eye billets treated with ethiprole and planted in organic soil with 
airtight plastic containers, 23.2°C (SEM 0.01). a 





Seed pieces with 




Ethiprole 


germinated root 




concentration 


primordia 


Germination of buds 


(ppm) 


(%) 


(%) 





100.0a 


100.0a 


100 


100.0a 


100.0a 


1,000 


100.0a 


90.0a 


10,000 


10.0b 


0.0b 


20,000 


0.0b 


0.0b 


40,000 


0.0b 


0.0b 



a Means in the same column followed by the same letter are not significantly different (a=0.05), 
Duncan's test. 



16 



TA. 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

DISCUSSION 

The bioassay was a relatively easy approach for evaluating candidate materials for 
wireworm control. Airtight lids were advantageous from the standpoint of maintaining soil 
moisture. However, it remained possible that the efficacy of a material for wireworm control 
might appear different using an assay without airtight lids because air exchange could affect 
factors such as the persistence of insecticide odor. The assay could be conducted without lids, in 
which case water would have to periodically be added to each container. To determine how 
much water to add, a baseline initial weight could be determined for each container after it is set 
up, and then enough water to restore a container's weight back to the initial level could 
periodically be added to compensate for loss of soil moisture. A study comparing lidded versus 
non-lidded containers would be worthwhile. Soil moisture levels near 50% were suitable for 
wireworms in the particular organic soil used in the assays. In soils with lower than 50-60% 
organic matter, lower soil moisture levels by weight would be needed, with the particular 
moisture level being dependent upon suitability for wireworms. 

The speed of germination of some cultivars is inherently slower than others. Most 
cultivars germinated normally under the bioassay conditions, but it is possible that some cultivars 
could perform better under the assay conditions than others. Based on the differences observed 
among the eight cultivars with respect to speed of germination and development, some cultivars 
may be better suited than others for a bioassay aimed at screening for materials to reduce stand 
losses by wireworms. For example, a cultivar intermediate or slow in germination rate may be 
advantageous with respect to giving wireworms ample time to attack a billet. As intuitively 
expected, plants emerged faster when billets were planted with eyes in an up position. 

The data indicated it may be disadvantageous to hold M. communis for a long period of 
time before screening a material for wireworm control because a reduction in wireworm damage 
may be mistaken as control. If wireworms stored for a long time had to be used in an assay, 
greater numbers of wireworms could be introduced per billet. M. communis is thought to have 
one annual generation in southern Florida, with most wireworms pupating during early to mid 
spring (e.g., late March to early May). Wireworms are relatively easy to collect from cane 
stubble soon after harvest during late October - March. When wireworms are collected during 
the winter and maintained in containers of soil with carrots as a food source on a laboratory 
bench, few wireworms pupate even if they are held for more than a year. It is possible such 
wireworms may feed less because they have completed development and are simply waiting for 
environmental cues to pupate. If so, it may be disadvantageous to utilize wireworms collected 
during October- January after around the following March. 

Relatively little wireworm mortality occurred in most of the trials regardless of which 
insecticide was tested, yet little damage to eyes prior to germination often occurred. Wireworms 
in containers with billets not treated with insecticides usually caused substantial injury. 
Therefore, wireworms in containers with treated billets may have simply avoided the billets due 
to repellency of the insecticides (e.g., odor or other characteristics which deterred feeding). 
Insecticides may vary in both toxicity and repellency (Silverman and Liang 1999). Working 
with M. communis in North Carolina, Villani and Gould (1985) found that five extracts from four 
plant families significantly reduced wireworm feeding damage to potato. It is possible that a 



17 



Hall: Laboratory Screening of Insecticides for Preventing Injury by the Wireworm Melanotus Communis (Coleoptera : Elateridae) to 

Germinating Sugarcane 

nontoxic material which repels wireworms from germinating eyes of sugarcane could be useful 
for reducing damage before germination, but developing shoots might still be subject to attack. 

At the rates studied, bifenthrin, thiamethoxam 25WG, thiamethoxam 2G, and tefluthrin 
3G each appeared to have value as materials for reducing damage by wireworms to germinating 
eyes of seed cane planted in organic soils. However, germinated shoots of billets treated with 
these materials were sometimes injured by wireworms, usually some distance away from the 
billet itself. Some seed-piece treatments may protect eyes from wireworm injury during 
germination but not young shoots. Overall, the most promising material based on these limited 
data appeared to be thiamethoxam 25WG with respect to reducing damage to both germinating 
eyes and young shoots. Ethiprole was phytotoxic to CL77-797, at least at concentrations above 
1,000 ppm, and may have been somewhat phytotoxic to CL61-620 and CP84-1 198. A granular 
formulation of ethiprole might be less toxic to cultivars such as CL77-797. Little wireworm 
mortality occurred in containers of billets treated with ethiprole at any rate, but surviving 
wireworms frequently caused injury to the billets. Zeta-cypermethrin appeared to have little 
value as a wireworm control material at the rates studied, which were comparatively much 
smaller than the rates tested of the other liquid materials. Higher rates of zeta-cypermethrin 
might be more effective. 

Since the Florida sugar industry currently uses granular formulations of either ethoprop 
20G or phorate 20G for wireworm control, alternative pesticides in granular formulations would 
be more convenient substitutes than liquid pesticides. The recommended application rate of 
phorate 20G, 1 kg per 300 row meters, equates to approximately 10.9 g product/m or 2.2 g ai/m 
when applied in a 30-cm band. The recommended application rate of ethoprop 20G, 0.6 to 1.3 
kg per 300 row meters, equates to 6.8 to 13.7 g per m or 1.4 to 2.7 g ai/m 2 when applied in a 30- 
cm band. With respect to g ai/m 2 , my test rates of thiamethoxam 2G (0.055 to 0.220 g ai/m 2 ) and 
tefluthrin 3G (0.083 to 0.330 g ai/m 2 ) were much lower than the recommended rates of phorate 
20G and ethoprop 20G; higher rates of the two candidate alternatives might have been more 
effective for killing wireworms in organic soil. Other granular pesticides which could be 
investigated for wireworm control include Deltagard 0.1 %G, Talstar PL-GR (0.2%) and Aztec 
2.1%G (Cherry 2001). The Florida industry could consider liquid alternatives to ethoprop 20G 
and phorate 20G. Ethoprop EC (6 lb per gal) was once registered for wireworm control in 
Florida sugarcane, with recommended application rates of 100 to 250 g ai/300 row meters (at 
spray volumes of 4 to 6 1 per 300 row meters, solutions of around 15,000 to 60,000 ppm). 

The bioassay could be standardized using initial screening rates of 100, 1,000, 10,000 and 
50,000 ppm solutions of liquid materials, or rates of 100, 1,000, 2,000 and 4,000 mg ai/m 2 for 
granular materials, with 20 containers per rate and 3 wireworms per container. Larger numbers 
of containers per rate would be advantageous for statistical comparisons. 

ACKNOWLEDGMENTS 

Sherry Little (Research Department, United States Sugar Corporation) provided 
invaluable assistance throughout these experiments. The materials studied were graciously 
provided by H. Gary Hancock (FMC Corporation), Jairo Melgarejo (Aventis), Henry Yonce 
(Zeneca) and John Taylor (Syngenta). 



18 






Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

REFERENCES 

1. Cherry, R. H. 2001. Efficacy of soil insecticides for wireworm control in Florida 
sugarcane. J. American Soc. Sugar Cane Technol. 21: 151-152. 

2. Hall, D. G. 2001. The wireworm problem in Florida sugarcane. Proc. Int. Soc. Sugar Cane 
Technol. 24 (2): 378-381. 

3. Hall, D. G. and R. H. Cherry. 1985. Contact toxicities of eight insecticides to the 
wireworm Melanotus communis (Coleoptera: Elateridae). Fla. Entomol. 68: 350-352. 

4. Silverman, J. and D. Liang. 1999. Effect of fipronil on bait formulation-based aversion in 
the German cockroach (Dictyoptera: Blattellidae). J. Econ. Entomol. 92: 886-889. 

5. Villani, M. and F. Gould. 1985. Screening of crude plant extracts as feeding deterrents of 
the wireworm Melanotus communis. Entomol. Exp. Appl. 37: 69-75. 



19 



Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

EARLY GENERATION SELECTION OF SUGARCANE FAMILIES AND CLONES IN 

AUSTRALIA: A REVIEW 

Collins A. Kimbeng 

Department of Agronomy 

Louisiana Agricultural Experiment Station, LSU Ag Center 

Baton Rouge, Louisiana 70803 

USA 

and 

Mike C. Cox 

Bureau of Sugar Experiment Stations 

PO Box 651 

Bundaberg, Queensland 4670 

Australia 

ABSTRACT 

Sugarcane breeding programs typically commence by evaluating a large number of 
seedlings derived from true seed. Individual clone (mass) selection applied at this stage of the 
program has been shown to be inefficient because of lack of replication and the associated 
confounding effects of the environment. In Australia, the introduction of mobile weighing 
machines made it possible to implement family selection. Several research projects 
demonstrated that family selection, when followed by individual clone selection, was superior in 
terms of genetic gain and more cost effective than either family or individual clone selection 
alone. This combination of family and individual clone selection is now used routinely in all the 
Australian programs. Families are evaluated using replicated plots for cane yield (mechanically 
harvested and weighed) and sucrose content in the plant crop. Individual clones are selected, 
based mainly on visual appraisal for cane yield, from selected families in the first ratoon crop. 
Family selection is usually liberal with about 30 - 40 % of families selected. More clones are 
selected from the best families with progressively fewer clones being selected from the moderate 
to average families. The availability of objective family data makes it possible to estimate the 
breeding value of parents using the Best Linear Unbiased Predictors (BLUP). This information 
is used to retain or drop parents from the crossing program and to plan better cross combinations. 

Approved for publication by the Director of the Louisiana Agricultural Experiment Station as 
manuscript number 02-14-0563. 

INTRODUCTION 

Although sugarcane is grown commercially as a clone, sugarcane breeding programs 
typically commence by evaluating large numbers of seedlings derived from true seed. Sugarcane 
breeders have traditionally employed intensive selection of individual seedlings or seedling 
bunches to select clones at this stage. Selection is usually subjective, based on visual appraisal 
for cane yield. Some programs also consider sucrose content, which is indirectly measured as 



20 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Brix (% soluble solids w/w in the juice) using a hand-held refractometer, in their selection 
criteria. Although satisfactory gains have been achieved using individual seedling selection, it is 
not efficient (Hogarth et al., 1997; Skinner, 1971). The lack of replications, competition effects 
among seedlings and, because individual clone selection is labor intensive and expensive, all 
contribute to reduce selection efficiency. 

Research in Australia revealed that family selection would be superior to individual 
seedling selection at this stage (Hogarth, 1971). Family selection is particularly useful for traits 
with low heritability because, unlike clones, families can be replicated across years and sites, 
thereby improving estimates of family means as well as aiding in the identification of stable 
families (Jackson and McRae, 1998; Falconer and Mackay, 1996). Because sugarcane is 
exploited commercially as a clone, the rationale for family selection is not to produce superior 
families with commercial value but rather to identify families with a higher frequency of superior 
clones. Family selection makes it possible to focus selection for superior clones (individual 
clone selection) on the best families, because the probability of finding superior clones at later 
stages of the program is highest within these families (Cox and Hogarth, 1993). An added 
advantage of family selection in sugarcane is that family data can be used to infer the breeding 
value of parents based on progeny performance (Balzarini, 2000; Cox and Stringer, 1998; 
Stringer et al., 1996; Chang and Milligan, 1992a, b). 

In the 1970s, families still had to be cut and weighed manually; therefore, the cost of 
implementing family selection was prohibitive at the time. With the development of mobile 
weighing machines in Australia, it became possible to investigate the advantages of family 
selection in more detailed experiments and under different geographical and environmental 
conditions (Hogarth and Mullins, 1989). Following results from these experiments, the 
Australian programs were redesigned to include family selection at this early (seedling) stage 
(Cox and Hogarth, 1993; Hogarth and Mullins, 1989). In this report, we share some of our 
experiences with family selection in Australia. We briefly review some of the experiments that 
led to the redesign of the Australian programs and further examine the impact of family selection 
on other aspects of the selection program. In particular, we reveal how family selection has 
contributed positively to the selection of parents and crosses and to population improvement. In 
this paper, as in other sugarcane breeding papers, the phrase family selection is used in some 
instances as an all encompassing one to describe the selection of families and clones within 
families. 

Family selection in Australia 

Sugarcane growing regions and family selection experiments 

In Australia, sugarcane is cultivated over a 2100 km stretch from northern New South 
Wales (approximately 30°S) to northern Queensland (approximately 17°S), with the actual 
hectarage spread unevenly across this distance (Figure 1). Additional hectarage is emerging in 
the Ord river basin. The Bureau of Sugar Experiment Stations (BSES) operates five separate 
sugarcane selection programs in Australia, which are separated into regions by latitude (Hogarth 
and Mullins, 1989) and are strategically located in the major sugarcane-growing regions. Each 
selection program operates independently, but family selection is a common feature in the early 



21 



Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

stages of all the programs (Table 1). The number of seedlings and clones planted and selected at 
each stage, varies in the different programs. 

Several family selection experiments have been carried out under different geographical 
and environmental conditions in Australia (Jackson et al., 1995a, b; McRae and Jackson, 1995; 
McRae et al., 1993; Cox et al., 1996; Hogarth et al., 1990; Hogarth, 1971). But, the best set of 
experiments to use in illustrating the benefits of family selection was carried out in the Burdekin 
region (Ayr, Figure 1) where the growing conditions have been described as unfavorable to 
selection (Jackson et al., 1992; Pollock, 1982). In this region, sugarcane is grown under 
irrigation, which results in large and frequently lodged crops. Because individual clone selection 
is impractical under such conditions, the practice was to restrict crop growth by minimizing 
irrigation and fertilizers to prevent lodging and enable individual clone selection. However, 
because the crop growth potential was not realized under such conditions, this probably had a 
negative impact on selection response because visual estimation of cane yield was poorly 
correlated with actual cane yield in heavily lodged crops (Jackson et al., 1992; Pollock, 1982). 
Indeed, in an experiment conducted by Hogarth et al. (1990), neither family selection nor mass 
selection was effective under conditions that restricted crop growth. The selection conditions 
(environments) were probably atypical of the target environment. Furthermore, under conditions 
of restricted crop growth, misleading information on family performance would probably lead to 
inappropriate parents being selected for crossing, thereby, impeding future selection progress 
(Kimbeng et al., 2000). 

An experiment was conducted in which lodging was experienced as a result of letting it 
grow to its full potential (Kimbeng et al., 2000). One hundred full-sib families were evaluated in 
single-row plots, replicated four times with 20 seedlings per family plot. Family plot data were 
collected in the lodged plant crop using mobile weighing machines as described for a Stage 1 
trial (see Table 1). In the young first ratoon crop, prior to lodging, three clones were visually 
selected, and another three clones were taken at random from each family plot. These clones 
were each planted to a single-row, 1 0-m plot in a split-plot arrangement and replicated into four 
randomized complete blocks. Whole plots were assigned to families and sub-plots to selection 
methods (random vs. selected) for a total of six clones per plot. First clonal stage data were 
collected in the plant and first ratoon crops as described for a Stage 2 trial (Table 1). 

Figure 2 shows the percentage of elite clones (clones with Net Merit Grades, NMG > 
9.0; see Table 1 for description of NMG) in Stage 2 with respect to the selection strategy used in 
Stage 1 for the top 40% of families. Essentially, the results showed that family selection could 
be effective even under lodged conditions. This is evident from the performance among random 
clones, which was generally higher among the top NMG families and decreased progressively 
in the poorer NMG families. Visual selection in the young first ratoon crop was also effective 
in identifying elite clones within families, as evident from Figure 2 and the significant effect of 
selection method (random vs. selected, ldf) in the ANOVA (data not shown). Also, the 
effectiveness of visual selection was consistent across families as indicated by the lack of 
significant family by selection method interaction in the ANOVA (data not shown). Family 
selection in the plant crop followed by individual clone selection in the first ratoon crop was 
superior to either family or individual clone selection. Similar results were found in a 
simulation study that modeled family by environment interactions, genotypic correlations 



22 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

between the selected trait and sugar yield, among family variance, total variance and cost of 
selection (Jackson et al., 1995b). The authors reported superior genetic gain and cost 
effectiveness for combined family and individual clone selection compared to either family or 
individual clone selection in most cases. Family selection was also superior to individual clone 
selection in most cases. Individual clone selection was superior only in cases where there was 
both a small proportion of among-family variance and a high genetic correlation between the 
selected trait and sugar yield. 

Any form of family selection, however, would have to be liberal because some clones 
have been found to perform better than expected on the basis of their family performance in 
seedling trials (Kimbeng et al., 2000; Hogarth et al., 1990). Furthermore, although an overall 
increase in family mean is desirable, the ultimate goal for sugarcane breeders is to select the 
best-yielding clone(s). Cox et al. (1996) suggested that only the top 30 to 40% of families be 
targeted for routine individual clone selection. He contends that after intentionally selecting 
clones from the moderate NMG families (50-70 %) for a number of years, not a single clone 
from this category progressed to the advanced stages (Cox, Personal Communication). 
Kimbeng et al. (2000) also found the highest percentage of elite clones within the top 30 to 40% 
of families (and see Figure 2). Kimbeng et al. (2001a, b; 2000), however, found evidence that 
elite clones could be selected from the moderate to low NMG families. They found some 
outstanding clones among moderate NMG families, especially those that had high CCS but low 
TCH and vice versa. According to Kimbeng et al. (2001b), the time required to select 
individual clones from these relatively poor families should not be a limiting factor in a field 
operation, because these plots can be predetermined using the plant crop family data. In central 
Queensland, each row is harvested immediately after individual clone selection, giving the 
selecting crew equal access to all rows and clones during selection. 

A major practical benefit of family selection is that it allows genetic material to be 
evaluated across locations and years, which aids in the identification of stable families (Jackson 
and McRae, 1998). This is particularly useful in situations where family by environment 
interaction is important. In the Burdekin region (Ayr, Figure 1), McRae and Jackson (1995) did 
not find significant interactions between family and any of the environmental factors, namely 
soil types, management practices and crop cycle that they evaluated. Based on these findings, in 
this region, families are evaluated only in the plant crop and at one location (the breeding station) 
as described in Table 1. Significant family by environment interactions were found in the 
Herbert region (Ingham, Figure 1) (Jackson et al., 1994). However, Jackson et al. (1995a) and 
Jackson and Galvez (1996) later found that soil nutrient status was the principal cause of the 
interactions. Soil nutrient status is a predictable and repeatable source of genotype by 
environment interaction (Allard and Bradshaw, 1964) that was easily corrected. In southern 
Queensland, Bull et al. (1992) reported significant family by location interaction. When 
resources are not a constraining factor, families are evaluated at more than one location in this 
region. 

Competition among seedlings in a plot can affect selection response adversely if the 
appropriate intra-row spacing between seedlings is not used. Research under Louisiana growing 
conditions showed that genetic response was larger at a wider intra-row spacing of 82 cm 
compared to a narrower spacing of 41 cm (De Sousa-Vieira and Milligan, 1999). Intra-row 



23 






Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

spacing varies among the Australian programs and is probably influenced by land availability 
and the size of the crop. For example, an intra-row spacing of 50 cm is used in central 
Queensland (Mackay, Figure 1), but in the Burdekin (Ayr, Figure 1), where they have access to 
irrigation and tend to grow bigger crops, the spacing is 60 cm. 

Appraisal of family selection using data generated from routine selection activities 

Any crop improvement program needs to be constantly monitored to ensure that the 
breeding and selection methods are operating at optimal levels. Retrospective analyses using 
data generated from routine selection activities can be particularly helpful in this effort because 
these data serve as footprints of the program's activities. Cox and Stringer (1998) analyzed the 
efficacy of early generation selection for the southern Queensland program (Bundaberg, Figure 
1) using data from the selection database. In this analysis, all the clones that were advanced to 
Stage 3, based on their performance in Stage 2, were categorized according to the families from 
which they were derived in Stage 1 (see Table 1 for a detailed explanation of Stages). The 
results showed that selection rates for clones derived from Stage 1 families were low (3.8 %) for 
low NMG families (< 10), were similar for families with NMG 10 to < 13 (6.9% - 7.6%) and 
were quite high for the highest NMG category (13.6 %) (Table 2). It appears, during selection of 
clones in the first ratoon crop, selection intensity, which is normally higher for the poorer NMG 
families, more than compensated for the poor family performance. This explains the similar 
selection rates of clones from Stage 2 to Stage 3 for families with NMG 10 to < 13 (6.9% - 
7.6%). Thus, selection intensity can be a major driving force to increase genetic gain. The 
authors suggested that genetic gain could be improved by planting larger numbers of clones (in 
extra plots) of the better families and increasing individual selection intensity for these families. 
In this case, the extra plots would be selected in the plant crop without having to wait for more 
data. This strategy combines the strengths of the family selection and proven cross methods. 

An analysis similar to that of Cox and Stringer (1998) was performed for the central 
Queensland program (Mackay, Figure 1) using a much larger data set (Kimbeng et al., 2001a). 
The results, with respect to selection among families, were similar to those reported by Cox and 
Stringer (1998); selection rates were higher for the top NMG families and comparatively lower 
for the poor NMG families. However, a bias with this type of analysis is that the high NMG 
families were originally represented by more clones in Stage 2 compared to the poor NMG 
families. Therefore, no conclusion could be drawn with respect to the selection of clones within 
families. In an attempt to overcome this bias, Kimbeng et al. (2001a) divided the selection rate 
(Stage 2 to 3) by the percent of clones evaluated in Stage 2 for each NMG category. In this 
analysis, the selection rate was taken to represent the realized response and the percent of clones 
evaluated in Stage 2 represented the potential response. The results from this analysis revealed 
that although family selection was effective in identifying those families that harbor a greater 
proportion of elite clones, selection of clones within families was not efficient, especially for the 
high NMG families. Kimbeng et al. (2001a) observed that in central Queensland, the top NMG 
families did not undergo the strict appraisal process used for the lower NMG families and as a 
result more clones are advanced than is actually necessary. More clones are usually earmarked 
for selection from the high NMG families. Because the NMG formula awards a bonus for high 
sucrose content, there is a tendency not to Brix clones within the top NMG families because of 
the perception that most of the clones are high in sucrose content. The reverse is true for the low 
NMG families, where almost every clone is subjected to a Brix test before selecting a few. The 



24 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

analysis, unfortunately, could not accurately account for what happened in the average to poor 
families. These families had either been discarded or had already undergone very stringent 
selection. The breeder could be discarding potential clones if the selection intensity applied to 
these families is more intense than necessary. Although differential selection rates are used 
within families, whereby more clones are selected out of the best families (top 10 %), with 
progressively fewer clones being selected from the 20 to 40% of families, the number of clones 
selected from these families is currently not based on any objective data. Based on the available 
resources, only a finite number of clones can be evaluated in Stage 2 trials and, for family 
selection to be efficient, selection of clones within families would have to be optimized. In 
central Queensland, the resources allocated to Stage 2 trials can accommodate only about 10% of 
clones from Stage 1 . 

Simulated selection to optimize family selection 

An experiment was carried out in central Queensland (Mackay, Figure 1) to investigate 
optimum selection intensities for family and individual clone selection (Kimbeng et al., 2001b). 
In this experiment, families (replicated family plots) and random clones within each family plot 
were assessed for various characteristics, including cane yield, sucrose content, visual grade and 
Brix in the plant crop of a Stage 1 trial (see Table 1 for explanation of a Stage 1 trial). These 
clones were evaluated in Stage 2 (first clonal stage) in the plant and first ratoon crops. Response 
to selection in Stage 1 was judged on the performance of corresponding clones in Stage 2. The 
main objective was to simulate optimum rates of combined family and individual clone selection 
in Stage 1 . The simulations to determine optimum rates of combined family and individual clone 
selection in Stage 1 were performed using Microsoft Access Relational Database. 

The results confirmed that while family selection was effective in identifying families 
with a high proportion of elite clones, it was more efficient when combined with visual selection 
(Table 3). The efficiency improved further when clones with good visual grade were subjected 
to a Brix test. Most of the efficiency arose from the fact that inferior clones were rejected on the 
basis of visual grade and Brix, and considerably fewer clones were evaluated in Stage 2. Given 
that only 10% of clones from Stage 1 can be accommodated in Stage 2 trials, this would 
represent about 240 clones in this study (Table 3). 

Enforcing a strict selection for Brix led to the loss of a considerable number of elite 
clones. But, when the cut-off point for Brix was allowed to vary, depending on the visual grade, 
(for example a clone with low Brix is accepted when the visual grade is high), the number of 
elite clones that would have been discarded dropped dramatically, but one would have had to 
increase the number of clones evaluated in Stage 2. In practice, the decision to accept or reject a 
clone based on visual grade is much easier to make since that decision always equals to a yes 
(acceptable) or no (unacceptable) answer. Based on the results from the simulations, individual 
clone selection rates of 40, 30, 25 and 10% were optimum for families selection rates of 10, 20, 
30 and 40%, respectively, when selecting families (based on NMG) in the plant crop and clones 
(based on visual appraisal) in the first ratoon crop. Individual clone selection based on Brix was 
best determined by taking into consideration the visual grade of the clone. These selection rates 
should be applied with some caution because they probably depend on the germplasm base and, 
as such, may differ in other programs. In Louisiana, for example, the best outcome was achieved 
with 75% family and 13% within- family selection, and the author contends that this was only 
slightly more efficient than mass selection (Zaunbrecher, 1995). The author attributed this to the 



25 



Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

narrow genetic diversity or low among-family variance (1 1%) in the Louisiana program. During 
the study period, only about 80 parents were used to make an average of about 300 biparental 
crosses in Louisiana, compared to 800 -1000 parents used to make about 2,500 crosses in 
Australia each year. The number of parents used in the Louisiana crossing program has 
increased to about 160, largely because of increased efficiency of floral initiation using the 
photoperiod facility. 

Impact of family selection on other aspects of the breeding program 

Selection of parents, crosses and population improvement 

A selection cycle in sugarcane usually involves a sequence of about four to six stages 
(Skinner et al., 1987). A selection cycle typically takes about 12-15 years to complete. The first 
stage is the only stage, after hybridization, to be planted with true seed. Subsequent stages are 
planted using vegetative propagation, and progressively fewer clones are selected and evaluated 
in the more advanced stages. During this 12 to 15 year period, no opportunities exist for sexual 
recombination or the creation of new genetic variation that the breeder can exploit. The breeder 
has to rely on the initial variation created during hybridization. Research that can predict the 
outcome of a cross would help the breeder to concentrate effort on the most profitable crosses, 
which in turn would substantially increase the chances of selecting elite clones. The selection of 
genotypes to use as parents, or crosses to plant, is one of the most critical decisions the sugarcane 
breeder has to make. 

At the BSES, Hogarth and Skinner (1986) developed an algorithm for assessing the 
breeding value of parental clones that combined breeding information, agronomic data and 
disease ratings into a single index. The breeding information relied heavily on the percent of 
clones from a cross that are advanced to later stages. Crosses with high advancement rates 
(proven crosses), were usually replanted to large numbers of progenies, unduly increasing their 
odds of producing advanced clones to the detriment of experimental crosses. Furthermore, 
although the agronomic data and disease ratings combined information from both the parent and 
progenies, the method required several years to reliably estimate breeding value, and it is now 
known that individual clone selection in the early stages was not efficient. 

BSES breeders recognized the limitations of this empirical approach and sought more 
efficient methods of estimating breeding value. But this effort was hampered by the lack of 
objective data on family or clonal performance, as early stage data were based on indirect 
measurements; that is, visual assessment to estimate cane yield and Brix to estimate sucrose 
content. Therefore, the availability of objective family data on both cane yield and sucrose 
content presented a unique opportunity to apply statistical approaches to the problem. However, 
the highly unbalanced nature of data sets generated from routine progeny evaluation trials 
precluded the use of statistical methods such as factorial (or North Carolina design II) (Comstock 
et al., 1949, Comstock and Robinson, 1948) and Diallel (Griffing, 1956; Hayman, 1954) mating 
designs. 

The Best Linear Unbiased Predictor (BLUP), which was developed to estimate breeding 
value in animal breeding (Henderson 1975), can handle large, highly unbalanced data sets such 
as those generated in routine sugarcane progeny evaluation trials. The BLUP allows data from a 
diverse range of mating designs, relatives, and precisions to be combined into a single breeding 



26 



Jl 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

value for each trait and genotype (Balzarini, 2000). Chang and Milligan (1992a, 1992b) were the 
first to report that the BLUP was reliable in predicting the potential of a cross to produce elite 
progeny in sugarcane. They also found that the potential of a cross to produce elite progeny 
could be accurately predicted from the cross mean of that trait, and the cross mean was more 
readily obtained than the BLUP (Chang and Milligan, 1992b). These latter results were obtained 
using a balanced data set and were restricted to one stage of the breeding program. The real 
advantage of the BLUP over other statistical methods arises when highly unbalanced data sets, 
such as those generated from routine sugarcane selection trials, are analyzed across different 
stages of the program and include information about relatives (Balzarini, 2000; Stringer et al., 
1996). 

Using routine family appraisal data from the southern Queensland (Bundaburg, Figure 1) 
breeding program, Stringer et al. (1996) and Cox and Stringer (1998) compared the utility of the 
BLUP with that of an empirical method (Hogarth and Skinner, 1986) in predicting cross 
performance. The predictions were made by correlating the mean BLUP values obtained using 
data accumulated over several years up to a certain year, with the actual family mean values 
obtained in the following year. In other words, family mean plant crop data, in say 1995, were 
correlated with the corresponding mean BLUP values estimated using family data accumulated 
from, say 1992-1994. The empirical values were derived from at least ten years of data. These 
results showed that the BLUP method was superior to the empirical method in predicting cross 
performance (Table 4). Generally, the BLUP method requires less information (at least 1 year) 
compared to the empirical method (at least 10 years) and its power to predict cross performance 
increases as more data become available and is expected to increase even further when 
information on relatives is included in the model (Stringer et al., 1996). The robustness of the 
BLUP estimates depends largely on the availability of objective family appraisal data, albeit 
highly unbalanced. 

Encouraged by the high predictive power of the BLUP analytical method, BSES breeders 
began to change their philosophy with respect to choice of parents and crosses. The BLUP was 
increasingly used to select parents and crosses, and to design new crosses. This led to a gradual 
increase in crosses involving newer parents. Use of historical parents began to decline, even 
when they were involved in 'proven crosses' (Cox and Hogarth, 1993). The new philosophy 
sought to achieve a much-needed balance between the short-term goals of producing elite 
sugarcane clones with the long-term need to continuously improve the base population. These 
issues needed to be considered simultaneously, because the repetitious nature of breeding for 
short-term needs was unlikely to provide the best results to accomplish long-term goals. For 
example, the hitherto strong emphasis on proven crosses in the BSES breeding program served 
the short-term need of producing elite varieties. However, it hampered efforts to broaden the 
genetic base of the breeding population, because only limited chances were available to evaluate 
experimental parents and crosses. Furthermore, it is well known among sugarcane breeders that 
the genetic base of cultivated sugarcane is very narrow, so concerted efforts had to be made to 
broaden the base population (Berding and Roach, 1987; Mangelsdorf, 1983). 

Population improvement and base broadening efforts at the BSES encompass the rapid 
introduction of superior clones from advanced stages of the selection program as well as superior 
germplasm from exotic crosses, and international and national programs (inter-station exchange), 



27 



Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

into the crossing program (Cox and Hogarth, 1993). In other instances, population improvement 
involved recurrent selection for specific traits, for example high early sucrose content (Cox et al., 
1994; Cox et al., 1990) to provide suitable parents for the variety development crossing program. 
The availability of sound, objective data on family performance coupled with robust estimates of 
the BLUP, are crucial to the success of population improvement efforts. 

The implementation of this new effort was assessed for the southern BSES program by 
evaluating the relative performance of families derived from crossing new versus old parents. 
The analysis used four years of routine family appraisal data in which parents were arbitrarily 
categorized as old (O), medium (M), or new (N) if the seedling parent had a year prefix < 65, 65- 
74, or > 74, respectively (Cox and Hogarth, 1993). The crosses were designated OxO, OxM, 
OxN, MxM, MxN, or NxN (Table 5). Although the small sample size of the NxN crosses 
precluded a reasonable assessment of this group of crosses, the overall results point to the 
inferior performance of old parents compared to the relatively new ones. Old parents performed 
poorly even when used in combination with relatively new parents, compared to crosses between 
relatively new parents. These results justify the continuous use and rapid recycling of parents in 
the breeding program. Again, data accumulated from family evaluation trials are crucial to the 
successful implementation of this policy. 

Apart from evaluating parental performance, the population from which families and 
clones are selected (Stage 1, see Table 1) and the population of clones immediately following 
family and clonal selection (Stage 2, see Table 2) are also constantly monitored. This is to 
ensure that these populations are not adversely affected as a result of adopting family selection 
measures (for example, the BLUPs to select parents; the rapid recycling of newer parents 
including overseas clones). The performance of seedling populations (Stage 1) from 1993 to 
2000 in southern Queensland depicts an overall gradual improvement in NMG at the rate of 0.02 
units per year. Cane yield was a major driving force of this improvement [TCH = 0.02Year + 
0.58; R 2 = 0.70], compared to sucrose content [CCS = -0.002Year + 0.93; R 2 = 0.03]. 
Heritability, estimated on an entry-mean basis using replicated family plots (Stage 1), was higher 
for cane yield, 64%, compared to sucrose content, 48% (Kimbeng and McRae, 1999). Cane 
yield may, therefore, be more influential in determining among-family differences in seedling 
populations (Stage 1 trials) compared to sucrose content. 

Within the same period, the NMG of clones (Stage 2) immediately following family and 
clonal selection improved on average by 1.58 units per year (Figure 4). The NMG of the top 
10% of the mean, which constitutes most of the clones advanced to the next stage, improved on 
average by 2.02 units per year. Contrary to the seedlings, population improvement in the clones 
was driven more by improvements in sucrose content [CCS = l.OYear + 89.92; R 2 = 0.63] than 
by cane yield [TCH = 0.11 Year + 81.73; R 2 = 0.005], which is consistent with well-established 
expectations. In Stage 2 trials, large numbers of clones are evaluated in unreplicated, single-row 
plots. Cane yield is more adversely affected by the lack of replication and competition effects 
among clones in small plots compared to sucrose content (Jackson and McRae, 2001; McRae 
and Jackson, 1998; Hogarth, 1977). Kimbeng et al. (2001a) reported correlation coefficients that 
were always higher in magnitude for sucrose content compared to cane yield between clones in 
Stage 2 (single-row, unreplicated) and Stage 3 (2 replicates, multiple locations, 4-row plots) 
trials. Even in replicated clonal plots, the degree of genetic determination was five fold higher 



28 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

for Brix compared to cane yield (Hogarth, 1977). Sucrose content is a more influential trait than 
cane yield in determining among clone differences in Stage 2 trials. The BSES is now routinely 
using spatial analysis, with the model also adjusting for intergenotypic competition, to improve 
estimates of cane yield in Stage 2 trials (Stringer and Cullis, 2002a, b). Research is underway to 
test the selection system proposed by Jackson and McRae (2001) in which, clones are evaluated 
in replicated 5-m plots with selections geared more towards sucrose content (measured 
objectively) and liberal for cane yield (measured as visual yield). 

CONCLUSIONS 

Several research and simulation studies have shown that combined family and individual 
clone selection is a practical and cost-efficient method of selection in early stage sugarcane trials. 
Family selection is very practical under lodged conditions and is especially suited to mechanical 
harvesting. Family selection, based on the plant crop data, is useful in identifying those families 
that harbor the highest proportion of elite clones. This makes it possible to focus selection for 
superior clones (individual clone selection) on the best families. Adopting family selection in 
early stage trials has positively affected other aspects of the selection program. For example, the 
availability of objective data on progeny performance presented the opportunity to generate 
robust estimates of the breeding value of parents involved in crosses. This allowed for a more 
rapid recycling of elite parents into the crossing program than was previously possible with the 
proven cross method. The population from which families and clones are selected and the 
population of clones immediately following family and clonal selection showed an overall 
gradual improvement indicating that these populations were not adversely affected by the 
adoption of family selection. Taken together, this can only lead to an improvement in the overall 
efficiency of the selection programs. 

ACKNOWLEDGMENTS 

We gratefully acknowledge the immense contribution of plant breeding staff at the BSES 
Mackay and Bundaberg Stations. Suggestions by Dr Scott Milligan (United States Sugar 
Corporation) and by anonymous reviewers are gratefully acknowledged. Finally, we are grateful 
to the Directors of the BSES and Louisiana State University Agricultural Center for their 
permission to publish this paper. 

REFERENCES 

1. Allard R. W., and A. D. Bradshaw. 1964. Implications of genotype-environmental 
interactions in plant breeding. Crop Science 4: 503-508. 

2. Balzarini, M. G. 2000. Biometrical models for predicting future performance in plant 
breeding. PhD Dissertation, Louisiana State University. (Dissertation Abstracts: 99-79242.) 

3. Berding N., and E.T. Roach. 1987. Germplasm collection, maintenance and use. In: D.J. 
Heinz(ed), Sugarcane improvement through breeding Elsevier, New York, pp 143-210. 

4. BSES. 1984. The Standard Laboratory Manual for Australian Sugar Mills. Volume 1. 
Principles and Practices. Bureau of Sugar Experiment Stations: Brisbane, Australia. 



29 



Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

5. Bull, J. K., D. M. Hogarth, and K. E. Basford. 1992. Impact of genotype x environment 
interaction on response to selection in sugarcane. Australian Journal of Agricultural 
Research 32:731-737. 

6. Chang, Y. S., and S. B. Milligan. 1992a. Estimating the potential of sugarcane families to 
produce elite genotypes using bivariate methods. Theoretical and Applied Genetics 
84:633-639. 

7. Chang, Y. S., and S. B. Milligan. 1992b. Estimating the potential of sugarcane families to 
produce elite genotypes using univariate cross prediction methods. Theoretical and 
Applied Genetics 84:662-671. 

8. Comstock, R. E., and H. F. Robinson. 1948. The components of genetic variance in 
populations of biparental progenies and their use in estimating the average degree of 
dominance. Biometrics 4:254-266 

9. Comstock, R. E., H. F. Robinson, and P. H. Harvey. 1949. A breeding procedure designed 
to make maximum use of both general and specific combining ability. Agronomy Journal 
41:360-367. 

10. Cox, M. C, and J. K. Stringer. 1998. Efficacy of early generation selection in a sugarcane 
improvement program. Proceedings Australian Society Sugarcane Technologists 20: 148- 
153. 

11. Cox, M. C, T. A. McRae, J. K. Bull, and D. M. Hogarth. 1996. Family selection improves 
the efficiency and effectiveness of a sugarcane improvement program. In Wilson, J. R., 
Hogarth, D. M., Campbell, J. A. and Garside, A. L. (eds). Sugarcane: Research towards 
Efficient and Sustainable Production, Pp 42-43. CSIRO Div. Tropical Crops and Pastures, 
Brisbane. 

12. Cox, M. C, Hogarth, D.M., and P. B. Hansen. 1994. Breeding and selection for high early 
season sugar content in a sugarcane (Saccharum spp. hybrids) improvement program. 
Australian Journal Agricultural Research 45:1569-1575. 

13. Cox, M. C, and D. M. Hogarth. 1993. Progress and changes in the South Queensland 
Variety Development Program. Proceedings International Society Sugarcane Technologists 
15:251-255. 

14. Cox, M. C, D. M. Hogarth, and R. T. Mullins. 1990. Clonal evaluation of early sugar 
content. Proceedings Australian Society Sugarcane Technologists 12: 90-98. 

15. De Sousa-Vieira, O., and S. B. Milligan. 1999. Intrarow spacings and family x environment 
effects on sugarcane family evaluation. Crop Science 39:358-364. 

16. Falconer, D. S., and T. F. C. Mackay. 1996. Introduction to quantitative genetics. Fourth 
Edition. Longman Group Ltd., UK. 



30 









Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

17. Griffing, B. 1956. Concept of general and specific combining ability in relation to diallel 
crossing systems. Australian Journal Biological Science 9:463-493. 

18. Hayman, B. I. 1954. The theory and analysis of diallel crosses. Genetics 39:789-809. 

19. Henderson, C. R. 1975. Best linear unbiased estimation and prediction under a selection 
model. Biometric 31:423-477. 

20. Hogarth, D. M., M. C. Cox, and J. K. Bull. 1997. Sugarcane improvement: Past achievements 
and future prospects. In: Kang, M.S. (ed.) Crop Improvement for the 21 st century, pp 29-56. 

21. Hogarth, D. M., M. J. Braithwaite, and T. C. Skinner. 1990. Selection of sugarcane 
families in the Burdekin district. Proceedings Australian Society Sugarcane Technologists 
12:99-104. 

22. Hogarth, D. M., and R. T. Mullins. 1989. Changes in the BSES plant improvement 
program. Proceedings International Society Sugarcane Technologists 20: 956-961. 

23. Hogarth, D. M., and J. C. Skinner. 1986. Computerisation of cane breeding records. 
Proceedings International Society Sugarcane Technologists 19:478-491. 

24. Hogarth, D. M. 1977. Quantitative inheritance studies in sugarcane. III. The effect of 
competition and violation of genetic assumptions on estimation of genetic variance 
components. Australian Journal Agricultural Research 28: 257-268. 

25. Hogarth, D. M. 1971. Quantitative inheritance studies in sugarcane. II. Correlations and 
predicted responses to selection. Australian Journal Agricultural Research 22: 103-109. 

26. Jackson, P. A., and T. A. McRae. 2001. Selection of sugarcane clones in small plots: 
effects of plot size and selection criteria. Crop Science 41: 315-322. 

27. Jackson, P. A., and T. A. McRae. 1998. Gains from selection of broadly adapted and 
specifically adapted sugarcane families. Field Crops Research 59: 151-162. 

28. Jackson, P. A., and G. Galvez. 1996. Role of variable soil nutrient levels in causing 
genotype x environment interaction in sugarcane. In Wilson, J. R., Hogarth, D. M., 
Campbell, J. A. and Garside, A. L. (ed). Sugarcane: Research towards Efficient and 
Sustainable Production, Pp 52-54. CSIRO Div. Tropical Crops and Pastures, Brisbane. 

29. Jackson, P. A., T. A. McRae, and D. M. Hogarth. 1995a. Selection of sugarcane families 
across variable environments. II. Patterns of response and association with environmental 
factors. Field Crop Research 43:109-118. 

30. Jackson, P. A., T. A. McRae, and J. K. Bull. 1995b. The role of family selection in 
sugarcane breeding programs and the effect of genotype x environment interactions. 
Proceedings International Society of Sugarcane Technologists 22:261-269. 



31 



Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia. A Review 

31. Jackson, P. A., W. M. Symington, T. E. Morgan, and A. W. Wood. 1992. The CSR 
sugarcane breeding program - Future direction and strategies. Proceedings Australian 
Society of Sugarcane Technologists 14:123-129. 

32. Jackson, P. A., T. A. McRae, and D. M. Hogarth. 1994. Selecting superior sugarcane 
crosses for the Herbert River district. Proceedings Australian Society Sugarcane 
Technologists 16:47-54. 

33. Kimbeng, C. A., D. Froyland, D. Appo, A. Corcoran, and M. Hetherington. 2001a. An 
appraisal of early generation selection in the central Queensland sugarcane improvement 
program. Proceedings Australian Society Sugarcane Technologists 23:129-135. 

34. Kimbeng, C. A., T. A. McRae, and M. C. Cox. 2001b. Optimising early generation 
selection in sugarcane breeding. Proceedings International Society Sugarcane Technologists 
24 (2): 488-493. 

35. Kimbeng, C. A., T. A. McRae, and J. K. Stringer. 2000. Gains from family and visual 
selection in sugarcane, particularly for heavily lodged crops in the Burdekin region. 
Proceedings Australian Society Sugarcane Technologists 22: 163-169. 

36. Kimbeng, C. A., and T. A. McRae. 1999. Optimum selection strategies in original 
seedlings particularly for heavily lodged crops. Sugar Research and Development Final 
Report. Bureau of Sugar Experiment Stations: Brisbane, Australia. 

37. Mangelsdorf, A. J. 1983. Cytoplasmic diversity in relation to pests and pathogens. 
International Society of Sugarcane Technologists Newsletter 45:45-49 

38. McRae, T. A., and P. A. Jackson. 1998. Competition effects in selection trials. 
Proceedings Australian Society Sugarcane Technologists 20:154-161. 

39. McRae, T. A., and P. A. Jackson. 1995. Selection of sugarcane families for the Burdekin 
river irrigation area. Proceedings Australian Society of Sugarcane Technologists 17:134- 
141. 

40. McRae, T. A., D. M. Hogarth, J. W. Foreman, and M. J. Braithwaite. 1993. Selection of 
sugarcane seedling families in the Burdekin district. In 'Focused Plant Improvement' 
Proceedings of the Tenth Australian Plant Breeding Conference. 77-82. 

41. Pollock, J. S. 1982. Variety selection in the Burdekin. Proceedings Australian Society of 
Sugar Cane Technologists 4: 121-129. 

42. Skinner, J. C, D. M. Hogart, and K. K. Wu. 1987. Selection methods, criteria, and indices. 
Developments in crop science 11: Sugarcane improvement through breeding DJ Heinz 
(ed.) Elsevier Amsterdam. 









32 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

43. Skinner, J. C. 1971. Selection in sugarcane: a review. Proceedings International Society 
Sugarcane Technologists 14:149-162. 

44. Skinner, J. C. 1967. Grading cultivars for selection. Proceedings International Society of 
Sugarcane Technologists 12: 938-949. 

45. Stringer, J. K., and B. R. Cullis. 2002a. Application of spatial analysis techniques to adjust 
for fertility trends and identify interplot competition in early stage sugarcane selection trials 
Australian Journal of Agricultural Research 53: 91 1-918 

46. Stringer, J. K., and B. R. Cullis. 2002b. Joint modeling of spatial variability and interplot 
competition. In McComb, J. A. (Ed) 'Plant Breeding for the 1 1 Millennium'. Proceedings of 
the 12 th Australasian Plant Breeding Conference, Perth, W. Australia, 15-20 September 2002, 
pp 614-619. 

47. Stringer, J. K., T. A. McRae, and M. C. Cox. 1996. Best linear unbiased prediction as a 
method of estimating breeding value in sugarcane. In Wilson, J. R., Hogarth, D. M., 
Campbell, J. A. and Garside, A. L. (eds). Sugarcane: Research towards Efficient and 
Sustainable Production, Pp 39-41. CSIRO Div. Tropical Crops and Pastures, Brisbane. 

48. Zaunbrecher, R. 1995. Improving selection procedures in sugarcane using cross appraisal 
methods. Masters Thesis, Louisiana State University. 



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Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

Table 1. The activities of the first two stages of a typical BSES sugarcane selection program 

Stage/ Crop Operation 1 ^ 

Year 

1 Stage 1 Seedling stage planted: Full-sib families x 5 replicates x 20 seedlings/ 

replicate. 

2 P Family performance data collected: Sucrose content (CCS) is estimated 

using eight stalks, one from each of eight randomly chosen stools in a 
plot. Cane yield (TCH) is estimated on a family-plot basis using 
mechanical harvester and mobile weighing tipper. The selection index, 
net merit grade (NMG), is calculated using CCS, and TCH data. NMG 
expresses family performance relative to that of standard families or 
proven crosses, which are adjusted to a mean of ten. The NMG formula 
penalizes families with poor appearance grade and awards a bonus for 
high sucrose content. 

3 1R Clones selected from best families: Individual clone selection is based 

on visual appraisal for yield and appearance grade and on Brix (% soluble 
solids w / w in the juice) measured using hand held refractometers. 

Stage 2 First clonal stage planted: Single-row, single replicate, 10-m plots. 

4 P First clonal stage data collected and top 30% of clones selected as 

"tentatives": CCS is estimated using two random stalks in a plot. TCH is 
estimated for each clone using mechanical harvester and mobile weighing 
tipper. The selection index, NMG, is calculated using CCS and TCH 
data. 

5 1R Data collected on "tentatives" and the top 20% selected: CCS 

estimated using two random stalks in a plot. TCH is estimated for each 
clone using mechanical harvester and mobile weighing tipper. NMG is 
calculated using CCS and TCH. 



T See Skinner (1967) for a more detailed explanation and calculation of NMG; the procedure to 
estimate CCS is outlined in a BSES (1984) publication. 



34 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 



Table 2. Selection rates, from Stage 2 to 3, of clones derived from different net merit grade 
(NMG) classes in Stage 1 . f 



Stage 1 
NMG 


No. of 
families 
selected 
in Stage 1 


No. of 

clones 

selected 

Stage 1 to 2 


%of 

clones 

selected 

Stage 1 to 2 


No. of 

clones 

selected 

Stage 2 to 3 


%of 

clones 

selected 

Stage 2 to 

3 


%of 

Stage 1 

clones 

selected 

to Stage 3 


9.0-9.9 


19 


53 


2.7 


2 


3.8 


0.11 


10.0-10.9 


54 


379 


7.0 


26 


6.9 


0.48 


11.0-11.9 


36 


486 


13.5 


36 


7.4 


1.00 


12.0-12.9 


18 


304 


16.9 


23 


7.6 


1.28 


> 13.0 


11 


191 


17.4 


26 


13.6 


2.36 


Total 


138 


1413 


10.2 


113 


8.0 


0.82 



T See Table 1 for a description of NMG and selection Stages. 



Table 3. Gain from different selection strategies in Stage 1 as measured by performance in 
Stage 2. f 



Selection strategy * 


Appraised 
Stage 1 


Evaluated 
Stage 2 


With NMG > 9.0 
Stage 2 § 


Gain, % 






No of clones 






Individual clone 


2444 


340 


51 


15.0 


Family (F) 


944 


944 


88 


9.3 


F + Visual grade 


944 


360 


54 


15.0 


F + Visual grade + Brix 


944 


240 


43 


17.9 



T See Table 1 for explanation on Stages of selection and NMG. 

* Only the top 40% of families are shown here. 

§ Clones with NMG > 9.0 are considered to be elite clones and are selected to the next stage. 



35 



Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

Table 4. Correlation coefficients (r) between net merit grade (NMG) and Best Linear 
Unbiased Predictor (BLUP), and between NMG and empirical method among crosses in 
sugarcane. 



No. of families 



Year(s) of data 

used to estimate 

BLUP values 



Year of data used 

to estimate NMG 

values 



(NMG vs BLUP) 



I" (NMG vs Empirical 
method) 



81 


1992-93 (2) 


1994 


97 


1992-94(3) 


1995 


173 


1992-95 (4) 


1996 



0.62 
0.63 
0.65 



T See Table 1 for explanation on NMG. 

* At least 10 years of data used to estimate empirical mean values. 



0.45 
0.50 

NA 



Table 5. Mean net merit grade and standard deviation for families derived from parents 
arbitrarily categorized as old (O), medium (M), or new (N). 



Family category 


No. of families 


OxO 


21 


OxM 


135 


OxN 


22 


MxM 


83 


MxN 


30 


NxN 


2 



Net merit grade 



t 



5.31 ± 1.30 c 

6.38 ± 1.47 b 

6.17 ± 1.47 b 

7.07 ±1.74 a 

7.05 ±1.55 a 

5.91 ± 1.42 abc 

T Parents were arbitrarily categorized as old (O), medium (M), or new (N) if the 

seedling parent had a year prefix < 65, 65-74, or > 74, respectively; data averaged 

over four years. 
* See Table 1 for explanation on NMG. NMG was calculated relative to standard 

clones in the trial. Usually, proven crosses are used as standard families. 
§ Means followed by different letters are significantly different (P > 0.05); the NxN 

group had too few families to permit any reasonable comparison. 



36 



.«. 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 






Figure 1. The shaded portions show areas where sugarcane is cultivated in Australia. The 
breeding stations operated by the BSES are located at Meringa (south of Cairns), Ingham, Ayr, 
Mackay and Bundaberg. 



37 



+ 



Kimbeng and Cox: Early Generation Selection of Sugarcane Families and Clones in Australia: A Review 

Figure 2. Percentage of elite Stage 2 clones resulting from different selection strategies in Stage 
1 . See Table 1 for explanation of selection stages and NMG. 



16 
15 

<N 
U 

8 14 

on 

c 

'X 13 

o 

A 12 



e n 

u 

JS io 

o 
u 

s - 



■Visual selection 
'Random selection 







10 20 30 

Family selection rate for NMG in Stage 1, % 



40 



Figure 3. Population improvement in sugarcane: performance (NMG) of seedlings (Stage 1) 
relative to the cultivar Q151 from 1993 to 2000. See Table 1 for explanation of Stage 1 trials 
and NMG. 



0.65 



O 




0.55 



38 



Journal American Society of Sugarcane Technologists, \vol. 23, 2003 

Figure 4. Population improvement in sugarcane: performance (NMG) of clones in Stage 2 
relative to the cultivars Q141 and Q151 from 1994 to 2000. See Table 1 for explanation of Stage 
2 trials and NMG. 



150 



^130 

5 no 

to 

1 

•S 90 






70 



50 4 



Population mean 
•Top 10% of mean 



NMG = 2.02 Year + 117.35 

2 




1994 



1995 



1996 



NMG= 1.58 Year + 66.48 
R 2 = 0.56 




1997 
Year 



1998 



1999 



2000 



39 



Bressiani et al.: Repeatabilty within and between selection stages in a sugarcane breeding program. 

REPEATABILITY WITHIN AND BETWEEN SELECTION STAGES IN A SUGARCANE 

BREEDING PROGRAM 

Jose A. Bressiani 1 ; Roland Vencovsky 2 and Jorge A. G. da Silva 3 . 

1 Centro de Tecnologia Copersucar, Secao de Melhoramento, CP 162, CEP 13400-970, 
Piracicaba, Sao Paulo, Brasil, bressiani (alcopersucar.com.br 

2 Escola Superior de Agricultura "Luiz de Queiroz", Departamento de Genetica, CP 83, CEP 

13400-970, Piracicaba, Sao Paulo, Brazil, rvencovs(a),esalq .usp.br 

3 Texas Agricultural Experiment Station, Texas A&M University, 2415 E. Hwy 83, 78596 - 

Weslaco, TX, USA, iadasilva@ag.tamu.edu 

ABSTRACT 

Aiming to obtain repeatability estimates (r^) to help in the identification of superior 
clones, six full-sib sugarcane families were evaluated in the first three of six clonal selection 
stages. The traits evaluated were: stalk length and diameter, stalk weight and number and Brix 
% cane juice. Results showed that, for stalk length and Brix, r p(x) estimates weren't significantly 
different between stages I and III and between II and IH. For stalk diameter, stalk number and 
weight of stalks, there was a clear difference of r p(x) values between stages I and HI and between 
II and IQ. These results indicate that, for phenotypic selection in stage I, priority should be given 
to Brix % cane juice and to stalk length in the first place, whereas from stage H forward, 
additional emphasis should be given to stalk diameter, number of stalks and weight of stalks. 
When the same selection stage is considered, repeatability estimates for each trait were also 
similar from plant to first ratoon, which indicates that selection for ratooning ability is not 
effective in the first two selection stages. 

Keywords: sugarcane, repeatability, early selection 

INTRODUCTION 

New sugarcane cultivars are obtained through the selection of vegetatively propagated 
genotypes obtained from true seed, which is derived from the hybridization of superior parents. 
Selection is applied in all breeding stages: the choice of parents, cross combinations and the 
plant population originating from the crosses made (Skinner et al., 1987). Individual seedling 
selection during the initial stage is of low efficiency given the low broad sense heritability for 
the majority of traits (Skinner, 1982). It has been common practice in breeding programs to 
obtain phenotypic estimates for the traits under selection during the initial breeding stages. 
(Dudley and Moll, 1969; Skinner et al., 1987). 

Repeatability estimates are utilized to measure the association of the same trait between 
different initial selection stages and crop cycles (plant cane and ratoons). Knowing these 
estimates helps to set up selection criteria for visual evaluation, which increases selection 
efficiency and reduces the risk of losing superior genotypes. 

Studies with estimates of repeatability have been reported by Mariotti (1973) in 
Argentina, Miller and James (1975) and Milligan et al. (1996) in USA, Nageswara and Ethirajan 



40 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

(1985) in India, Rodrigues (1986) in Colombia, Randoyal (1999) in Mauritius, and Bakshi Ram 
and Chaudhary (2000) in the West Indies, among others. Great variation in repeatability is 
observed among these studies, which indicates not only the influence of the environment on 
selection, but also a strong interaction between genotypes x environments and between 
genotypes x selection criteria. 

The purpose of this work was to determine the estimates of repeatability for the more 
important traits in sugarcane, during the initial stages of selection and under the conditions of the 
breeding program in Braz 

MATERIALS AND METHODS 

The population utilized in this work was represented by the progenies of six bi-parental 
crosses (full-sibs), obtained at random from the Copersucar Breeding program, involving 12 
different parents from the germplasm bank at Camamu, Bahia, Brazil. Seedlings obtained from 
each of the six crosses were planted in three experiments, one each year, in order to represent the 
first three selection stages of a total of six in the COPERSUCAR selection program. All 
experiments were planted in a randomized block design, with four replicates, and k genotypes 
(seedling or clone) within plots according to Steel and Torrie (1980), with k equal to 70 
seedlings in experiment 1, 20 in experiment 2, and 10 in experiment 3. Sub-plot size varied 
from one stool spaced 0.5 m in the row in experiment 1, to one furrow two meters long in 
experiment 2, and then to two furrows six meters long in experiment 3. In all three experiments, 
rows were 1 .4 m apart and the subplot sizes were the same as those used in the first three stages 
of selection in the Copersucar breeding program. 

Twelve months after planting in the plant-cane stage, and 12 months after harvesting of 
the plant cane for the first-ratoon stage, we measured the following traits in the whole plot of 
each individual plant (sub-plot): stalk height (cm), stalk diameter (1 to 9 grade obtained with a 
cm-scaled rule, with 1 being the thickest diameter and 9, the thinnest one), stalk number, weight 
of stalks, and Brix % juice. 

The repeatability estimates (r p(x) ) were obtained between crops and between selection 
stages. According to Falconer and Mackay (1996), t^ k) determines the upper boundary of the 
broad-sense heritability (h 2 J, and was estimated using the following expression: 

^(X) - y 

v p 

where r P(x) represents the repeatability of trait x, V G represents the genetic variance, V EP is the 
permanent environmental variance and V P is the phenotypic variance. 

If V EP is zero, r p( X ) = h a . The permanent environmental variance occurs when 
data is collected and replicated over time in the same experiment, as is normal in sugarcane 
crops harvested over several ratoons. In vegetatively propagated crops like sugarcane, there is 
also the possibility of transmission of non-genetic effects (V EP ) with propagation. These effects 



41 



Bressiani et al.: Repeatabilty within and between selection stages in a sugarcane breeding program. 

would appear in the next stage among the clones (Skinner, 1962). In this situation, repeatability 
among stages of selection has been used in sugarcane breeding. 

The estimates of repeatability in each of the experiments, from the analysis of variance 
(Steel and Torrie, 1980), considered that seedlings or clones gave rise to two data sets (plant and 
ratoon stages) and was calculated as follows: 

<j p 



<jp +<J 

where o p is the estimate of the variance among seedlings or clones and contains the genetic 
variance among them plus the variance due to permanent environmental effects expressed in the 
two crop cycles (plant and ratoon). The term a 2 measures the environmental variance, at the 
sub-plot level, due to interaction between seedlings or clones with the crop cycles. 

Estimates of repeatability between the experiments 1 to 3 (stage I to IU) were obtained 
through covariance analysis (Steel and Torrie, 1980), as it involved data from different 
experiments, as opposed to the case with crop cycles. Thus, these repeatabilities correspond to 
the phenotypic correlation of trait (x) on a given stage and this same trait (x'), in other selection 
stages and cycles and were estimated as follows: 



r P(x) ~ r P{xx') ~ 



Cov P(*0 
<J P(x)CT />(*•) J 



where Co v P{xxt) is the phenotypic covariance oftrait x between experiments(stages), <J p ( x ) 
is the mean phenotypic variance of trait x and <Xp ( *■) is the mean phenotypic variance of trait 



x . 



These analyses were first calculated for each cross and then after pooling for all crosses. 
For pooled data, a test for homogeneity among the estimates of repeatability between crosses 
was made and a % 2 test was used to accept or reject it (Steel and Torrie, 1980). 



RESULTS AND DISCUSSION 

Estimates of repeatability in sugarcane are presented in Tables 1 to 5. Individual 
estimates for each cross are not presented separately since the differences for this group of 
crosses were not significant (p>0.05) based on x 2 test for homogeneity. Table 1 shows that the 
highest values for repeatability of stalk length were observed between stage Hi-plant and stage I- 
ratoon and also between stage E-ratoon and stage I-ratoon. These estimates are similar to those 
presented by Mariotti (1973) in Argentina, who found r p(x) = 0.36 for mean stalk length between 
stages I and II on first ratoon crop. On the other hand, Bakshi Ram and Chaudhary (2000) found 
estimates that varied from 0.15 to 0.21 between stage I and II plant cane for three open crosses. 



42 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 



Under these same conditions, Rodrigues (1986) observed estimates between 0.5 and 0.6 for r^ 
in the plant crop, while Randoyal (1999), using family means, found values of 0.59 and 0.60 for 
repeatability among plant cane and ratoon in stage I. 

Table 1. Repeatability estimates for stalk length. 



Stage 


Crop Cycle 


Stage I 
Ratoon 




Stage 


n 


Stage m 




Plant 




Ratoon 


Plant 


Stage I 


Plant 


0.39** 


0.37* 




0.42** 


0.43** 




Ratoon 




0.32** 




0.54** 


0.56** 


Stage n 


Plant 
Ratoon 








0.38** 


0.49** 
0.52** 


** significant at the 0.01 level 













The absence of significant differences of repeatability between plant-cane and first- 
ratoon crops in stages I and II indicates that selecting for stalk length could be done in the plant 
cane crop, which results in a higher selection gain per unit of time, given that the genotypes 
under selection will reach stage HI two years after planting stage I. However, selecting for stalk 
length must be liberal, given that the correlation values between stages I and HI and between 
stages II and III did not exceed 0.5. 

Table 2 presents repeatability values observed for stalk diameter. Repeatabilities were 
slightly higher than those obtained for stalk length, with no difference between plant and first- 
ratoon crops. The repeatability observed between stages I and in were inferior to those observed 
between stages II and m, indicating that selection for this trait on stage I has low efficiency, 
particularly on ratoon crops. Our recommendation is that selection for stalk diameter on stage I 
should be very liberal, and more intense on stage n, where repeatability is higher. The 
repeatability values obtained in this study are close to those obtained by Rodrigues (1986) but 
inferior to those reported by Bakshi Ram and Chaudhary (2000), who found estimates between 
0.84 and 0.90. We recommend that selection for stalk diameter should be made on plant cane in 
stages I and H. 

Table 2. Repeatability estimates for stalk diameter 



Stage 


Crop Cycle 


Stage I 
Ratoon 




Stage 


n 


Stage m 




Plant 




Ratoon 


Plant 


Stage I 


Plant 


0.52** 


0.58** 




0.45** 


0.45** 




Ratoon 




0.47** 




0.42** 


0.37** 


Stage H 


Plant 
Ratoon 








0.53** 


0.62** 
0.55** 



** significant at the 0.01 level 



43 



Bressiani et al.: Repeatabilty within and between selection stages in a sugarcane breeding program. 

For stalk number (Table 3), the highest repeatability occurred in stage II between plant 
cane and first ratoon, with r^ = 0.69. Repeatabilities between stage I and II were low, close to 
those obtained for stalk length and inferior to those obtained for stalk diameter. However, 
between stages I and HI and between stages II and IE, repeatability values were higher than 
those obtained for stalk length and close to those obtained for stalk diameter. In this case our 
results are different from those of Rodrigues (1986) and Bakshi Ram and Chaudhary (2000), but 
similar to those of Miller and James (1975), who found repeatability values between stages I, II 
and in similar to those for stalk diameter (0.5). 



Table 3. Repeatability estimates for stalk number 






Stage Crop Cycle Stage I 


Stage H 


Stage m 


Ratoon 


Plant Ratoon 


Plant 



Stage I Plant 0.63** 0.34** 0.36** 0.41** 

Ratoon 0.39** 0.44** 0.46** 

Stage II Plant 0.69** 0.60** 

Ratoon 0.55** 

** significant at the 0.01 level 

Table 4 shows repeatabilities for Brix % cane juice. Here the r p(x) values obtained among 
all stages and crosses were uniform and high, with values greater than 0.60 in most cases, which 
indicates that Brix % cane juice is the character with highest repeatability in the initial stages of 
selection. The plant-cane crop had the most uniform results when compared to those obtained 
for the ratoon crop, with the highest values occurring between stages I and II, in plant cane. 
These values are higher than those reported in the literature (Mariotti, 1973; Miller and James, 
1975; Nageswara and Ethirajan, 1985; Rodrigues, 1986; Bakshi Ram and Chaudhary, 2000). 

Table 4. Repeatability estimates for Brix % cane juice. 



Stage 


Crop Cycle 


Stage I 
Ratoon 




Stage 


n 


Stage m 




Plant 




Ratoon 


Plant 


Stage I 


Plant 


0.45** 


0.78** 




0.72** 


0.67** 




Ratoon 




0.71** 




0.68** 


0.62** 


Stage H 


Plant 
Ratoon 








0.59** 


0.70** 
0.67** 



** significant at the 0.01 level 

As a quantitative trait, resulting from other yield components (stalk length, stalk diameter 
and number of stalks), the weight of stalks had low repeatability values (Table 5). These values 
were small between stages I and II and between stages I and HI, both for plant and ratoon crops. 



44 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 



Repeatability values between stages II and HI were higher, however, indicating that weight of 
stalks in stage I should not be used as a direct selection criterion. Its components - stalk length, 
stalk diameter and number of stalks - should instead be preferred for selection in this stage. 

Table 5. Repeatability estimates for stalk weight. 



Stage 


Crop Cycle 


Stage I 
Ratoon 




Stage 


n 


Stage m 




Plant 




Ratoon 


Plant 


Stage I 


Plant 


0.48** 


0.35** 




0.36** 


0.29** 




Ratoon 




0.33** 




0.42** 


0.30** 


Stage H 


Plant 
Ratoon 








0.60** 


0.57** 
0.53** 



** 



significant at the 0.01 level 



Based on the results obtained in stage in (which is the stage with the largest plot, lowest 
genotype x environment interaction and lowest competition between plots compared to previous 
stages) the following observations were made: (a) for stalk length and Brix, r^ values weren't 
significantly different between stages I and HI and between stages II and IE; (b) for stalk 
diameter, stalk number and weight of stalks, there was a clear difference of r p(x) values between 
stages I and HI and between stages II and III. These results indicate that, for phenotypic selection 
in stage I, priority should be given to Brix % cane juice and to stalk length, whereas from stage 
II forward, additional emphasis should be given to stalk diameter, number of stalks and weight 
of stalks. 

CONCLUSIONS 

Brix % cane juice presented high repeatability values between stages I and III and also 
between plant-cane and first-ratoon crops. Particularly for this trait, individual selection can be 
intensified in stage I. 

Stalk length showed low repeatability between stages I and II and intermediate 
repeatability between stages I and HI and stages II and HI, in both plant and ratoon crops. Given 
the similar values for r^ between stages I and IE and stages II and IE, we reached the 
conclusion that the same criterion utilized for selection on stage I can be applied on stage H 

The traits stalk diameter and number of stalks showed moderate repeatability among all 
stages and crops studied, with r p(x) values between stages II and IE slightly higher than those 
between stages I and IE, for both crops. In this scenario, selection for these traits in stage I 
should be less intense than in stage II, and it can be applied on plant cane. 

Weight of stalks had low repeatability in stage I, and intermediate repeatability in stage 
II. Repeatability values were lower than those found for the number of stalks, stalk length and 



45 



Bressiani et al.: Repeatabiity within and between selection stages in a sugarcane breeding program. 

stalk diameter in this study. As a recommendation, individual selection based on weight of 
stalks should be avoided in stage I, being applied only from stage II forward. 

Regarding the plant and ratoon crop cycles, the values found for repeatability indicated 
that the individual selection could be applied on plant cane for both stages I and n, since the r (x) 
values obtained were similar for plant cane and ratoon cane. 

ACKNOWLEDGEMENTS 

We are grateful to COPERSUCAR and their breeders and technicians for their support 
and help along with these experiments. We would like to thank Dr. James Irvine for fruitful 
discussion and suggestions. 

REFERENCES 



1. Bakshi Ram and B. S. Chaudhary. 2000. Individual and simultaneous selection for Brix 
yield in seedling populations of sugarcane. Sugar Cane International, Jun, 12-19. 

2. Dudley, J. W. and R. H. Moll. 1969. Interpretation and use of estimates of heritability 
and genetic variances in plant breeding. Crop Science, Madison, 9:257-262. 

3. Falconer, D.S and T. F. C. Mackay. 1996. Introduction to Quantitative Genetics. 4 th ed. 
London: Longman, 464p. 

4. Mariotti, J. A. 1973. Experiencias de seleccion clonal en cana de aziicar en la provincia 
de Jujuy. II - Repetibilidad y Heredabilidad de caracteres de interese agronomico. 
Revista Agronomica Norte Argentina, 10 (l-2):61-73. 

5. Miller, J. D. And N. I. James. 1975. Selection in six crops of sugarcane. I - 
Repeatability of three characters. Crop Science, 15:23-25. 

6. Milligan, S.B., K. A. Gravois, and F. A. Martin. 1996. Inheritance of sugarcane 
ratooning ability and the relationship of younger crop traits to older crop traits. Crop 
Science, 36:45-50. 

7. Nageswara, R. A. O. and A. S. Ethirajan. 1985. Repeatability and predictability in 
progenies of crosses of high and low sugar cultivars of sugarcane. Indian Journal of 
Agricultural Science, 55(4):246-250. 

8. Randoyal, K. 1999. Genetic correlation and repeatability for agronomic characters in 
sugar cane populations in contrasting environments and different crop years. Sugar 
Cane, Apr, 4-12. 

9. Rodrigues, I. A. 1986. Influencia del sistema de cruzamiento en las poblaciones 
obtenidas de cana-aziicar. II - Repetibilidad de los principales caracteres. Boletin 
INICA, 2:1-10. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

10. Skinner, J. C. 1962. Sugarcane selection experiments. In: International Society of Sugar 
Cane Technologists Congress, 11. Jakarta. Proceedings. Jakarta: The Organizing 
Committee, p. 561-567. 

11. Skinner, J. C. 1982. Efficiency of bunch planted and single planted "seedlings" for 
selection of superior families in sugarcane. Euphytica, 31:523-37. 

12. Skinner, J. C, D. M. Hogarth, and K. K. Wu. 1987. Selection methods, criteria and 
indices. In: Heinz, D.J. Sugarcane Improvement through Breeding. Amsterdam: 
Elsevier, p. 409-453. 

13. Steel, R. G. D. And J. H. Torrie. 1980. Principles and Procedures of Statistics. A 
Biometric Approach. 2 nd Ed. McGraw Hill. USA, 633p. 



47 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

ENHANCED SUGARCANE ESTABLISHMENT 
USING PLANT GROWTH REGULATORS 



Bob Wiedenfeld 

Texas Agricultural Experiment Station 

Texas A&M University Research & Extension Center 

2415 E. Highway 83, Weslaco, TX 78596-8399 



ABSTRACT 

Since sugarcane is vegetatively propagated, large amounts of seed cane are used in order to 
insure a good stand. Plant growth regulator compounds, often used as ripening agents, can cause 
sprouting at lower nodes. This response to growth regulators could lead to better stands at planting 
while possibly using less seed. Field studies were conducted over three years to determine the 
effectiveness of different plant growth regulator compounds and methods of application on 
emergence enhancement for several different sugarcane cultivars. In the first test, application of 
ethephon [(2-chloroethyl) phosphonic acid] or glyphosate [isopropylamine salt of N- 
(phosphonomethyl) glycine] to standing cane three weeks prior to cutting as seed had no effect, or 
decreased shoot counts in the sugarcane stand planted with this seed source. Ethephon application 
to the seed pieces in-furrow at planting at the standard seed cane planting rate tended to increase 
shoot counts in the new planting for the first four months, and stalk heights for five months after 
planting on some cultivars. In the second test, ethephon application in-furrow at planting at reduced 
seed cane planting rates increased shoot counts for up to nine months following planting but had very 
little effect on stalk heights, again only on some cultivars. In the third test in two commercial 
plantings, ethephon application had very little effect on shoot counts or stalk heights, but seed cane 
planting rates used by planting crews turned out to exceed recommended levels. Also, the two 
cultivars in these plantings may have been less responsive to ethephon than others used in the earlier 
tests. Even when seed cane planting rates in the commercial plantings were reduced by 32%, no 
differences in final shoot populations were found indicating that the planting rates used were much 
higher than necessary. Ethephon application to seed cane in-furrow at planting was effective in 
increasing tillering, but natural declines in shoot population when stalk growth rates were highest 
eliminated any benefit except where very low seed cane planting rates were used. 

INTRODUCTION 

Sugarcane is vegetatively propagated, therefore large amounts of seed cane are required for a new 
planting. The recommended planting rate is around 9 to 10 Mg ha" 1 , but higher rates are often used. 
Fields used as a source of seed cane are lost for production that year, which takes out about 3% of 
all fields each year in Texas. While some sugarcane is planted mechanically, most is still planted 
by hand in Texas. Since a sugarcane crop will generally be grown for several years, it is important 
to insure a good stand. Therefore growers often plant very high rates of seed cane to make sure they 
have enough viable seed pieces for good field establishment. 

Plant growth regulators (PGRs) act on sugarcane by modifying or retarding some aspect of 
cane growth (Alexander, 1973). PGRs are used to stimulate sugar accumulation in the stalk on 

48 



\ 



.«. 



Wiedenfeld: Enhanced Sugarcane Establishment Using Plant Growth Regulators 

mature cane. Ripening using various growth regulating compounds is a common practice on 
sugarcane around the world (Eastwood and Davis, 1997), but only glyphosate [isopropylamine salt 
of-(phosphonomethyl) glycine] is used in the United States for this purpose. A common side effect 
of PGR application has been the formation of sideshoots from lower nodes. Sprouting of additional 
buds would result in more shoots and a better stand from the seed cane planted. Studies have 
indicated that certain plant growth regulator compounds increase tillering in newly planted sugarcane 
in greenhouse tests, but responses varied with cultivar (Bischoff and Martin, 1986; Eiland and Dean, 
1985; Wong-Chong and Martin, 1983). In South Texas, dipping of seed pieces in a solution of 
ethephon [(2-chloroethyl) phosphonic acid) enhanced tillering of cultivar NCo 310 (Wiedenfeld, 
1988). While dipping seed pieces may be effective, a more practical and economical application 
method would be desirable. 

The objective of this study was to determine the effectiveness of different plant growth 
regulator compounds and methods of application on sugarcane emergence enhancement for several 
different cultivars. 

MATERIALS AND METHODS 

Field studies were conducted over a three year period in the Lower Rio Grande Valley of 
Texas, an area with a subtropical, semiarid climate (average annual rainfall - 500 mm). Soils are 
alluvial, medium textured (typically sandy clay loam) and calcareous. 

During the first two years, tests were conducted on a Raymondville clay loam soil (Fine, 
mixed, hyperthermic Vertic Calciustolls) with a pH of 8.2. Treatments were applied to 5 sugarcane 
cultivars: CP70-321, CP71-1240, CP72-1210, CP80-1827 and TCP87-3388; and were applied in 
plots 6.1 m wide (4 rows spaced 1.5 m apart) by 9.1 m in length in randomized block designs with 
6 replications. Treatments in the first year consisted of an untreated check, application of ethephon 
[(2-chloroethyl) phosphonic acid, Ethrel®, Rhone-Poulenc] or glyphosate [isoropylamine salt of N- 
(phosphonomethyl) glycine, Roundup®, Monsanto] to standing cane 3 weeks prior to cutting for seed 
cane, or application of ethephon in-furrow to the seed cane at planting (Table 1). Ethephon was 
applied at the rate of 1 19 g a.i./ha, and glyphosate was applied at the rate of 301 g a.i./ha. Seed cane 
planting rate was double stalk overlap plus about 25%, or approximately 3900 pieces 1.5 m long per 
ha, which is the recommended rate for South Texas (Rozeff, 1998). 

Treatments the second year consisted of an untreated check or application of ethephon in- 
furrow to the seed cane at planting at the above rate, with seed cane planted at 2 different densities - 
single and double stalk overlap (Table 1 ). Cultivar CP80- 1 827, used the first year, was replaced with 
cultivar CP8 1-1405 the second year due to lack of response to treatments and because CP80-1827 
is not widely grown while CP8 1-1 405 was thought to have potential for use in the Lower Rio Grande 
Valley of Texas. The amount of seed cane planted was measured in the second year by weighing all 
cane planted in each plot. 

The third year tests were conducted in two commercial plantings. The Hiler location was on 
a Hidalgo sandy clay loam soil (Fine-loamy, mixed, hyperthermic Typic Calciustolls, pH 8.3) using 
cultivar TCP87-3388, and the Beckwith location was on a Harlingen clay soil (Very-fine, 
montmorillonitic, hyperthermic Entic Chromusterts, pH 8. 1 ) using cultivar CP70- 1133. Treatments 

49 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

consisted of an untreated check or ethephon application at the above rate applied to the normal rate 
of seed cane being planted by the commercial crews, or to a reduced cane planting rate (Table 1). 
The reduced rate was achieved by asking the commercial planting crews to plant at half of the 
normal rate. Treatments were applied in plots 1 .5 m wide (1 row) by 30.5 m in length in randomized 
block designs with 3 replications at both locations. The third year, all seed cane planted was 
weighed in two 3 m sections of row in each plot. 

Tests were furrow irrigated as required, and received herbicide application and mechanical 
cultivation for weed control each year. Shoot population counts were made by counting all shoots 
in two 3 m sections of row in each plot. Counts were initiated about 8 weeks following planting and 
continued periodically for a total of 10 to 16 counts until mid- August each year. Stalk height was 
measured on 3 stalks per plot in the first and second years, and on 2 stalks per plot in the two 
commercial tests the 3 rd year. Stalk measurements were taken between 5 and 13 times in each study 
depending on the year. All data were analyzed statistically by cultivar using Analysis of Variance 
and Duncan's multiple range test. 

RESULTS AND DISCUSSION 

During each growing season shoot counts generally increased until a peak was reached, 
typically when maximum stalk growth rates were occurring, then tended to decline thereafter (Figs. 
1-3). Highest average stalk growth rates approached 3.9 cm per day. Some differences in shoot 
counts and growth rates between cultivars were observed. 

Ethephon application in-furrow tended to be the most effective at increasing shoot counts and 
heights in 1998 (Fig. 1). When a significant treatment effect occurred on shoot counts (20 out of 65 
cultivar x date combinations) and plant heights (6 out of 25 cultivar x date combinations, Table 2), 
in-furrow ethephon application increased shoot counts 25% of the time, and increased stalk heights 
67% of the time. Glyphosate application to standing cane appeared to have a detrimental effect on 
shoot counts at some dates. Where statistically significant treatment effects are indicated in Table 
2, glyphosate application caused a reduction in shoot counts 95% of the time, and a reduction in 
stalk heights 50% of the time. Ethephon application to standing cane appeared to have very little 
effect. Treatment effects on shoot counts tended to disappear after about 4 months following 
planting. Treatments effects in this first test were most pronounced on cultivars CP70-321, CP70- 
1240 and CP72-1210; and were less evident or nonexistent on CP80-1827 and TCP87-3388. 
Amount of seed cane used in the first experiment was not measured, but planting rate was based on 
the "standard" recommendation which results in about 9 Mg/ha being planted. It was concluded that 
ethephon application in-furrow at planting was the treatment that showed the most promise based 
on the results obtained this first year. It was also observed that shoot numbers rose and then declined 
to an equilibrium level later in the season, indicating that the beneficial effects of ethephon on shoot 
emergence might be maximized at reduced planting rates. 

Therefore, a standard double stalk overlap and a reduced single stalk overlap planting rate 
were used in the second test (Table 3) with and without in-furrow ethephon application. The 
beneficial effects of ethephon application occurred most dramatically at the reduced planting rate, 
increasing shoot counts in some cases up to the levels obtained at the higher planting rate without 
ethephon application in this study (Fig. 2). Where treatment effects were statistically significant on 

50 



Wiedenfeld: Enhanced Sugarcane Establishment Using Plant Growth Regulators 

shoot population (32 of 50 cultivar x date combinations, Table 4), 41% of those were due to 
ethephon application. Stalk heights were affected by treatment on only 6 of the possible 35 cultivar 
x date combinations, but on 5 of those 6 occasions the effect was due to ethephon application. 
Where significant treatment effects occurred on the parameters measured not attributable to ethephon 
application, the effect was due to differences in the amount of seed cane planted. Also, treatment 
effects on shoot counts persisted for 9 months after planting (Table 4). Cultivars CP71-1240 and 
CP72- 1210 showed the greatest response to the ethephon treatment, as in the previous trial. TCP87- 
3388 shoot counts were affected by treatments applied in the second experiment, but the effect was 
almost entirely due to amount of seed cane planted. Differences between sugarcane cultivars in 
responses to PGR's has been routinely observed, making it necessary to calibrate PGR applications 
based on the response desired for each cultivar. 

The rate of seed cane planted turned out to be higher than "recommended rates" in both 
commercial fields used in the 3 rd experiment (Table 3). Some treatment effects on shoot counts were 
observed (Fig. 3) at one of the two locations up to almost 4 months after planting, but none were 
observed thereafter (Table 5). The cultivar TCP87-3388 used at the Hiler location showed little 
response to ethephon application in the prior tests while cultivar CP70-1 133 used at the Beckwith 
location had not been tested in the first two years of this study. 

CONCLUSIONS 

This study indicates that ethephon application in-furrow at planting on sugarcane seed pieces 
does increase shoot counts and stalk heights on some cultivars, in particular CP71-1240 and CP72- 
1210. However, since shoot numbers in sugarcane tend to increase rapidly early during growth but 
then decline to an equilibrium level later in the season when the most rapid growth rates occur, the 
beneficial effects of the increased shoot counts that were caused early in the season tend to disappear. 
Only where substantially reduced planting rates are used does the benefit of the increased shoot 
counts persist through the entire growing season. 

Another possible benefit of increased early season shoot counts and stalk heights would be 
to cause quicker canopy cover providing better competition over weeds. While glyphosate would 
not work for this purpose, ethephon may be a viable candidate for this use, although it would be 
necessary to determine whether the magnitude of the response would be adequate to provide the 
desired benefit. 

Where reduced planting rates were used in the commercial sugarcane fields, no reduction in 
final shoot counts were obtained compared to the growers' standard planting rates regardless of 
ethephon treatment, indicating that these growers were using substantially more seed cane than is 
necessary to obtain maximum stands. 



51 



Journal American Society of SugarcaneTechnologists, Vol. 23, 2003 

REFERENCES 

1. Alexander, A.G. 1973. Sugarcane Physiology. A comprehensive study of the Saccharum 
source-to-sink system , pp. 443-464. Elsevier Scientific Publishing Co., Amsterdam. 

2. Bischoff, K.P. and F. A. Martin. 1 986. The response of saccharum species to growth regulators 
used as tillering agents. LSU Sugarcane Research Annual Progress Report, p. 54. 

3. Eastwood, D. and H. B. Davis. 1997. Chemical ripening in Guyana - progress and prospects. 
SugarCane. 1997(3):4-17. 

4. Eiland, B. R. and J. L. Dean. 1985. Growth regulator effects on sugar cane germination and 
tillering. J. Amer Soc. Sugar Cane Tech. (abstract) 5:112. 

5. Rozeff, N. 1998. Preplant fertilization, seed cane and planting of sugarcane. In: N. Rozeff, J. 
M. Amador and J .E. Irvine. South Texas Sugarcane Production Handbook. Texas A&M 
University Research & Extension Center at Weslaco and Rio Grande Valley Sugar Growers, 
Inc., Santa Rosa. 

6. Wiedenfeld, R.P. 1988. Effects of growth regulators on tillering, flower control and ripening 
of sugarcane in the Lower Rio Grande Valley of Texas. J. Amer. Soc. Sugar Cane Tech. 8:67- 
74. 

7. Wong-Chong, J. and F.A. Martin. 1983. Greenhouse studies on the interaction of genotype and 
plant growth regulators with regard to early tillering in sugar cane. J. Amer. Soc Sugar Cane 
Tech. (abstract) 2:87. 



52 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 





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53 



Weidenfeld: Enhanced Sugarcane Establishment Using Plant Growth Regulators 



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54 



Wiedenfeld: Enhanced Sugarcane Establishment Using Plant Growth Regulators 

Table 3. Seed cane planting rate for the different planting densities in the 2 nd and 3 rd years of the 
study. 



Season 



Seed piece density 1 



Location 


Sugarcane 
Cultivar 


low 




high 








— Mg/ha - 






CP70-321 


3.6 




7.0 




CP71-1240 


4.5 




9.1 




CP72-1210 


4.4 




9.1 




CP81-1405 


4.5 




8.8 




TCP87-3388 


3.8 




8.2 


Hiler farm 


CP70-1133 


9.0 




13.4 


Beckwith farm 


TCP87-3388 


9.4 




13.8 



1999 



2000-01 



'Planting densities used in the 1999 crop were single (low) and double (high) overlap; and in the 
2000-01 crop were a reduced (low) and a commercial (high) rate. 



55 



Weidenfeld: Enhanced Sugarcane Establishment Using Plant Growth Regulators 





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56 



Wiedenfeld: Enhanced Sugarcane Establishment Using Plant Growth Regulators 

Table 5. Statistical significance of treatment effects on mean shoot population (pop) and height 
(hgt) measured at 2 locations on various days after planting (DAP)in the third year. 



Hiler farm 










Beckwith farm 




TCP87-3388 


DAP 


pop 


hgt 




CP70-1133 




Date 


Date 


DAP 


pop 


hgt 


Oct 24 


73 


ns 


- 


Oct 24 


61 


ns 


- 


Dec 7 


117 


* 


- 


Dec 11 


109 


ns 


- 


Jan 2 


143 


* 


- 


Jan 2 


131 


ns 


- 


23 


164 


ns 


ns 


23 


152 


ns 


- 


Feb 6 


178 


ns 


s 


Feb 6 


166 


ns 


- 


Marl 


201 


ns 


ns 


Marl 


189 


ns 


- 


15 


215 


ns 


ns 


15 


203 


ns 


- 


26 


226 


ns 


ns 


Apr 2 


221 


ns 


- 


Apr 2 


233 


ns 


ns 


May 1 


250 


ns 


ns 


May 1 


262 


ns 


ns 


16 


265 


ns 


ns 


16 


277 


ns 


ns 


Jun 1 


281 


ns 


ns 


Jun 1 


293 


ns 


ns 


12 


292 


ns 


ns 


12 


304 


ns 


ns 


27 


307 


- 


ns 


27 


319 


ns 


ns 


28 


308 


ns 


- 


Jul 18 


340 


ns 


ns 


Jul 18 


328 


ns 


ns 


27 


349 


ns 


ns 


27 


337 


ns 


ns 


Aug 9 


362 


ns 


ns 


Aug 9 


350 


ns 


ns 



Differences between treatments means were statistically significant at the 10% (s) or 5% (*) level, 
or were not significantly different (ns). 



57 



Wiedenfeld: Enhanced Sugarcane Esteblishment Using Plant Growth Regulators 



shoot count 



stalk height 



25 
20 
15 
10 

5 - 


20 
15 
10 

5 


20 
15 
10 

5 


20- 
15 
10 

5 


20 
15 
10 

5 






CP70-321 • • 

5 g_S 



CP71-1240 




^R*^5 



CP72-1210 




CP80-1827 




TCP87-3388 




Mar Apr May Jun Jul Aug 




May Jun 



Jul Aug 



ethephon standing 
ethephon in-furrow 
glyphosate standing 
check 



Figure 1 . Sugarcane shoot counts and heights over time for different cultivars showing the effect 
of ethephon and glyphosate on standing cane and ethephon application in-furrow vs. a check in the 
1 st year of the study. 



58 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 




stalk height 




May Jun Jul Aug 



Sep 



single, untreated 
single, ethephon 
double, untreated 
double, ethephon 



1 



Figure 2. Sugarcane shoot counts and heights over time for different cultivars showing the effect 
of ethephon vs. untreated at single and double overlap planting rates in the 2 nd year of the study. 



59 



Wiedenfeld: Enhanced Sugarcane Esteblishment Using Plant Growth Regulators 



shoot count 



40 




<U 

£ 20 



10 



Hiler farm * 

o 



Beckwith farm 




stalk height 




Oct Nov Dec Jan Feb Mar Apr May Jun 



Jan Feb Mar Apr May Jun Jul Aug 



reduced, untreated 
reduced, ethephon 
standard, untreated 
standard, ethephon 



Figure 3. Sugarcane shoot counts and heights over time for two different locations and cultivars 
showing the effect of ethephon vs. untreated at reduced and standard planting rates in the 3 rd year of 
the study. 



60 



. 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

ESTIMATING THE FAMILY PERFORMANCE OF SUGARCANE CROSSES USING 

SMALL PROGENY TEST 

P.Y.P. Tai 1 *, J. M. Shine, Jr. 2 , J. D. Miller 1 , and S. J. Edme 1 

'USDA-ARS Sugarcane Field Station 

Canal Point, FL. 

2 Florida Sugar Cane League, Inc., Clewiston, FL. 

(Currently Sugar Cane Growers Cooperative of Florida 

Belle Glade, FL.) 

* Corresponding author: ptai(g),saa.ars.usda.gov 

ABSTRACT 

Improvement of sugarcane seedling populations by eliminating inferior progeny should 
increase the frequency of elite clones and increase the selection efficiency. The objective of this 
study was to evaluate the effectiveness of a progeny testing technique using a progeny performance 
test with a small number of seedlings per cross. Approximately seventy seedlings per cross from 
the seed germination tests of 1987, 1988, and 1989 cross series were transplanted to the field along 
with the regular seedling program. Selection rate and visual grade were assessed on each cross and 
forty seedlings were randomly selected for the measurement of stalk diameter, stalk number, stalk 
weight, and juice quality on each progeny. Selected Stage I clones were planted in Stage II tests for 
the measurement of juice quality. Multiple regression analyses were used to select the best 
predictive model for the progeny performance based on the selection rate. Results indicated that the 
frequency distribution of selection rates of all three cross series was markedly skewed toward higher 
performance in both small progeny tests and the regular seedling program. Stalk diameter was the 
best predictor of the selection rate within the regular seedling program. Information obtained from 
small progeny tests should help breeders select superior crosses to increase the incidence of elite 
clones for their regular seedling program. 

INTRODUCTION 

The Canal Point sugarcane variety development program (Tai and Miller, 1989) annually 
evaluates approximately 100,000 seedlings. Improvement of sugarcane seedling populations by 
eliminating inferior progeny would increase the frequency of superior seedlings and increase 
selection efficiency. Selection in original seedlings is intended to obtain some superior varieties, and 
to improve the average value of the whole population (Hogarth, 1987). There are numerous 
difficulties during the early stages of selection including the large number of clones, performance 
differences to be expected from single stools, later from the necessarily small plots, and the 
subjective nature of selection at this stage (Arceneaux et al., 1986). Numerous experiments have 
been conducted to assess the effectiveness of selection for a particular character or set of characters, 
the correlations between such characters, and prediction of response to selection (Brown et al., 1 968; 
Hogarth, 1971; Miller and James, 1975; Miller et al., 1978; Tai and Miller, 1989; Walker, 1965). 
Walker (1965) reported that Brix is a better selection criterion because of its high correlation 
between stages, and stalk number is also a reasonably good selection criterion, but cane weight is 
not very reliable. Sugar content is poorly correlated at the two ages and no attempt is made to select 

61 



Tai et al.: Estimating the Family Performance of Sugarcane Crosses Using Small Progeny Test 

for high sugar in these early ages. Tai et al. (1980) reported that stalk number, stalk weight, Brix, 
sucrose percent, and sugar per ton of cane were highly repeatable between selection stages (Stages 
II and HI), but tons of cane per hectare, and tons of sugar per hectare, were not repeatable between 
these two selection stages. In addition to selection for a single character, the selection index can 
be used by combining many important characters into a single measure (Hogarth , 1987). Miller et 
al. (1 978) used stalk length, stalk diameter, stalk number, and Brix to construct a selection index for 
tonnes of sugar per hectare. Direct measurement of many important characters of sugarcane is time 
consuming and expensive. Sugarcane breeders have used grading systems (visual rating) to evaluate 
the potential commercial value of clones (Skinner, 1 967). Grading is less accurate but less expensive 
than the selection index. 

Several methods have been proposed for estimating the potential of sugarcane families to 
produce superior seedlings (elite genotypes), including factors for superior performance (FSP) by 
Arceneaux et al. ( 1 986), the probability of exceeding a target value (PROB) (Milligan and Legendre, 
1991), and a univariate cross prediction method (Chang and Milligan, 1992). The factors for 
superior performance (FSP) method is easy to use, but a FSP value can only be obtained after the 
original seedlings have been carried through all stages of selections. The univariate cross prediction 
method described by Chang and Milligan (1992) requires extensive data collection. 

The selection percentage is a measure of the overall merit of the cross which represents all 
the aspects of desirability considered in these stages and the weight given to each component 
character by the selector (Walker, 1963). A high selection percentage indicates that the population 
had a high mean and/or variance for some or all desirable characters. Tai and Miller (1989) reported 
that selection rate between early stages of selection was highly correlated. 

A progeny test with small number of individuals is routinely used to estimate the selection 
rate for the evaluation of proven crosses in sugarcane breeding programs in Australia (Hogarth, 
1 987). The progeny assessment trials also have been routinely used to identify the best families and 
select the superior clones from these families (Cox et al. 2000). Wu et al. (1978) studied the 
minimum sample size as the minimum number of individual sugarcane seedlings or stools necessary 
to estimate, with reasonable precision, mean and variance of a trial in a population and found forty 
individuals from a population to be the minimum sample size required to estimate the mean and 
variance for refractometer solids (Brix), stalk number, stalk diameter, or stalk length. 

The objective of this study was to evaluate the effectiveness of using small numbers of 
seedlings per cross to estimate the progeny performance of families based on the selection rate. 



MATERIALS AND METHODS 

Progeny tests were established in each May of 1988, 1989, and 1990 by planting 70 to 100 
seedlings per cross from the regular seed germination tests for 1987 (33 entries), 1988 (44 entries), 
and 1 989 (29 entries) cross series, respectively. Those seedlings were transplanted to the field in two 
rows 1 .5 m apart with 0.3 m between seedlings within a row. A visual rating (Rl) (poor = 1, fair 
= 3, and good = 5) was made on each cross in early December of the same year. Data on stalk 
diameter (Dl) were collected from up to five stalks for each of those 40 seedlings picked at random 

62 






Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

in late December. Stalk diameter was measured near the mid-internode at 0.30 m above ground level 
and the number of millable stalks for each seedling was recorded. Stool weight (Kl ) was calculated 
by multiplying the stalk weight (Wl) by the stalk number (Nl ). Data on stool weight were obtained 
from both the 1988 and the 1989 cross series. One stalk was cut from each of 40 seedling stools. 
The resulting 40-stalk bundle per cross was weighed and divided at random into two sub-samples, 
20 stalks each, for juice analysis. The average Brix or sucrose from the two sub-samples was used 
for all statistical analyses. 

Selection using the same criteria as the regular seedling program (Tai and Miller, 1 989) was 
conducted in early January. Selection rate from the progeny test (SRI) (%) was computed as: 
(selected seedlings/number of seedlings of each progeny sample) X 100. Approximately 600 to 
1,000 seedlings for each of those same crosses used in the progeny test were planted in the regular 
seedling program in the following year (CP 90, CP 91 and CP 92 clones selected from 1987, 1988, 
and 1989 cross series, respectively) . Selection rates for the regular seedling stage (SR2) (%) were 
computed as: (selected seedlings/number of regular seedlings per cross) X 100. One stalk 
(approximately 1 m long) from each of those selected seedlings was cut in January each year and 
planted as Stage I in a single-row plot in 1 .5 m between rows and 0.6 m apart between plots. Plant- 
cane selection of Stage I clones was conducted in September of each year. Selection rate for Stage 
I (SR3) (%) was computed as (selected Stage I clones/original seedlings per cross) X 100. Each 
selected Stage I clones was advanced to Stage II (Tai and Miller, 1989). An eight-stalk seed cane 
sample was cut from each selected clone in Stage I and used to establish a 2-row plot 4.6 m long and 
1.5 m wide in Stage II in October each year. Juice quality data were based on the Stage II samples 
harvested the following October. Juice quality was not measured on selections made in Stage I, the 
average of juice quality measurements from Stage II clones in each cross was used for all statistical 
analyses. 

Predicting the selection rate (%) for progeny sample (SRI ), regular seedling (SR2), and Stage 
I (SR3) was made by regression analysis (SAS, 1988) using the progeny assessment data on stalk 
diameter, stalk weight, and visual rating. The multiple regression of dependent variables, selection 
rates (SRI, SR2, and SR3), on stalk diameter (Dl), stalk weight (Wl), stalk number (Nl), stool 
weight (Kl), and visual rating (Rl) based on the progeny test for each cross series were analyzed. 
The GLM procedure (SAS, 1988) was used to select the best predictive models for SRI, SR2 or 
SR3. 

RESULTS AND DISCUSSION 

The seedlings of the regular Seedling Stage generally had lower stalk weight and juice quality 
than the selected Stage I clones tested in Stage II (Table 1 ). Visual rating of three cross series ranged 
from 3.48 to 4.0 and their selection rates exceeded 20%. The results also indicate that the plant 
measurements for stalk characters and juice quality factors in Seedling Stage were smaller than those 
in Stage n. Those differences could be due to the plant development stage and the growth 
environment. The seedlings were developed from the true seed with a limited food supply while 
Stage U clones developed from buds with adequate food supply from the cane stalks. DeSousa- 
Vieira and Milligan (1999) showed that the plant spacing greatly affects stalk number and its 
variances. 



63 



Tai et al.: Estimating the Family Performance of Sugarcane Crosses Using Small Progeny Test 

Progeny tests suggest that a visual rating (Rl ) was closely associated with stalk diameter (D 1 ) 
(r = 0.43** for 1987 cross series, r = 0.37** for 1988 cross series, and r = 0.65** for 1989 cross 
series), while Rl was not consistently associated with stalk weight (Wl) (r = 0.83** for 1987 cross 
series and r = 0.41** 1989 cross series were significant, but r = 0.24 for 1988 cross series was not 
significant, Table 2). Dl and Wl were positively correlated. Both the selection rate for progeny 
sample (SRI) and the selection rate for the regular seedling (SR2) were closely correlated with either 
Dl or Wl in both the 1987 and 1989 cross series. Both selection rates, SRI and SR2, were strongly 
affected by both Dl and Wl as shown in both the 1988 and 1989 cross series, while the selection 
rate for the Stage I clones (SR3) was affected by neither trait. In most crosses, Rl was not 
significantly correlated with SRI, SR2, or SR3. SR2 was positively associated with SR3 in three 
cross series. 

Correlations of juice quality between the progeny tests and selected Stage I clones were 
inconsistent. The 1987 crosses gave significant correlations while 1988 and 1989 cross series were 
not significant (Table 3). The inconsistency could be due to both plant growth stages and field 
environment (DeSousa-Vieira and Milligan, 1 999). The seedlings and Stage II were planted at a very 
different intra-row spacing. This may explain why the selection rate from Seedling Stage to Stage 
I was not well correlated to stalk weight. The stalk diameter varied considerably among individual 
seedlings within a cross. Also the composite stalk sample, which consisted of one stalk per seedling 
stool, would not have an equal amount of cane juice or cane stalk weight representing each stool. 
The measurement may not closely represent the juice quality of seedlings. Maturity, which also 
varied considerably among seedlings and between crosses, would affect the quality of cane juice. 
Correlations between traits shows they were changing rather than static and would be affected by 
cane growth and maturity (Dodonov et al. 1987; Tai et al. 1996). Family selection based on the 
mean of some traits may not be very effective in the early stages of selection. The selection rate 
between Seedling Stage and Stage I was significantly correlated in all three series of crosses as 
reported earlier by Tai and Miller (1989). The results suggest that family selection based on the 
selection rate should be effective. The larger the number of superior families included in the 
Seedling Stage, the higher percentage of superior individual clones will be potentially selected for 
the Stage I and the subsequent selection stages. 

The multiple regressions for SRI, SR2, and SR3 are summarized in Table 4. The best 
regression models varied among the progeny test, Seedling Stage, and Stage I. Results indicate that 
the selection rate would be heavily dependent on stalk diameter D 1 and (D 1 ) 2 in the Seedling Stage. 
Other predictor variables were not chosen for the model for SR2 in any of the three cross series. 
Both the 1987 and 1989 crosses had very similar regression models for SR2, but they differed from 
that of the 1 988 crosses. The quadratic regression model suggests that seedlings with either very thin 
or very thick stalks would drastically reduce the selection rate (Fig. 1). Seedling populations with 
an average stalk diameter between 2 1 and 25 mm would produce the highest selection rate. Predictor 
variables, stalk diameter (Dl) and stalk number (Nl), were chosen for the model for SR3 in the 1 988 
cross series and (R1)(W1) was chosen for the model in the 1989 cross series, but no predictor 
variable was chosen for the model for SR3 in 1987 cross series. The difference in the prediction 
models for SR2 and SR3 could be due to many factors. Stalk size of Stage I clones is generally 
much larger than that of the Seedling Stage due to selection for larger stalk diameter in the Seedling 
Stage (Tai and Miller, 1989). The selection criteria in Stages I and II emphasize other characters, 
such as stalk number, stalk shape, growth habit, solidness, plant height, etc, versus stalk diameter. 

64 






Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Both stalk number (Nl) and rating (Rl) x stalk weight (Wl) appeared to be more predictive of 
selection rate in Stage I than stalk diameter (Dl) based on the progeny test. DeSousa-Vieira and 
Milligan ( 1 999) pointed out that the predicted family gains for millable stalk number per plant, stalk 
length and stalk weight using widely spaced plants would be more accurate than using narrowly 
spaced plants. 

A progeny test with a small number of seedlings per cross should eliminate some of the poor 
crosses before a large population of seedlings is planted for the selection program. Adjusted R- 
squares of some regression models were relatively small; therefore, the effectiveness of predicting 
the selection rate might be low. Further study is needed to improve the regression model to estimate 
the selection rate. Even though individual (mass) selection can be more effective in maintaining 
genetic diversity of the seedling population than family selection, individual selection may not be 
the most efficient way to manage a seedling program. The progeny test to assess the potential 
performance of seedling progeny should benefit the selection program by planting larger numbers 
of the best progenies in the regular seedling program. 

ACKNOWLEDGMENTS 

The authors are grateful to Victor Chew for his assistance in testing the regression models. 

REFERENCES 

1 . Arceneaux, G., J. F. Van Breemen, and J. O. Despradel. 1986. A new approach in sugar cane 
breeding: comparative study of progenies for incidence of superior seedlings. Sugar Cane 1 986 
(1):7-10. 

2. Brown, A. H. D., J. Daniel, and B. D. H. Latter. 1968. Quantitative genetics of sugarcane, n. 
Correlation analysis of continuous characters in relation to hybrid sugarcane breeding. Theor. 
Appl. Genet. 38:1-10. 

3. Chang, Y. S., and S. B. Milligan. 1992. Estimating the potential of sugarcane families to 
produce elite genotypes using univariate cross prediction methods. Theor. Appl. Genet. 84:662- 
671. 

4. Cox, M.C., D. M. Hogarth, and G. R. Smith. 2000. Cane breeding and improvement. In D. M. 
Hogarth,, and P. G. Allsopp (eds.). Manual of Cane Growing. Bureau of Sugar Experiment 
Stations, Brisbane, Queensland, Aust., pp. 91-108. 

5. DeSousa-Vieira, O., and S. B. Milligan. 1999. Intra-row plant spacing and family x environment 
interaction effects on sugarcane family evaluation, Crop Sci. 39: 358-364. 

6. Dodonov, G. P., D. A. Cherepanov, 1. 1. Raponovich, and O. S. Melik-Sarkisov. 1 987. Variation 
and correlation of morphophysiological traits of sugarcane during ontogeny and their selection 
of seedlings. Soviet Agricultural Biology: Part 1 :Plant Biology 1987 (3):79-87. Allerton Press, 
New York. 



65 



Tai et al.: Estimating the Family Performance of Sugarcane Crosses Using Small Progeny Test 

7. Hogarth, D. M, 1971 . Quantitative inheritance studies, n. Correlation and predicted response 
to selection. Aust. J. agric. Res. 22:103-109. 

8. Hogarth, D. M. 1987. Genetics of sugarcane. In D. J. Heinz (editor), Sugarcane Improvement 
Through Breeding. Elsvier, New York. Pp. 255-272. 

9. Miller, J. D., N. I. James, and P. M. Lyrene. 1978. Selection indices in sugarcane. Crop Sci. 
18:368-372. 

10. Miller, J. D., andN. I. James. 1975. Selection in six crops of sugarcane. I. Repeatability of three 
characters. Crop Sci. 15:23-25. 

11. Milligan, S. B., and B. L. Legendre. 1991. Development of a practical method for sugarcane 
cross appraisal. J. Am. Soc. Sugarcane Technol. 11:59-68. 

12. SAS Institute. 1988. SAS/SAT User's Guide 6.03ed. SAS Inst. Inc., Cary, NC. 

13. Skinner, J. C. 1967. Grading varieties for selection. Proc. ISSCT 12:938-949. 

14. Tai, P. Y. P., J. D. Miller, B. S. Gill, and V. Chew. 1980. Correlations among characters of 
sugarcane in two intermediate selection stages. Proc. ISSCT 16:1 1 19-1 126. 

15. Tai, P. Y. P., and J. D. Miller. 1989. Family performance at early stages of selection and 
frequency of superior clones from crosses among Canal Point cultivars of sugarcane. J. Am. 
Soc. Sugarcane Technol. 9:62-70. 

16. Tai, P. Y. P., G. Powell, R. Perdomo, and B. R. Eiland 1996. Changes in sucrose and fiber 
contents during sugarcane maturation. Sugar Cane 1996(6): 19-23. 

1 7. Walker, D. I. T. 1963. Family performance at early selection stages as a guide to the breeding 
programme. Proc. ISSCT 11:469-483. 

18. Walker, D. I. T. 1965. Some correlations in sugarcane selection in Barbados. Proc. ISSCT 
12:650-655. 

19. Wu, K. K., D. J. Heinz, H. K. Meyer, and S. L. Ladd. 1978. Minimum sample size for 
estimating progeny mean and variance. Crop Sci. 18:57-61. 



66 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Table 3. Correlation coefficients of juice quality characters between small progeny test and selected 
Stage I clones (CP 90 series from 1987 cross series, CP 91 series from 1988 cross series, and CP 92 
series from 1989 cross series) tested in Stage H 

Correlation between* Brix Sucrose Purity 

1987 Crosses and selected CP 90 clones 0.40* 0.35* 0.36* 

1988 Crosses and selected CP 91 clones 0.12 0.15 0.23 

1989 Crosses and selected CP 92 clones O20 024 018 

* Significant at P = 0.05. 

f Data on Brix, sucrose, and purity were based on samples collected from Stage II test. 



69 






Tai et al.: Estimating the Family Performance of Sugarcane Crosses Using Small Progeny Test 



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70 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

INCIDENCE AND SPREAD OF SUGARCANE YELLOW LEAF VIRUS IN 
SUGARCANE CLONES IN THE CP-CULTIVAR DEVELOPMENT PROGRAM AT 

CANAL POINT 

J. C. Comstock and J. D. Miller 

Sugarcane Field Station, USDA-ARS, Canal Point, FL 33438 

ABSTRACT 

The incidence of sugarcane yellow leaf virus (SCYLV) in sugarcane clones increased the 
longer the clones were in the CP-cultivar development program and exposed to natural infection. 
During 1998 to 2002, the average incidence of SCYLV in Stage II clones was 30.1 %, while 
SCYLV incidence in Stage IV clones, in the program 3 years longer, was 55.6 %. A few clones 
had an incidence of SCYLV below 25 % by the time they were advanced to Stage IV. These 
clones may have partial resistance to the virus. The results have implications for breeding and 
selecting for resistance to the virus. 

INTRODUCTION 

Sugarcane yellow leaf syndrome was recognized in Hawaii in the 1980s and was 
subsequently observed in numerous countries (Comstock et al, 2002b; Izaguirre-Mayoral et al, 
2002; Lockhart et al, 1996; Lockhart and Cronje, 2000; Vega et al, 1997; Viswanathan, 2002). 
Two different pathogens, sugarcane yellow leaf phytoplasma and sugarcane yellow leaf virus 
(SCYLV) have been associated with the sugarcane yellow leaf syndrome symptoms (Cronje et 
al., 1998; Lockhart et al, 2000; Scagliusi and Lockhart, 2000). In Florida, only SCYLV has 
been reported (Comstock et al, 1998). Disease losses of 25 % in Brazil in SP 71-6163 have 
been attributed to SCYLV (Vega et al, 1997). Yield losses of 15 to 20 % also have been 
reported due to yellow leaf virus in Louisiana (Grisham et al, 2002). Elevated Brix readings of 
juice extracted from the midribs of symptomatic leaves have been reported (Comstock et al, 
1994). Differences in leaf area, total reducing sugars, chlorophyll content, and sugar transport 
were observed between symptomatic and asymptomatic plants infected with SCYLV (Izaguirre- 
Mayoral et al, 2002; Viswanathan, 2002). All reported changes negatively impact sugar yield. 

Symptoms of SCYLV are more evident in mature and stressed plants (Lockhart and 
Cronje, 2000). Only isolated plants exhibit symptoms in Florida before the start of the harvest 
season that begins in mid-October. Symptoms start as the weather turns cooler in October- 
November, initially with the lower midrib of leaves 3 to 6 (counting from the top expanding 
leave downward) becoming yellow. The yellowing then expands into the leaf blade with 
necrosis starting from the leaf tip and progressing down the leaf blade becoming most evident in 
December until the end of the harvest season in March. During January through March, entire 
fields may appear yellowish. 

This paper addresses SCYLV in the CP-cultivar development program in Florida. 
Symptoms of the syndrome were observed in 1994 in clones that were used in crossing at the 
USDA Sugarcane Field Station at Canal Point, Florida (Comstock et al., 1994). The presence of 
SCYLV was confirmed by a serological tissue blot assay using a SCYLV specific antibody 
(Comstock et al, 2002a; Comstock et al, 1999) and a reverse transcriptase polymerase chain 



71 



Comstock and Miller: Incidence and Spread of Sugarcane Yellow Leaf Virus in Sugarcane Clones in the CP-Cultivar Development Program at 

Canal Point 

reaction assay using primers to detect the virus (Comstock et ah, 1998). There are no reports of 
the sugarcane yellow leaf phytoplasma in Florida. 

The objectives of this paper are: 1) to determine the variability of incidence of SCYLV in 
clones in the CP-cultivar development program at Canal Point, Florida, 2) to determine if the 
incidence of SCYLV increases in the clones with time, 3) to determine if resistance exists in the 
current selection program and 4) to determine if natural infection can be used to select clones 
resistant to the virus. 

MATERIALS AND METHODS 

Surveys 

Plants of sugarcane clones in Stages II through IV (four sequential years) of the CP- 
cultivar development program (USDA-ARS Sugarcane Field Station, Canal Point, Florida) were 
surveyed for the presence of SCYLV for 5 years, during 1998 through 2002. The number of 
clones, plants sampled, and locations of plots in the cultivar development program that were 
sampled during 1998 to 2002 are presented in Table 1. The incidence of SCYLV infection of the 
clones in each CP Series was an average of the incidence of all the clones based on the number 
of infected leaf samples divided by the total number of leaves sampled and assayed in that year 
and selection stage. 

Tissue Blot Immunoassays 

SCYLV infection was determined by assaying for the presence of the virus in the 
youngest fully emerged leaf by a tissue blot immunoassay using antibodies specific for the virus. 
Briefly, the leaf was removed from a plant and the leaf blade tissue was removed from the 
midrib. The basal portion of the midrib was cut with a sharp, razor-blade scalpel, and the freshly 
cut midrib was firmly pressed on a nitrocellulose membrane, leaving a clear impression of the 
leaf midrib on the membrane. One impression per leaf midrib was made. The membrane was 
serologically developed using SCYLV specific antibodies developed by B. E. Lockhart, 
University of Minnesota (Minneapolis) according to Schenck et al. (1997) except that Fast Blue 
was used as the enzyme substrate (Comstock et al., 1998). A stereo-microscope was used to 
examine the leaf prints. Because SCYLV is located in the phloem, a sample was positive for the 
presence of the virus when the phloem bundles within the leaf print stained blue. 

RESULTS AND DISCUSSION 

The incidence of SCYLV infection among clones for each CP Series in Stage II through 
IV for years 1998 through 2002 is shown in Table 1. For each CP Series, the incidence of 
samples with SCYLV generally increased the longer the series was in the cultivar development 
program. The average yearly incidence of SCYLV infected clones in Stage II ranged from 25.6 
to 32.0 % during the five years that they were sampled. The incidence of SCYLV infection 
among all clones that were advanced to Stage IV during the same period ranged from 41.2 to 
66.8 % (Table 1). The average incidence of SCYLV in Stage II was 30.1 % for years 1998- 
2002 and increased to 55.6 % in Stage IV. These results plus the fact that the incidence of 
SCYLV among plants in grower's fields in Florida exceeds 85% clearly indicates a possible 



72 






Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

threat of SCYLV in Florida. The virus is present in essentially all commercial CP-cultivars. 
The high incidence of infection in the selected population indicated that there is little resistance 
among CP sugarcane clones. Almost all parental clones used for crossing in the cultivar 
development program are infected with the virus or have symptoms indicating a lack of SCYLV 
resistance for the crossing program (Comstock et al., 1998; Miller et al., 1994). 

In Venezuela, there were clear reductions in yield parameters between symptomatic and 
asymptomatic plants that are infected with the virus. However, without severe symptom 
development, the yield losses were not dramatic (Izaguirre-Mayoral et al., 2002). In India, in 
similar comparisons of yield parameters between symptomatic versus asymptomatic plants, 
reduced stalk diameter, lower Brix readings, and lower photosynthetic rates were associated with 
symptomatic plants. SCYLV infection was based on visual symptoms and not on detecting the 
virus in test plants. However, serological tests confirmed the presence of the virus in most plants 
suspected of being infected in a separate diagnostic test (Viswanathan, 2002). 

The incidence of SCYLV in the CP 95 through CP 98 Series clones is shown at each 
stage as they moved through the program from Stage II to Stage IV trials (Tables 2-5). Six 
individual clones (CP 96-1865, CP 97-1164, CP 97-1850, CP 97-1944, CP 97-1989 and CP 97- 
2068) had an incidence of SCYLV infection of 20 % or less in Stage IV. These clones 
presumably have some resistance to SCYLV infection, since there was equal opportunity for 
infection with other clones in field trials during the 7 years of testing after being derived from 
true seed. These clones with less than 20 % incidence of SCYLV infection apparently had a 
partial resistance. The clones had no common parentage. 

The high increase in incidence of SCYLV in the cultivar development program indicates 
that little resistance has been incorporated using the present parental clones. An effort to 
introduce resistance from sources other than the CP clones presently used for breeding would 
assist in the development of SCYLV resistant clones. Clones of Saccharum spontaneum appear 
to be a good choice, since only seven of 100 clones surveyed in the World Collection at Miami 
were infected with SCYLV compared to 75 % of the S. qfficinarum clones (Comstock et al., 
2002a). Others have reported S. spontaneum clones as having a low incidence of infection 
(Schenck et al., 1997). An alternative breeding option would be to use imported commercial 
clones that are reported resistant. Eight Hawaiian varieties (H varieties) with SCYLV resistance 
have been imported via the USDA quarantine for use in crossing. Additionally, several clones 
that appear to have partial resistance, since less than 25 % of the plants sampled were SCYLV 
infected in Stage IV, will be evaluated on their potential to produce resistant progeny. Their 
progeny also would be more commercially acceptable and therefore, more desirable than using 
wild & spontaneum clones and imported commercial clones as parents. 

A major restriction in incorporating resistance is a lack of an efficient method of 
inoculating plants to evaluate resistance. Although the spread of SCYLV is relatively fast, it is 
not fast enough to allow efficient screening of populations for the incorporation of resistance into 
a cultivar development program. Several years are required to insure adequate exposure of 
plants relying on natural infection by aphids. A period of 3-5 years to evaluate resistance 
restricts the cultivar development program. The low number of virus-free clones or clones with a 
low incidence of infection that remains after a 3-5 year exposure period is totally inadequate. 



73 



Comstock and Miller: Incidence and Spread of Sugarcane Yellow Leaf Virus in Sugarcane Clones in the CP-Cultivar Development Program at 

Canal Point 

Methodology to inoculate massive numbers of plants using insectary aphids is needed but 
probably not feasible since the numbers of clones that can be evaluated will still be limited. 
Once the plants are inoculated, virus detection in plants is not a limitation since the tissue blot 
immunoassay allows the rapid determination of the presence of SCYLV in thousands of plants. 

As an alternative to detecting resistant plants, a project to associate molecular markers 
with the resistance is in progress. If marker assisted selection can be developed for SCYLV 
resistance, the process for the development of resistant cultivars would be greatly enhanced. 

REFERENCES 

1. Comstock, J. C, J. E. Irvine, and J. D. Miller, 1994. Yellow leaf syndrome appears on the 
United States mainland. Sugar J. 56:33-35. 

2. Comstock, J. C, J. D. Miller, and R. J. Schnell, 2002a. Incidence of sugarcane yellow leaf 
virus in clones maintained in the world collection of sugarcane and related grasses at the 
United States National Repository in Miami, Florida. Sugar Tech 3:128-133. 

3. Comstock, J. C, J. D. Miller, P. Y. P. Tai, and J. E. Follis, 1999. Incidence of and 
resistance to sugarcane yellow leaf virus in Florida. Proceedings International Soc. Sugar 
Cane Technol. 23:366-372. 

4. Comstock, J. C, M. Pena, J. Vega, A. Fors, and B. E. L. Lockhart, 2000b. Report of 
Sugarcane Yellow Leaf Virus (SCYLV) in Ecuador, Guatemala and Nicaragua. Plant Dis. 
86:74. ; 

5. Comstock, J. C, M. S. Irey, B. E. L. Lockhart, and Z. K. Wang, 1998. Incidence of yellow 
leaf syndrome in CP cultivars based on polymerase chain reaction and serological 
techniques. Sugar Cane 4:21-24. 

6. Cronje, C. P. R., A. M. Timon, P. Jones, and R. A. Bailey, 1998. Association of a 
phytoplasma with yellow leaf syndrome of sugarcane in Africa. Ann. Appl. Biol. 133:177- 
186. 

7. Grisham, M. P., Y-B. Pan, B. L. Legendre, M. A. Godshall, and G. Eggleston, 2002. Effect 
of sugarcane yellow leaf virus on sugarcane yield and juice quality. Proc. Int. Soc. Sugar 
Cane Technol. 24:434-438. 

8. Izaguirre-Mayoral, M. L., O. Carballo, C. Aleste, M. Romano, and H. A. Nass, 2002. 
Physiological performance of asymptomatic and yellow leaf syndrome-affected sugarcane 
in Venezuela. J. Phytopathol. 150:13-19. 

9. Lockhart, B. E. L., M. S. Irey, and J. C. Comstock, 1996. Sugarcane bacilliform virus, 
sugarcane mild mosaic virus, and sugarcane yellow leaf syndrome. Pages 108-112 in: 
Sugarcane germplasm conservation and exchange. B. J. Croft, C. T. Piggin, E. S. Wallis, 
and D. M. Hogarth, editors. Australian Centre for International Agricultural Research. 



74 









._. 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

10. Lockhart, B. E. and C. P. R. Cronje, 2000. Yellow leaf syndrome. Pages 291-295 in: Rott, 
P., Bailey, R. A., Comstock, J. C, Croft, B. J. and Saumtally, A. S. (eds) A guide to 
sugarcane diseases. Centre de cooperation intemationale en recherche agronomique pour le 
developpment (CIRAD) and International Society of Sugar Cane Technologists (ISSCT) 
Montpellier, France. 339 pp. 

11. Miller, J. D., B. L Legendre, M. P. Grisham, J. C. Comstock, W. H. White, and D. M. 
Burner, 1994. Impact of leaf scald and yellow leaf syndrome on parental clones for use in 
1994-1995 crossing season at Canal Point. Sugar Bulletin 72: 6, 19-22, 24-26, 28-29. 

12. Scagliusi, S. M., and B. E. L. Lockhart, 2000. Transmission, characterization, and serology 
of a luteovirus associated with yellow leaf syndrome of sugarcane. Phytopathology 90:120- 
124. 

13. Schenck, S., B. E. Lockhart, and J. S. Hu, 1997. Use of a tissue blot immunoassay to 
determine the distribution of sugarcane yellow leaf virus in Hawaii. Sugar Cane 4:5-8. 

14. Vega, J., S. M. Scagliusi, and E. C. Ulian. 1997. Sugarcane yellow leaf disease in Brazil 
evidence of association with a luteovirus. Plant Dis. 81:21-26. 

15. Viswanathan, R. 2002. Sugarcane yellow leaf syndrome in India: Incidence and effect on 
yield parameters. Sugar Cane Int. September/October pp. 17-23. 



75 



Comstock and Miller: Incidence and Spread of Sugarcane Yellow Leaf Virus in Sugarcane Clones in the CP-Cultivar Development Program at 

Canal Point 

Table 1. Incidence of SCYLV in clones in the CP-cultivar development program. 





1998 


1999 


2000 


2001 


2002 


Overall 
mean 


Stage II 














Series 


CP97 


CP98 


CP99 


CP00 


CP01 




No. clones 


1008 


957 


854 


463 


1423 




Leaves/clone 


1 (2 dates) 


1 


1 


3 


1 




Location 


CP Station 


CP Station 


CP Station 


CP Station 


CP Station 




% Positive 3 


25.6 % 


38.3 % 


27.8 % 


32.0 % 


27.0 % 


30.1 % 


Stage III 










s 




Series 


CP96 


CP97 


CP98 


CP99 


CP00 




No. clones 


130 


130 


130 


130 


130 




Leaves/clone 


20 


10 


10 


10 


10 




Location 


Sugar 


Sugar 


Sugar 


— 


— 






Farms 46.7 


Farms 


Farms 


~ 


— 




% Positive 3 


% 


24.0 % 


35.4 % 


— 


~ 


35.4 % 


Location 


— 


Duda 


Duda 


Duda 


Duda 




% Positive 3 


~ 


23.9 % 


31.3% 


36.4 % 


55.6 % 


36.8 % 


Stage III Inc. 














Series 


CP95 


CP96 


CP97 


CP98 


CP99 




No. clones 


40 


40 


40 


40 


28 




Leaves/clone 


20 


10 


10 


10 


10 




Location 


Sugar 
Farms 


Sugar 
Farms 


Duda 


Duda 


Duda 




% Positive 3 


55.3 % 


49.3 % 


26.6 % 


48.8 % 


51.4% 


46.3 % 


Stage IV 














Series 


CP94 


CP95 


CP96 


CP97 


CP98 




No. clones 


11 


11 


11 


14 


14 




Leaves/clone 


80 


40 


40 


40 


40 




Location 


Sugar 


Sugar 


Duda 


Duda 


Duda 




% Positive 3 


Farms 


Farms 












66.8 % 


54.8 % 


54.8% 


41.2% 


60.2 % 


55.6 % 



3 % positive is the number of leaves tested positive divided by the total number of leaves tested. 






76 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Table 2. Incidence of SCYLV in CP 95 Series clones during their advancement to Stage IV. 



Clone 


Stage 


Stage 


Stage III 


Stage 


Stage 




11/1996* 


HI/1997 


Increase/ 1998 


IY/1999 


IV /2000 








0/ 






CP 94-2203 


ND 





2.5 


42.7 


CP 95-1039 


+ 


100 


92 


100 


82.0 


CP 95-1076 


ND 


ND 


ND 


15 


71.0 


CP 95-1429 


— 





25 


42.5 


71.0 


CP 95-1446 


ND 


100 


ND 


100 


90.9 


CP 95-1569 


— 


40 


95 


15 


47.5 


CP 95-1570 


- 





30 


47.5 


78.3 


CP 95-1712 


- 


40 


30 


52.5 


80.0 


CP 95-1726 


+ 





100 


95 


90.7 


CP 95-1834 


+ 





100 


87.5 


70.0 


CP 95-1913 


- 


100 


45 


45 


84.5 



A single leaf assayed per clone: + is positive and - is negative. ND = no data. 



Table 3. Incidence of SCYLV in CP 96 Series clones during their advancement to Stage IV. 



Clone 



Stage n 
1997* 



Stage III 
1998 



Stage III Inc. 
1999 



Stage IV 
2000 



Stage IV 
ratoon/2001 



CP 96-1161 
CP 96-1171 
CP 96-1252 
CP 96-1253 
CP 96-1288 
CP 96-1290 
CP 96-1300 
CP 96-1350 
CP 96-1602 
CP 96-1686 
CP 96-1865 



-H-+ 



+ 



%• 



80 


70 


52.5 


90 


75 


100 


ND 


100 


40 


60 


95 


95 


100 


100 


100 


100 


55 


90 


47.5 


100 


20 


10 


27.5 


32.5 


80 


70 


90 


100 


7 


ND 


55 


75 


45 


50 


35 


100 


50 


30 


100 


42.5 


10 








17.5 



* Each + or - indicates the number of leaves sampled per clone: + is positive and - is negative. 
ND = no data. 



77 



Comstock and Miller: Incidence and Spread of Sugarcane Yellow Leaf Virus in Sugarcane Clones in the CP-Cultivar Development Program at 

Canal Point 

Table 4. Incidence of SCYLV in CP 97 Series clones during their advancement to Stage IV. 



Clone 


Stage 11/ 


Stage III/1999 


Stage III 


Stage TV/ 2001 


Stage IV 




1998 




Inc/2000 




ratoon/ 




* 








2002 










o/ 

47.5 




CP 97-1068 


— 


70 


80 


67.5 


CP 97-1164 


— 


10 








2.5 


CP 97-1362 


— 





ND 


47.5 


80 


CP 97-1387 


+ + 


90 


ND 


95 


22.5 


CP 97-1433 


— 


10 


50 


72.5 


ND 


CP 97-1777 


— 


30 





20 


47.5 


CP 97-1804 


- + 


100 


70 


100 


100 


CP 97-1850 


+ - 





ND 


2.5 


12.5 


CP 97-1928 


- + 


100 


ND 


50 


97.5 


CP 97-1944 


— 





40 





2.5 


CP 97-1979 


— 





10 


7.5 


27.5 


CP 97-1989 


— 





ND 


10 


20 


CP 97-1994 


— 








97.5 


42.5 


CP 97-2068 


— 


10 


ND 


26.7 


7.5 



* Each + or - indicates the number of leaves sampled per clone: + is positive and - is negative. 
ND = no data. 



Table 5. Incidence of SCYLV in CP 98 Series clones during their advancement to Stage IV. 



Clone 


Stage 11/ 1999* 


Stage III/ 2000 


Stage III Inc. 
2001 


Stage rW 2002 








o /o 




CP 98-1029 


+ 


80 


- 


100 


CP 98-1 107 


- 





10 


40 


CP 98-1118 


- 





30 


55 


CP 98-1 139 


- 





- 


22.5 


CP 98-1325 


- 





10 





CP 98-1335 


ND 





- 


100 


CP 98-1417 


- 


70 


- 


15 


CP 98-1457 


+ 


- 


100 


95 


CP 98-1481 


- 


- 


- 


12.5 


CP 98-1497 


— 


10 


- 


65 


CP 98-1513 


ND 


40 


60 


85 


CP 98-1569 


+ 


10 


- 


65 


CP 98-1725 


+ 


80 


- 


95 


CP 98-2047 


ND 


- 


80 


92.5 



A single leaf assayed per clone: + is positive and - is negative. ND = no data. 



78 



PEER 

REFEREED 

JOURNAL 

ARTICLES 

MANUFACTURING 
SECTION 



79 






Madsen et al.: Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 

EVALUATION OF A NEAR INFRARED SPECTROMETER FOR THE DIRECT 

ANALYSIS OF SUGAR CANE 

L.R. Madsen II, B.E. White, and P.W. Rein 

Audubon Sugar Institute 

Louisiana State University Agricultural Center 

Baton Rouge, LA 70803 



ABSTRACT 

A FOSS InfraCana Near Infrared (NIR) spectrometer was installed at a Louisiana mill for 
the 2001/02 crushing season to assess its suitability for direct analysis of cane delivered to the 
mill. Analysis of cane by both wet disintegration and core press methods were used as the 
primary measurements. Calibration equations for pol, brix, fiber, moisture and ash in cane were 
produced. Values of standard error were excellent, and the prospects for the use of such an 
instrument for the accurate direct analysis of cane look promising. 



INTRODUCTION 

Currently, the core-press method (CPM) of analysis is used in Louisiana for 
determination of sugar cane quality. The results of these determinations are used to calculate the 
theoretical recoverable sugar (TRS), in lbs sugar per ton of cane. TRS is used to determine how 
much a given grower will be paid for a consignment of cane. Methods similar to core press are 
currently used in many other cane-growing regions such as Colombia, Trinidad, and the 
Philippines (Edye and Clark, 1996). Core press analysis requires a team of at least three analysts 
per shift, for two eight-hour shifts. The time required for sample turn-around is roughly four 
hours. Since this method is intensive both in terms of time and labor, sampling every load is 
impossible. Usually, moisture % residue figures are not finally generated until the end of the 
shift; this means that the nature of the cane is not known until well after it has entered the mill. 
The goal of this investigation is to improve the quality of cane analysis whilst decreasing overall 
seasonal cost. 

The cost of cane analysis consists of personnel, supplies, and utilities. Supply costs 
include Octapol and/or ABC juice clarifier, glassware, and utilities. Loss of profit can result from 
inaccuracies in cane quality data and losses caused by mill stoppage. Increased rate of sampling 
and quicker analysis would not only result in a greater likelihood of achieving representative 
sampling, but may decrease down times caused by foreign material entering the mill. While 
examining new methodology, modern technology and high-speed computing has rendered near 
infrared reflectance spectroscopy (NIRS) worthy of inspection. The InfraCana uses large samples 
(5 to 15kg) so that sub-sampling for increased precision is unnecessary (Berding and Brotherton, 
1996). It is necessary to point out that NIR spectroscopy and chemometrics can provide a result 
that is only as good as the data put into it. When calibrated using quality data, these new 



80 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

instruments promise high-speed, increased analytical precision, and long-term net savings. These 
savings would directly improve profitability for both the farmers and the mills. 

NIR technology has been validated for quality control use in a wide variety of industries, 
including forage, fiber, grain, and cereal. FOSS provided a prototype InfraCana NIRS system to 
the Audubon Sugar Institute, which was installed at Cinclare mill in Louisiana for the 2001-02 
crushing season. The instrument was calibrated using data acquired via Direct Analysis of Cane 
(DAC), as specified in the International Commission for Uniform Methods of Sugar Analysis 
(ICUMSA 1994). The DAC results were compared to results achieved using the core press 
method. The NIRS was calibrated for pol, brix, fiber, moisture, ash % cane, and TRS using the 
WinlSI (Infrasoft) Chemometrics software package. The results of this calibration equation were 
subject to cross validation between laboratory results and the NIRS predicted values. The results 
of this cross-validation were key in the evaluation of the instrument as an alternative to CPM for 
purposes of cane payment. 



MATERIALS AND METHODS 



The NIRS 




Figure 1 . InfraCana Near Infrared Spectrometer. 

The NIRS consists of four major components (Figure 1). The first, the sample conveyor, 
transfers a core sample evenly into the second component, the Jeffco Shredder. The fibrated 
sample is fed into component three, the read conveyor. Here, a cane-leveling device packs the 
cane into an even bed on a moving conveyor. When the cane bed is homogenous, infrared cane- 
height sensors tell the read head of the spectrometer to open, and to begin data acquisition. The 
average sample weighing 10kg will usually yield 60 total spectral replicates. Spectral scans are 
taken from 1100-2500nm until the cane height sensors indicate heterogeneity within the cane 
bed. The shutter on the read window snaps shut, a result "docket" is printed, and the fibrated 
cane is conveyed out of the instrument. 



81 



Madsen et al.: Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 

Acquisition of Laboratory Data 

Samples of billeted cane were acquired using an inclined coring machine. A core sample 
consists of billets up to twelve centimeters in length, a sample weighing between five and twelve 
kilograms. Two core samples per truck were taken. One core sample was fibrated using the 
existing hydraulic shredder. The material prepared this way has approximately 65% open-cells, 
and is referred to as Core Shredded Material (CSM) (Figure 2). This sample was subject to 
analysis via CPM. The second sample was shredded using the Jeffco shredder built into the 
NIRS. Material thus prepared has approximately 95% open-cells; it is referred to as Jeffco 
Shredded Material (JSM) (Figure 3). This sample was automatically transferred to a second 
conveyor where the NIR spectra were observed, and the data were saved to hard drive. The 
sample was conveyed out of the instrument, where it was collected and subject to DAC. 




Figure 2. Core Shredded Material. 







Figure 3. Jeffco Shredded Material. 



82 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Sample Analysis 





Analytical Protocol: 




' 


■UMSifrCM 


H - 












| 








i 




1 










(jnlNHSnifar 




MtoOmUw 




DACBEftBfu&b 






▼ 




I 








! ! 






cm 




JW 






1 






* 






1 




I 




CTMBBKBffiiflw 






cm Jm** 




■ACto»ffc 






i 


1 

























Figure 4. Flowchart of Analytical Protocol. 

A flowchart describing analytical operations is included (Figure 4). A one-kilogram 
sample of JSM was weighed into a water-jacketed wet disintegrator pot. To this was added two 
kilograms of water. This deviation from ICUMSA DAC was necessary as Jeffco shredded 
material tends to absorb extraction water forming a sticky ball that does not macerate well; our 
wet disintegrator pot would not hold 6L. The sample was disintegrated for eight minutes at 7200 
rpm. A lOg sample of the resulting extract was transferred into a 15mL conical centrifuge tube. 
This sample was centrifuged at 4000 rpm for ten minutes and analyzed for brix by refractometer. 
lOOppm Sodium azide was added as a preservative and sample was frozen. A 150mL sample of 
the extract was transferred into a glass jar. To the 150mL sample was added 19 grams of Octapol 
flocculent. The sample was shaken then filtered, whilst discarding the first 25mL of filtrate. The 
clarified filtrate was analyzed for polarimetric sucrose using an automatic saccharimeter. The 
frozen sample was taken back to the lab for sugar analysis (sucrose, glucose, and fructose) by 
HPLC. 500 grams of JSM were dried to constant weight, not to exceed -2g in 30 minutes 
(ICUMSA), at 105°C using a Deitert Moisture Teller forced draught air drier. The sample, once 
dried to constant weight, was placed into a plastic bag for storage and transport. 

The results were used to calculate pol, brix, fiber, and moisture % cane. These figures 
were used to calculate TRS. 

After the season, the stored dry matter was subjected to analysis for carbonated ash. All 
samples were analyzed in duplicate. The sample was placed into a tared dish, and a screen was 
placed over the top. The sample was incinerated at 650°C for 45 minutes. The sample was 
removed from the furnace, and allowed to cool to ~150°C. The screen was removed, and the dish 
containing the ash was weighed. The sample was carefully stirred and further incinerated at 



83 



Madsen et al.: Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 

650°C for ten minutes. The sample was removed from the furnace and allowed to cool. The 
sample was weighed, and transferred into a plastic bag for storage. 

These data were used to calculate ash % cane. This number was subtracted from the fiber 
% cane to produce a figure for corrected fiber % cane. 

The results from the core press analysis were provided by the mill administration. The 
given data provide pol and brix % juice, residue weight (from 1.0kg), and volumetric sediment. 
From these data were calculated pol, brix, fiber, and moisture % cane. These figures were used to 
calculate the TRS. 

Calibrating the MRS 

Both of the data sets were entered into the WinlSI software package. Here, the spectral 
results were matched to the laboratory data. Constituents for pol, brix, fiber, moisture % cane, 
and TRS were entered. The first derivatives of the spectral data were taken, and it was to these 
that the laboratory data is assigned. The data sets were regressed using a modified Partial Least 
Squares (PLS) algorithm. "Outliers" with a Global H value (distance from the global average) of 
more than three were re-evaluated. If the outlier was determined to result from anomalous 
spectral data, it was removed from the data set. For each constituent an equation was generated, 
and standard error of calibration (SEC) was calculated. 

Ash % cane exhibits a logarithmic trend. To generate an equation that is not heavily 
biased by the average, this constituent was calibrated using the logio of the laboratory data. The 
instrument then predicts ash % cane as a logarithm. The anti-log is taken, and the result 
subsequently produced. SEC and r 2 are produced for the logio result. 

The equations were used to evaluate a sample of the spectra. Here, lab results were 
compared with the NIR predicted values. This cross-validation is the final verification needed to 
determine if the equation produces representative predictions. The standard error of cross- 
validation (SECV) was used to determine the equation accuracy. 

RESULTS 

Laboratory results for DAC and CPM compared well. However, the pol % cane for CPM 
was always higher than that for DAC, as seen in Figure 5. This was attributed to extraction 
efficiency. DAC analysis used added water and provided more complete extraction. Fiber % 
cane for CPM values were, on average, between 10 and 17%. The DAC results displayed 
unusual spikes, ranging from 20 to 45%, as seen in Figure 6. Fiber % cane is a figure derived by 
difference from moisture and brix. As a result, any component other than water or brix will be 
seen as fiber % cane. Other components can include mud and/or trash. The spikes seen in the 
DAC-derived fiber % cane reflected the presence of mud, trash, or both. 






84 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 



25.00 



20.00 



15.X 



10.00 



5.00 



0.00 




31 51 



Sample Number 

Figure 5. Pol % Cane, by core press method and by DAC. Arranged by parallel sample number. 



5Q00 




Figure 6. Fiber % Cane, by core press method and by DAC. Arranged by parallel sample 
number. 



85 



Madsen et al.: Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 

After calibration, the software calculated the standard error of calibration (SEC), and the 
square of the linear correlation coefficient r 2 (RSQ). The standard error of cross validation 
(SECV) refers to the compound error relating the differences between actual and predicted 
results. The constituent results for the calibration derived from DAC (Table 1) and CPM (Table 
2) data sets demonstrated the effects of non-representative sampling. Both sets were based on the 
same spectra. Although laboratory data correlates reasonably well, SEC and RSQ demonstrate 
that the CPM results do not correlate well to the spectra. 

The statistics for the DAC based NIR equation closely paralleled those found in literature 
(Table 3). A comparison of DAC results for SECV is given in Table 4. 

The samples that were frozen were analyzed by HPLC for sucrose, glucose, and fructose. 
The results did not correlate with the pol sucrose. This effect was attributed to a lack of biocidal 
(NaN 3 , lOOppm) efficacy; the samples biologically degraded during processing, storage and 
transport. 

Table 1. NIR equation based upon DAC analytical data. N is the number of samples used, SEC 
is the standard error of calibration, RSQ is the linear correlation coefficient, SECV is the 
standard error on cross validation; 1-VR relates to the correlation on population variance. 



Constituent 


N 


Mean 


SEC 


RSQ 


SECV 


1-VR 


Pol%Cane 


180 


12.90 


0.237 


0.961 


0.325 


0.927 


Brix%Cane 


183 


15.44 


0.246 


0.966 


0.427 


0.898 


Moisture%Cane 


170 


71.49 


0.489 


0.912 


0.592 


0.870 


Fiber%Cane 


171 


12.91 


0.518 


0.901 


0.699 


0.818 


CRFiber%Cane 


170 


11.17 


0.411 


0.907 


0.488 


0.869 


Logash%Cane 


185 


0.228 


0.082 


0.870 


0.099 


0.811 


TRS 


173 


216.7 


5.31 


0.948 


7.14 


0.905 



Table 2. NIR equation based upon CPM analytical data. 



Constituent 


N 


Mean 


SEC 


RSQ 


SECV 


1-VR 


Pol % Cane 


194 


13.16 


0.507 


0.648 


0.579 


0.545 


Brix % Cane 


182 


15.66 


0.379 


0.793 


0.431 


0.733 


Fiber % Cane 


171 


16.74 


0.844 


0.777 


0.908 


0.743 


% Moisture 


186 


71.19 


0.872 


0.604 


0.933 


0.546 


TRS 


192 


215.7 


11.51 


0.526 


12.50 


0.442 



86 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Table 3. Results for DAC derived NIR equation and the average literature values (Bentley, 
Staunton, Atherton, and Henderson, 2001; Berding and Brotherton, 1999; Edye and Clarke, 
1996; Larrahondo, Palau, Navarrete, and Ramirez; Johnson, 2000; Schaffler, Staunton, 
Lethbridge, Grimley, Streamer, Rogers, and Mackintosh, 1999) 



Constituent 


N 


SEC 


RSQ 


Our 
work 


From 
Literature 


Our 
work 


From 
Literature 


Our work 


From 
Literature 


Pol % Cane 


180 


970 


0.24 


0.14-0.44 


0.96 


0.94-0.99 


Brix % Cane 


183 


985 


0.25 


0.25-0.44 


0.97 


0.95-0.99 


Fiber % Cane 


171 


745 


0.52 


0.52-0.56 


0.90 


0.87 


% Moisture 


170 


622 


0.49 


0.57 


0.91 


0.92-0.95 


Ash%Cane 


185 


1340 


n/a 


0.44 


0.87 


0.78 


TRS 


173 


n/a 


5.31 


13.13 


0.95 


0.84 



Table 4. Results for DAC derived NIR equation and the average literature value of SECV. 



Constituent 


N 


SECV 


Our work 


From 
Literature 


Our work 


From 
Literature 


Pol % Cane 


180 


970 


0.33 


0.18-2.10 


Brix % Cane 


183 


985 


0.43 


0.25-0.70 


Fiber % Cane 


171 


745 


0.70 


n/a 


% Moisture 


170 


622 


n/a 


n/a 


Ash%Cane 


185 


1340 


n/a 


0.50 


TRS 


173 


n/a 


7.14 


13.62 



DISCUSSION 

As seen in Tables 1 and 2, NIR equations calibrated on DAC and CPM analytical data 
sets agreed poorly. We believe that this results from the sample-to-sample variation that occurs 
between two different core samples taken from the same load. The inclined core sampler was 
designed for use with whole cane, whereby a 23kg sample may be achieved. When this method 
is used for billets, the cutting head scatters some of the cane, while achieving a sample of only 5- 
15kg. The small sample size resulted in increased sample heterogeneity; in effect, the DAC and 
CPM analyses were performed on two different samples, albeit from the same truckload. NIRS is 
fast enough to compensate for small sample sizes by analyzing a larger number of samples. 

For each constituent, a range of cited values was given; see Tables 3 and 4. When 
compared, the DAC derived SEC, RSQ, and SECV for each constituent were within the ranges 
seen in the literature. The DAC % of LIT refers to the result of our calibration relative to the 



87 



Madsen et al.: Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 

average of the cited range for a particular constituent. Based upon analysis of these figures, the 
DAC based NIR equation performed at least as well as the literature cited. The SECV achieved 
for DAC calibrations were within the ranges found in the literature. These equations provided 
accurate as well as precise predictions relative to the laboratory results, as seen in Figures 7- 9. 



16 
15 
14 
13 



i 12 



11 

10 
9 
8 



Pol % Cane 




y = 0.9635x + 0.4676; 



R 2 = 0.954 



9 10 11 12 13 14 15 16 

Actual 



Figure 7. Pol % cane, DAC lab result vs. NIR prediction. 



20 -I 

18 

16 

■o 

I 

12 - 

10 

8 




Brix % Cane 
















JKJk * 




*ji 






y =» 0.958X + 0.6534 
.R*»-0.«682 


i 10 


12 14 

Actual 


16 18 2 






Figure 8. Brix % cane, DAC lab result vs. NIR prediction. 






88 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 













TRS 






260 
240 
220 
1 200 
I 180 
160 
140 
120 
















jJ? 


*&** 










♦J 




' ' f jf f 








♦ 






j/^ * : 




i 








y» 0.8407X + 12.846 


R'- 0.943 


1( 


K> 


120 


140 


160 


180 200 
Actual 


220 240 260 280 



Figure 9. TRS, DAC lab result vs. NIR prediction. 

Calibration of the NIRS for ash % cane required some special considerations. The NIRS 
reads samples containing soil. A viable method for quantitating soil in cane is combustion ash 
analysis. Samples containing soil reflected this as ash. WinlSI software can only fit 
experimental data to a linear model, causing high ash % cane results to be discarded as outliers. 
This resulted in an equation that will not produce a predicted result in excess of the average 
global maximum (Figure 10), which in this case is -5.0 %. To force the software to retain these 
points, the equation was linearized using the logio values of the laboratory data. The high results 
were no longer regarded as outliers, and the equation can, pending secondary calculation of the 
antilog, produce a predicted result that was between 87 and 117% of the actual value. The fit of 
the log equation to lower values was not jeopardized by these manipulations. 



5 
4.5 

4 
3.5 

3 



I" 
°" 2 



1.5 
1 

0.5 






♦ ♦ 


* * -— ^^~ - "**'^ 


♦• 




♦ ^ i ^0-* 00 *'^ 




i\ 




♦ 

* 




w 


• 






*9 m 


♦ 






w*< 


♦ 












y = 0.9924Ln(x) + 1.1471 


R 2 s 0.6822 



10 



15 



20 



25 



Actual 



Figure 10. Prediction of ash % cane: the log curve fit has been added to demonstrate the 
distribution shape of the actual vs. predicted values. 



89 



Madsen et al.: Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 

Analysis of the lab data has clarified several questions. The fiber % cane includes the ash 
and soil present in the sample. It became obvious that CPM does not reflect this since mud fouls 
the press; juice cannot be expressed from mud without added extraction water. In addition to 
this, the mud must then be cleaned out of the press while accumulating a sample backlog. An 
NIRS instrument calibrated by DAC will be able to measure samples containing large amounts 
of soil. A more accurate fiber result is achieved by difference (Figure 11). This figure has been 
called "corrected fiber" (CRFiber, Figure 12) and has been added as a constituent to the DAC 
derived NIR equation set. 




-10 



Sample Number 

Figure 1 1 . Ash % and Fiber % Cane Lab Data from DAC. 



7000 



60.00 



50.00 

& 40.00 
* 

I 

c 

X 30.00 



20.00 



1000 



0.00 



•CRFiber 




56 



76 



96 



116 



176 



196 



216 



136 156 

Sample Number 

Figure 12. Corrected Fiber % Cane, taken by difference from the DAC results for fiber and ash 
% cane. 



90 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Actual data from a Louisiana core lab showed costs of -$85,000 per season on 
employees and supplies. The same lab, using the NIRS might have spent -$14,000 per season. A 
net saving of -$70,000 per season may be achieved. At an initial cost of $160,000 dollars, a 
NIRS system of this type could be paid for in less than 3 years. Savings resulting from accurate 
data have not been assessed, but are likely to be even more significant. 

If NIRS is installed, a qualified technician may manage continuing calibration 
verification (CCV), once per week. This technician should serve to monitor the instrument, 
update calibration, and to serve as liaison for support in the event of technical difficulty. For 
Louisiana, serving 15 mills, only one liaison technician should be required, and could be 
subcontracted as an independent body. 

CONCLUSIONS 

The instrument was able to meet or exceed calibration values found in the literature for 
fibrated cane. Analysis of core-sampled cane can be completed within 120 seconds, while 
providing accurate results for pol, brix, fiber, moisture, ash % cane, and TRS. The possibility of 
discriminating and quantitating "trash" from mud has been realized, and may be exploited in the 
future. Increased throughput will allow for more comprehensive sampling. Improvement in 
sample representation will result in accurate payments. Immediate knowledge of excessive mud 
or "trash" at the weighbridge might be used to decrease the amount of foreign material entering 
the mill, reducing mill stoppage. 

The instrument needed no mechanical maintenance (other than routine cleaning) during 
the course of this trial, even under the most hostile ambient conditions. Use of the InfraCana will 
require only one operator per shift, rather than 3-5 per shift as at present, and is not subject to 
experimental error. In light of these developments, it can be concluded that the InfraCana NIRS 
may be proven a viable alternative to current core press method of cane analysis. 



ACKNOWLEDGMENTS 

The authors would like to thank the following, for without their mutual investment of 
time, patience, and knowledge, this project may not have reached fruition: 

The American Sugar Cane League contributed the funds required for this research. 
Julio Petersen of Foss NIRSystems was constantly available; his help allowed us to successfully 
negotiate the WinlSI software to generate a useful set of NIRS equations. Torsten Hansen of 
Foss/Tecator provided expeditious solutions to complex software issues. Colin Jeffress of Jeffco 
Engineering engineered the InfraCana and provided technical support and firmware upgrades. 
Barry Forse accommodated us warmly at Cinclare Sugar Mill, and provided an excellent 
prepared site for the instrument. From fabrication and maintenance to negotiation of site 
resources, Joe Bell, Lamar Aillet, and Scott Barrow from the Audubon Sugar factory were 
always at the ready. 



91 



Madsen et al . : Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 

REFERENCES 

1. Bentley, S. Staunton, P. G. Atherton, and C. Henderson. 2001. Application of NIR cane 
analysis technology to small consignments of cane in Fiji. Sugar Cane Technol. 24: 59-65. 

2. Berding, Nils, and G. A. Brotherton. 1999. Analysis of fibrated sugarcane by NIS: The 
laboratory solution. 2 nd Annual NIR Users Meeting for the Sugar and Alcohol Industries, 
Sao Paulo, Brazil, pp. 6-7. 

3. Berding, Nils, and G. A. Brotherton. 1996. Grabbing the BIG picture: a novel approach to 
beating within-sample material heterogeneity. NIR News 7(6): 14. 

4. Edye, L .A., and M. A. Clarke. 1996. Sugarcane quality analysis by near infrared 
spectroscopy. Proc. S. Afr. Sug. Technol. Assoc. 7: 127. 

5. ICUMSA Method GS5/7-1 . 1994. The determination of pol (polarisation), Brix and fiber in 
cane and bagasse by the wet disintegrator method - Official. 

6. Larrahondo, J. E., F. Palau, A. Navarrete, and C. Ramirez. 2000. Applications of near 
infrared spectroscopy in the sugarcane industry of Colombia. Centro de Investigacion de la 
Cana de Azucar de Colombia, Cenicana, Cali, Colombia 163-164 

7. Johnson, T. P. 2000. Cane juice analysis by near infrared (NIR) to determine grower 
payment. SPRI Annual Meeting. 9-12. 

8. Peterson, J. C. 1999. Near Infrared (NIR) Technology in the Sugar and Alcohol Industries. 
FOSS-NIRSystems, 12101 Tech Rd., Silver Spring, Md. 10904, USA. 3 pp. 

9. Schaffler, K. J., and J. H. Meyer. 1996. Near infrared analysis of shredded cane: a potential 
replacement for direct analysis of cane. Proc. S. Afr. Sug. Technol. Assoc. 70: 134. 

10. Staunton, S. P., P. J. Lethbridge, S. C. Grimley, R. W. Streamer, J. Rogers, and D. L. 
Mackintosh. 1999. Analysis of fibrated sugarcane by NIS: The on-line solution. Proc Aust. 
Soc. Sugar Cane Technol. 21:20-27 



92 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

AGRICULTURAL ABSTRACTS 

Green Cane Trash Blankets: Influence on Ratoon Crops in Louisiana 

E. P. Richard, Jr. and R. L. Johnson 

USDA-ARS, Southern Regional Research Center, Sugarcane Research Unit 

Houma, LA 

Approximately 75% of Louisiana's 2000 sugarcane crop was harvested with a chopper 
harvester. A significant portion of the chopper-harvested sugarcane was harvested green, especially 
early in the season. Information on the impact of the post-harvest, green-cane residue blankets on 
subsequent ratoon crops is inconclusive, but yield reductions have been reported. To insure 
maximum yields, the residue is generally removed by burning during the winter months when 
weather conditions are more favorable in reducing the likelihood the smoke will offend the public. 
The effects of residue blanket management methods on ratoon crops were studied following the 2000 
harvest. In one study, burning the residue in January resulted in higher (14%) sugar yields of first- 
ratoon LCP 85-384 compared to the no removal treatment. Delaying the burning of the residue until 
February or March did not significantly improve sugar yields over the no removal treatment. In a 
second study designed to evaluate varietal responses to dates of residue removal, first-ratoon crops 
of CP 70-321, LCP 85-384, HoCP 85-845, and HoCP 91-555 were found to respond similarly to 
the removal of the residue. The average sugar yield (6.6 Mg/ha) for the four varieties was 1 1 % higher 
than the no removal treatment (5.9 Mg/ha) when the residue was removed in early January, 
regardless of whether the residue was mechanically removed to the row sides or completely burned 
off. When burning was delayed until March, the average sugar yield (5.3 Mg/ha) was 10% lower 
than the no removal treatment suggesting that some damage to the emerged shoots was occurring 
with the later burn. Soil temperature and soil moisture readings taken early in the growing season 
(January to April, 2002) indicate that the soil is colder and wetter under the blanket of residue. The 
cold and wet soil condition created by the thick blanket of residue may be affecting crop emergence 
in the spring and ultimately sugar yields. 

The Effect of Combine Speed on Cane Quality at Alma Plantation in 2001 

H. Waguespack, Jr. 1 , W. Jackson 1 , B. Viator 2 , and C. Viator 2 

'American Sugar Cane League, Thibodaux, LA 
2 Calvin Viator, Ph.D. and Associates, LLC, Thibodaux, LA 

The parallel acceptance of a new sugarcane variety LCP 85-384 and the use of combine 
harvesters have significantly redefined the Louisiana sugarcane industry in recent years. The 
importance of high quality cane deliveries has been emphasized due to the new harvest method and 
the challenges faced by raw sugar processors. This study was conducted to help determine the 
influence of forward speed on cane quality. Alma Plantation in Lakeland, LA agreed to participate 



93 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

in the experiment throughout the 2001 harvest season. Weekly sampling was conducted using the 
same operator and a 2000 model 7700 Case Combine Harvester. The extractor fan speed was 900 
to 950 rpm in burned cane and 1 100 rpm in green cane. The treatments (speeds) were 1 .5, 2.5, 3.5 
and 4.5 mph and were monitored with a handheld radar unit to ensure accurate ground speed. For 
1 2 consecutive weeks, one truckload was cut at each speed and delivered to the mill to be weighed 
and sampled using the mill's core sampler. While the delivered tons of cane per acre was 
significantly less when the combine was slowed down to 2.5 and 1 .5 mph, the pounds of sugar per 
ton of cane was only higher in the 1.5 mph treatment as compared to 3.5 and 4.5 mph (P = 0.05). 
There was no significant difference in the resulting yield of pounds of sugar per acre between the 
treatments. The 4.5 mph treatment had the highest fiber % cane, but sediment readings were not 
significantly different among treatments. When the mill's incentive formula was applied to the yield 
results, the 1 .5 mph treatment received a bonus of 3.36 pounds of sugar per ton of cane which was 
only significantly greater than the -1.57 pounds of sugar per ton of cane for the 4.5 mph treatment. 
The data demonstrates that forward speed of the combine harvester has a significant influence on 
delivered cane yield and quality. Practical application of this information could be used to determine 
other optimal combine settings to improve cane quality from combine-harvested sugarcane in 
Louisiana. 



Use of Cover Crops in Rotation with Sugarcane in a South Florida Mineral Soil 

R, M. M uchovej, J. J. Mullahey, T. A. Obreza, and P. R. Newman 

University of Florida, Southwest Florida Research and Education Center 

Immokalee, FL 

The establishment of cover crops (grasses or legumes) prior to planting sugarcane 
(interspecific hybrids of Saccharum spp.) offers many potential agricultural and ecological benefits 
to the grower. These benefits include organic matter production to enrich the soil, ground cover to 
reduce windblown soil erosion, weed control (including less herbicide use), reduced runoff, 
improved infiltration, soil moisture retention, and soil tilth, nutrient enhancement, and food for 
wildlife. By improving soil organic matter, cover crops directly influence the soil water holding 
capacity by increasing water retention and lateral water movement within the soil. Rotation of 
susceptible agronomic crops with crops that are not nematode pest hosts or are resistant to certain 
nematodes has been a successful nematode management strategy. The objective of this study was 
to evaluate the impact of eight cover crops on sugarcane grown on sandy soils. Cowpeas, 
Aeschynomene, Hairy indigo, Sorghum sudangrass, Sterile sorghum, Sorghum sudan/cowpeas 
mixture, Japanese millet, and Tifleaf millet were planted in April 1 992- 1 994 in 0.25 to 1 .2 acre (0. 1 
to 0.50 ha) plots. Cover crop biomass was measured in August of each year, followed by sugarcane 
planting in September, which was subsequently harvested in November of the following year ( 1 993- 
1995). Cover crop yield was significantly higher for the grasses than for the legumes in 1993 and 
1994. Cool temperatures and flooded fields during the establishment period resulted in thin stands 
and low yields of the cover crops. Aeschynomene had the best ground cover (46%) of all cover crops. 
Cowpeas did not tolerate periods of standing water, indicating that this crop should be planted on 

94 






Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

drier sites. Japanese millet, which tolerates wet field conditions, should not be planted until late 
April or early may to prevent early (within 21 days of planting) seedhead emergence. The optimum 
time to plant warm-season cover crops may be early May, so that at least 4 months of growth are 
obtained before sugarcane is planted. In the 1993-1995 crop, sugarcane yield (tonnage and sucrose 
content) obtained for Aeschynomene was numerically higher than for all other cover crops treatments 
and the control treatment (fallow field with no cover crop planted with sugarcane). However, 
significant differences (Fisher's protected L.S.D. test , P=0.05) for sugarcane yields were only 
obtained between the Aeschynomene treatment and the Sorghum sudangrass and the Sorghum 
sudangrass/cowpeas mixture. 



Evaluation of Sorghum-Sudangrass Hybrids for Biomass Potential in Southern Louisiana 

T.L. Tew 

USDA-ARS, Southern Regional Research Center, Sugarcane Research Unit 

Houma, LA 

As close relatives of sugarcane, sorghum-sudangrass hybrids are easy to establish (seed 
propagated), could be used as an interim crop (April - July) during the fallow season, and may have 
potential as an complimentary bioenergy crop. Ten sorghum-sudangrass {Sorghum bicolor x S. 
bicolor var. Sudanese) hybrids were evaluated for biomass potential at the site of the USDA-ARS 
Sugarcane Research Unit in Houma, Louisiana. The experiment was designed to be largely 
observational with single-row unreplicated plantings. Beginning 14 May and continuing weekly 
through 1 July (nine weeks), 1 0-stalk samples of each hybrid were collected and analyzed to obtain 
fresh weight, dry weight, and Brix estimates. One of the hybrids known to be photoperiod sensitive, 
was non-flowering, and therefore expressed an indeterminate growth habit, continuing to increase 
in weekly cumulative dry matter content through the end of this experiment. At 97 days following 
planting (4 Apr 2001 - 10 Jul 2001) the nine hybrids with determinate growth habit, averaged 3 tons 
green matter/acre, 0.80 tons dry matter/acre, 8.5 Brix, and just over 7 ft height. By contrast the non- 
flowering hybrid achieved 8 tons GM/acre, 1.75 tons DM/acre, 6.7 Brix, and reached 12 ft height. 
During 2002, the bioenergy potential of this non-flowering hybrid will be entered into a sorghum test 
at Houma and directly compared with sorghum varieties considered for commercial bioenergy 
production in sugarcane-growing areas of Southwestern Louisiana. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

ENVOKE: A New Herbicide for Weed Control in U.S. Sugarcane 

E. K. Rawls 1 , M. Johnson 1 , S. Martin 1 , L. Glasgow 1 , J. Shine 2 , J. Powell 3 , B. Watson 4 and 

A. Bennett 5 

'Syngenta Crop Protection, Vero Beach, FL 
2 Sugarcane Growers Coop., Belle Glade, FL 

3 Okeelanta Corp., South Bay, FL 

4 U. S. Sugar Corp., Clewiston, FL 
5 University of Florida, IFAS, Belle Glade, FL 

Envoke®[N-(4,6-Dimethoxy-2-pyrimidm^ 
sulfonamide sodium salt] is a new broad-spectrum, post-emergence herbicide that Syngenta Crop 
Protection is developing for use in sugarcane, cotton, citrus and almonds. It has been field tested as 
a 75% water dispersible granule for several years in North America, South America, Africa, and Asia 
under the code name CGA-362622. The proposed common name is trifloxysulfuron-sodium. 
Envoke® will offer control of certain broadleaf, sedge, and grass weeds in cotton, sugarcane, citrus, 
and almonds including yellow nutsedge, purple nutsedge, flatsedge, redroot pigweed, spiny pigweed, 
pitted morningglory, ivyleaf morningglory, scarlet morningglory, hemp sesbania, cocklebur, 
sicklepod, broadleaf panicum, spurge, Spanish needles, and horseweed. 

In sugarcane, 0.3 - 0.6 ounces product/A (15.8 - 31.6 g ai/ha) of Envoke® can be applied 
post-emergence, depending on cultivar, with excellent crop tolerance. For optimum post-emergence 
activity, the addition of NIS is recommended at 0.25% v/v. The very low use rate of 0.3 to 0.6 ozs/A 
together with its favorable toxicological, ecotoxicological and environmental properties make 
Envoke® an excellent tool for sugarcane farmers. Envoke® is readily absorbed by shoots and roots 
and is readily translocated in weeds. Susceptible weeds are inhibited following an application of 
Envoke® with complete death occurring within 1 to 2 weeks after application. 

Envoke® is compatible with other herbicides including AAtrex® and Evik® which can be 
used to increase the weed spectrum and duration of control. Envoke® can be applied in combination 
with Evik®, post-directed only, to increase speed of activity and weed spectrum, especially the 
grasses. 



Experimental Products for Weed Control in Florida Sugarcane 

A.C. Bennett 

University of Florida, Everglades Research and Education Center, 

Belle Glade, FL 

Several new herbicides are being evaluated for weed control in Florida sugarcane. Both pre- 
emergence (PRE) and post-emergence (POST) herbicides are being evaluated. Control of a wide 
range of common weeds, including fall panicum, broadleaf panicum, alligator weed, purple nutsedge, 

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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

yellow nutsedge, and several other species is being evaluated. The PRE products in testing include 
flumioxazin and azafenidin, applied alone or in conjunction with labeled PRE herbicides. These 
treatments are being evaluated in comparison to standard PRE treatments. POST products under 
evaluation include carfentrazone, trifloxysulfuron, and flumioxazin. These products are being 
evaluated both alone and in conjunction with standard POST treatments, such as asulam, atrazine, 
halosulfuron, and ametryn. 

Early results indicate potential for good control of a range of weeds utilizing these new 
products alone or in tank-mixture with currently labeled products. Detailed results will be presented 
during the conference. 



Effect of Calcitic Lime and Calcium Silicate Slag Rates and Placement on LCP 85-384 

Plant Cane on a Light-Textured Soil 

W. B. Hallmark 1 , G. J. Williams 1 , G. L. Hawkins 2 and V. V. Matichenkov 3 

'Iberia Research Station, LSU Ag Center, Jeanerette, LA 

2 Sugar Research Station, LSU Ag Center, St. Gabriel, LA 

3 Indian River Research Center, University of Florida, Fort Pierce, FL 

Substantial sugarcane yield responses to silica application have been documented in Florida 
and Hawaii, but not in Louisiana. Our research determined the effect of calcitic lime and calcium 
silicate slag rates and placement on plant cane yields grown on a light-textured soil in Louisiana. 
Results showed that mixing 2.24 Mg ha' 1 and 4.48 Mg ha" 1 of calcium silicate slag into soil before 
planting, or placing 2.24 Mg ha" 1 of slag under cane at planting resulted in higher (P<0.10) sugar 
yields compared to the check. Mixing 2.24 Mg ha" 1 and 4.48 Mg ha' 1 of calcitic lime, however, into 
the soil before planting did not increase (P^O.10) sugar yields. Higher sugar yields obtained with 
calcium silicate slag vs. calcitic lime indicates that the yield response obtained with calcium silicate 
slag was due to its silica content. 



Sugarcane Leaf P Diagnosis in Organic Soils 

D. R. Morris 1 , B. Glaz 1 , G. Powell 2 , C. W. Deren 3 , G.H. Snyder 3 , R. Perdomo 2 and 

M.F. Ulloa 2 

'USDA-ARS, Sugarcane Field Station, Canal Point, FL 

2 Florida Crystals, South Bay, FL 

3 University of Florida, EREC, Belle Glade, FL 

Most of the sugarcane production in south Florida is on organic soils. Phosphorus is an 
essential plant nutrient that contributes to optimum sugarcane yields, but producers are required to 
reduce P levels in waterways. One way to monitor P nutrition is through leaf diagnosis. The 
objective of this study was to determine the best time to leaf sample during the summer months and 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

to relate optimum leaf P tissue content and yield. A 3-year field study was conducted on four organic 
soil locations in south Florida. An 8 by 3 factorial experimental design with four replications was 
used at each location with eight sugarcane (interspecific hybrids of Saccharum sp.) genotypes in 
combination with three fertilizer P rates (0, 24, and 48 kg P ha" 1 ). Fertilizer rates were based on soil 
test analysis with 24 kg ha" 1 being the recommended rate. Upper-most fully expanded leaves were 
sampled in early, mid, and late summer prior to three harvests (plant cane, first ratoon, and second 
ratoon). Two locations had optimum cane and sugar yields at 24 kg P ha" 1 for all harvests. There was 
no response to P fertilizer at one location for any harvest year, while the other location had the 
highest cane yields at 48 kg P ha" 1 for all harvests. Analysis of variance for leaf P content showed 
significant interactions for location by P rate by harvest and for location by P rate by leaf-sample 
time. Leaf P content did not always correspond to yield data. Within each location, sometimes the 
leaf P content increased with increasing P rate as did yield, and sometimes yields did not show a 
response to P fertilizer even though leaf P increased. Consistent patterns in time of leaf sampling 
within locations could also not be obtained. Correlation analysis of yield vs. leaf P content across 
all treatment in early and mid summer were statistically significant (PO.05), but coefficients were 
very low (r=0. 14 and 0.26, respectively). Correlations of harvests within location at each leaf sample 
time were occasionally significant (PO.01) with the highest correlation of r=0.79. But, there was 
no consistent pattern relating leaf P tissue content with yields. Optimum leaf P tissue content should 
be calibrated for each field, harvest, and sampling date for precision agriculture applications. 



Wireworm Effects on Sugarcane Emergence After Short-Duration Flood Applied at 

Planting 

B. Glaz 1 and R. Cherry 2 

'USDA-ARS, Canal Point, FL 
2 University of Florida, Belle Glade, FL 

Sugarcane (interspecific hybrids of Saccharum spp.) growers in Florida normally apply a soil 
insecticide at planting to limit wireworm (Melanotus communis Gyll.^ damage to planted stalk 
sections. Long-duration floods prior to planting sugarcane are also used to control wireworms. A 
recent study found that sugarcane emergence was improved by floods of 2-12 days applied at 
planting. The purpose of this study was to analyze sugarcane emergence after floods of 7, 14, and 
21 days applied at planting, as well as following a conventional application of an organophosphate 
insecticide at planting without flooding. In three outdoor experiments, wireworms were applied at 
the severe rate of 1 3 larvae per meter of row in plastic containers filled with Pahokee muck soil. In 
the first experiment, emergence under the flood treatments was lower than under the insecticide 
treatment, probably due to lower than normal air and soil temperatures. Emergence in the 14- and 
21 -day flood treatments and the insecticide treatment were similar in the final two experiments. 
However, reductions in plant weight were associated with some flood treatments. Previous work 
reported that wireworms damaged growing plants in containers, but damage was primarily limited 
to reduced emergence in field studies. The successful wireworm control of the 1 4- and 2 1 -day floods 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

and the negative effects on plant weights reported in this study need to be verified in field studies. 



Laboratory Screening of Insecticides for Preventing Injury by the Wireworm Melanotus 
communis (Coleoptera: Elateridae) to Germinating Sugarcane 

D. G. Hall 

United States Sugar Corporation 
Clewiston, FL 

A laboratory bioassay was investigated for screening candidate materials for preventing stand 
losses by wireworms in germinating plant cane. For liquid materials, single-eye billets were dipped 
into different concentrations of a material and then planted in plastic containers of organic soil; 
wireworms were then introduced, airtight lids were placed onto the containers, and wireworm 
survival and damage were assessed 4 wk later. Tests with granular materials were similar except the 
containers were partially filled with untreated soil; 30 ml of soil treated with the granular material 
were then added to the container; an untreated single-eye billet was placed onto this treated soil; an 
additional 30 ml of treated soil was then placed on and around the billet; and finally untreated soil 
was added to fill the container. Conditions inside the bioassay containers appeared suitable for 
germination and growth of most varieties. Airtight lids were advantageous from the standpoint of 
maintaining soil moisture. Data indicated it may be disadvantageous to hold wireworms for a long 
period of time before using them to screen a material. 

Bifenthrin, thiamethoxam 25WG, thiamethoxam 2G, and tefluthrin 3G appeared to have 
value as materials for reducing damage by wireworms to germinating eyes of seed cane planted in 
organic soils. However, germinated shoots of billets treated with these materials were sometimes 
injured by wireworms. Another material, ethiprole, was found to inhibit germination of CL77-797 
when applied in solutions greater than ~ 1,000 ppm. Little wireworm mortality occurred in 
containers of billets treated with ethiprole at any rates tested, but surviving wireworms frequently 
caused injury to the billets. Another material, zeta-cypermethrin, appeared to have no value as a 
wireworm control material at the rates studied (75 to 125 ppm). Overall based on limited data, the 
most promising of these materials with respect to reducing wireworm damage to both germinating 
eyes and young shoots appeared to be thiamethoxam 25 WG at 12,000 ppm. 



Management Thresholds for the Sugarcane Borer on Louisiana Varieties 

F. R. Posey, C. D. McAllister, T. E. Reagan, and T. L. Bacon 

Department of Entomology, LSU AgCenter, Louisiana Agricultural Experiment Station, 

Baton Rouge, LA 

The sugarcane borer (SCB) is responsible for greater than 90% of the total insect damage to 
sugarcane in Louisiana, and the process to decide when to spray is determined by many variables (i.e. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

infestation levels, weather conditions, economics of the grower, environmental concerns, etc.). 
Therefore the overall goal of this study is to provide key facts that would allow the industry to have 
a greater flexibility in controlling the SCB on different varieties while maintaining a high level of 
confidence that a reduction in sugar per acre and buildup of SCB pest populations can be avoided. 
SCB larval infestations were monitored weekly with leaf sheath sampling. The SCB resistant 
varieties CP70-321 and HoCP85-845, and the susceptible varieties LCP85-384 and HoCP91-555 
with four regimes of SCB control were treated with insecticide when the designated threshold levels 
were reached. 

Results indicated that the variety HoCP91-555 (highly susceptible) required three 
applications of insecticide during the growing season for both the 5% SCB infestation threshold 
(5%) and 5% early and 10% late season threshold (5%/10%). In comparison, LCP85-384 
(susceptible) required three insecticide applications for the 5% management threshold, but only two 
insecticide applications for the 5%/l 0% management threshold. The resistant variety HoCP85-845 
required two applications for the 5% threshold and only one application for the 5%/10% threshold. 
CP70-32 1 required only one application under the 5% and the 5%/l 0% management regimes. This 
study further demonstrates some positive results for the industry's leading variety LCP85-384 (it 
currently represents about 80% of the sugarcane grown in Louisiana) in terms of growers being able 
to manage this variety against the SCB with the use of timely application of insecticides. The 
5%/ 10% threshold shows promise and supports the industry's desire to reduce unneeded insecticide 
applications during the season due to increasing economic and environmental concerns. 



Yellow Sugarcane Aphid (Siphaflava) Colonization Strategy and its Effect on Development 

and Reproductive Rates on Sugarcane 

G. S. Nuessly and M. G. Hentz 

University of Florida, Everglades Research and Education Center 

Belle Glade, FL 

Yellow sugarcane aphid (YS A) is an occasional serious pest of sugarcane throughout the 
subtropics and tropics. Leaf feeding on susceptible cultivars results in red spots of various sizes and 
density usually followed by chlorosis and then necrosis. Prolonged feeding results in fewer new 
shoots, reduced stalk diameter and yield. Field samples indicate that winged aphids (alates) normally 
stay in one place on favored cultivars once they start reproduction and that alates are frequently 
found together in groups on leaves. This aphid also prefers leaves that are about halfway between 
the top visible dewlap (TVD) and the youngest senescing leaves. Research was begun to examine 
whether group feeding affected development rates, nymph production and development rates of the 
subsequent F2 generation. Leaf position relative to the TVD was also evaluated for its possible 
effect on these population parameters. Tests were conducted in a greenhouse using the susceptible 
cultivar CP80- 1 827 inoculated with YS A from a laboratory colony maintained on a Sorghum-Sudan 
hybrid. Individual aphids and those in small groups took longer to develop to adults and produced 
fewer nymphs per day than those that developed within larger groups. The F2 generation reached 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

adulthood and started reproducing in 25% less time than did the Fl . Leaf position had a minor effect 
on these population parameters. 



Field Trials of a Multiple-Pathogen Bioherbicide System with Potential to Manage 

Guineagrass in Florida Sugarcane 

S. Chandramohan 1 , M. J. Duchrow 2 , J. M. Shine, Jr. 2 , E. N. Rosskopf 3 , and 

R. Charudattan 1 . 

'Department of Plant Pathology, University of Florida, Gainesville, FL 

2 Sugar Cane Growers Cooperative of Florida, Belle Glade, FL 

3 USDA, ARS, USHRL, Ft. Pierce, FL 

Guineagrass (Panicum maximum) is a problematic weed in sugarcane in Florida due to its 
capacity for prolific spread and tolerance to chemical herbicides. Development of host-specific 
fungal plant pathogens as bioherbicides may provide a nonchemical option to manage these weedy 
grasses. Three fungi indigenous to Florida, Drechslera gigantea, Exserohilum longirostratum, and 
E. rostratum were evaluated in July and September 2001 in Pahokee, FL for the control of 
guineagrass {Panicum maximum). Mini-plots, each 10' x 5', with a 5' buffer zone between plots, 
were set up. A mixture of the three pathogens (1:1:1 v/v; total 10 6 spores per ml; 250 ml spore 
suspension per plot @54GPA) was applied to guineagrass in each plot (3 to 4 inches tall (July) and 
1 to 2 inches tall (Sep.)) as follows: (1) Sunspray 6E 40% - Paraffin Oil 10% (Inoc-40E-10P); (2) 
Sunspray 6E 30% - Paraffin Oil 10% (Inoc-30E-10P); (3) Sunspray 6E 20% - Paraffin Oil 10% 
(Inoc-20E-10P); (4) Sunspray 6E 40% (Inoc-40E); and (5) Paraffin Oil 10% (Inoc-lOP). 
Guineagrass in uninoculated control plots were treated with the respective carriers alone. The 
treatments were applied on July 03 and 18 and Sep. 02 and 22. A completely randomized block 
experimental design with four replicates for each treatment was used. At 3 weeks after initial 
inoculation (WAI), disease severity ranged from 1 5 to 27 % in July, and 52-90 % in Sep. on 
guineagrass applied with Inoc-40E, Inoc-20E- 1 OP, Inoc-30E- 1 OP, and Inoc-40E- 1 OP fungal mixture 
treatments. Uninoculated guineagrass plants treated with the carriers alone, were healthy. At 4 
WAI, plant growth was stunted, and reduction in panicle number per sq. m. area was 82%, 90% and 
93% in July, and 99%, 99%, and 99% in Sep in Inoc-30E-10P, Inoc-40E, and Inoc-40E-10P 
treatments, respectively. The reduction in panicle number was higher (P=0.05) than the control 
treatments. Thus, the mixture of D. gigantea, E. longirostratum, and E. rostratum has potential to 
be developed as a bioherbicide system for guineagrass in sugarcane. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Molecular Identification of Virus Isolates Causing Mosaic in Louisiana Sugarcane 

M. P. Grisham and Y. -B. Pan 

USDA, ARS, SRRC, Sugarcane Research Unit 
Houma, LA 

Ten strains of sugarcane mosaic virus (SCMV) and three strains sorghum mosaic virus 
(SrMV) have been reported to cause mosaic in Louisiana; however, only strains H, I, and M of SrMV 
were recovered from commercial fields during surveys conducted between 1973 and 1995. Annual 
surveys were discontinued because of the large amount of labor required to identify strains using host 
differentials. At the time of these surveys, this was the only technique available to identify strains 
of these viruses, and results had changed little during the last 10 years. Recent advances in 
technology have led to the development of a laboratory procedure capable of distinguishing the 
mosaic virus strains. A survey was conducted in 2001 using reverse transcriptase-polymerase chain 
reaction-based restriction fragment length polymorphism (RT-PCR-RFLP) analysis to determine if 
changes have occurred among the strains of virus causing mosaic of sugarcane in Louisiana. Strain 
I and strain H of SrMV were associated with approximately 65% and 21% of the sugarcane plants 
with mosaic symptoms, respectively. In the earlier surveys, more than 80% of the plants were 
infected with strain H each year. The remainder of the plants (14%) surveyed in 2002 appeared to 
be infected by a new strain with a distinctive RFLP banding pattern. Nucleotide sequencing is being 
conducted to identify the virus strain. Sugarcane plants with mosaic symptoms will be collected in 
2002 from a wider geographical area of the state and virus strains infecting the plants will be 
determined by RT-PCR-RFLP analysis. 



Incidence of Sugarcane Yellow Leaf Virus in Clones of Saccharum spp. in the World 
Collection at Miami and in the Collection at the Sugarcane Field Station, Canal Point 

J. C. Comstock 1 , J. D. Miller 1 and R. J. Schnell 2 

'USDA-ARS, Sugarcane Field Station, Canal Point, Florida 
2 USDA-ARS, National Germplasm Repository, Subtropical Horticultural Research Station, 

Miami, Florida 

Sugarcane yellow leaf virus (SCYLV) was detected in clones of Saccharum spp. in the World 
Collection and in the collection at Canal Point using a leaf mid-rib tissue blot immunoassay. The 
incidence of infection varied by the species of Saccharum. At Miami, approximately half the clones 
in the collection for each Saccharum spp. were sampled and the incidence of SCYLV in the clones 
was 7.0% for S. spontaneum, 74.5% for S. cfficinarum, 62.5% for S. robustum, 46.2% for S. sinense, 
and 14.0% for S. barberi. At Canal Point, there were only sufficient numbers of S cfficinarum, S. 
robustum and S. spontaneum clones to sample and the incidence of SCYLV was 59.7% for the 134 
clones of S. officinarum sampled, 60.7% for the 28 clones of S. robustum and 15.4% for the 52 
clones of S. spontaneum. The results clearly indicate that SCYLV is present in clones present in the 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

World Collection in Miami and that S. spontaneum and S. barberi are the two most resistant of the 
five species of Saccharum. 



Selection of Interspecific Sugarcane Hybrids using Microsatellite DNA Markers 

Y. B. Pan, T. Tew, M. P. Grisham, E. P. Richard, W. H. White and J. Veremis. 

USDA-ARS, Southern Regional Research Center, Sugarcane Research Unit 

Houma, LA 

Three types of species-specific DNA markers, namely, PCR, RAPD, and microsatellites, 
have been recently developed at the USDA-ARS, SRRC, Sugarcane Research Unit, Houma, 
Louisiana. Among these, the microsatellite markers are the most polymorphic and can produce 
distinctive fingerprints (or molecular alleles) among sugarcane varieties as well as their wild 
relatives. In 2001, 11 wild x elite biparental crosses were made that involved 10 clones of 
Saccharum spontaneum and six commercial-type sugarcane varieties. The S. spontaneum clones 
were used as maternal parents to explore the possible impact of their cytoplasm on our varietal 
development program. A problem associated with sugarcane breeding is the potential for self- 
pollination of the maternal wild parents. We have demonstrated in earlier work that self-pollination 
can occur even after a hot-water treatment to emasculate the maternal tassels. Therefore, some of 
the seeds were selfed progeny. Since S. spontaneum is on the Federal noxious weed list, direct 
planting of S. spontaneum (including selfed progeny) to the field is prohibited. To circumvent the 
planting of selfed S. spontaneum, we used microsatellite markers to screen the seedlings from these 
crosses while they were still in the greenhouse. In this presentation, we will show the percentage 
self-pollination in these crosses where the S. spontaneum flowers were hot-water treated. We also 
will demonstrate how microsatellite markers can be used to eliminate at the seedling stage unwanted 
selfs from the basic breeding and selection program. 



Development of Microsatellite Markers from Sugarcane Resistance Related Genes 

J. DaSilva 

Texas A&M University 
Weslaco, TX 

Microsatellites are arrays of short DNA sequence motifs, with 1 to 6 base pairs in length and 
are characterized by their hyper variability, abundance, reproducibility, Mendelian inheritance and 
co-dominant nature. The Microsatellite marker technique is simple, robust, reliable and suitable for 
a large throughput system. It is also applicable when the plant material available for analysis is 
limited in quantity and sufficiently quick to allow early decisions to be made prior to further 
screening. These advantages make the microsatellite technique a suitable tool for molecular 
selection in large breeding programs. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Expressed Sequence Tags (EST) in the sugarcane database were electronically searched for 
microsatellites and 402 were identified. Out of 267 (245 disease and 22 pest) resistance-EST 
investigated, 37 (34 disease and 3 pest) were positive for the presence of microsatellites. PCR 
primers flanking these microsatellites were designed and tested as markers on ten sugarcane 
genotypes - four commercial hybrids and 6 wild genotypes. Polymorphisms were evident both at 
the commercial clones, as well as among the Saccharum species. The presence of microsatellites 
within disease resistance genes could be the flexible mechanism that sugarcane possesses to ensure 
response to a new pathogen. DNA rearrangements, resulting from slippage during replication, which 
is characteristic of microsatellite sequences, would be allowing the cane plant to generate novel 
resistance to match the changing pattern of pathogen virulence. 

In humans, a few disease genes carry tri-nucleotide microsatellites. A novel mechanism for the 
amplification of these microsatellites sequences seems to be the root cause of these genetic 
abnormalities. Should the same mechanism work in plants, mapping microsatellites markers from 
disease resistance EST may increase the probability of tagging resistance genes in sugarcane 
commercial as well as in wild germplasm. 

Microsatellites were also found in other 75 EST coding for proteins not related to disease 
resistance, such as sugar metabolism, and can be used as molecular markers for linkage mapping and 
tagging of other genes. 



The Effect of Temperature on Flowering and Seed Set in Sugarcane at Canal Point. 

J. D. Miller and S. Edme 

USDA-ARS 
Canal Point, FL 

South Florida experiences wide variation in the frequency and intensity of flowering in 
sugarcane in different years. The crossing program at Canal Point has maintained about 2000 pot 
cultures of at least 150 cultivars per year for each of the past 1 years. The individual cultivars have 
varied throughout the period but they are representative of the same genetic background. The 
number and time of emergence of tassels based on the number of tassels cut for use in crosses will 
be correlated to the minimum temperatures from September through January. The effect of low 
temperature on pollen fertility is well documented, but little information is available about the effect 
of low temperatures on tassels to be used as females. The plants used to produce the male tassels 
used in these crosses were protected from low temperatures by being moved into the crossing and 
photoperiod houses at night. The effect of temperature on flowering and seed set in sugarcane at 
Canal Point will be discussed. 



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Characterization of S. Spontaneum Collection for Juice Quality 

J. A. DaSilva and J. A. Bressiani 

Texas A&M University 
Weslaco, TX 

In order to utilize a wider germplasm sample and more efficiently explore wild Saccharum 
species for breeding purposes, we initiated the characterization of 94 S. spontaneum and 2 S. sinense 
clones from the Copersucar germplasm collection at Piracicaba, SP, Brazil. Laboratory analysis was 
carried out for juice quality of these genotypes. Data were collected for Brix, Purity, Reducing 
Sugar, Pol and Fiber. Within the spontaneum genotypes, values ranged from 7.2 to 16.5 for Brix, 
from 0.4 to 7.8 for Pol and from 21% to 45% for Fiber. 

Molecular marker analysis (southern) with an EST from Sucrose synthase as DNA probe on the 
DNA of 1 1 S. spontaneum genotypes is presented, showing polymorphism at this locus. Electronic 
search on sugarcane DNA sequence database shows Simple Sequence Repeats within genes 
controlling sugar metabolism. 

The analysis on juice quality showed a wide variation for sugar content among spontaneum 
genotypes, which suggests genetic variation for these traits within this species. The molecular data 
shows high polymorphism at the chromosome locus where the gene controlling the Sucrose synthase 
enzyme is located, suggesting that cane breeders could use molecular markers for marker-assisted 
selection to introduce positive alleles into commercial genotypes. Such a strategy would speed up 
the Back Cross method to introduce wild alleles in commercial varieties aiming to widen the narrow 
sugarcane genetic basis. 



Family Selection in Sugarcane: Notes from Australia 

C. A. Kimbeng 

Louisiana State University, Dept. of Agronomy 
Baton Rouge, LA 

Sugarcane breeding programs typically commence by evaluating a large number of seedlings 
derived from true seed. Mass selection applied at this stage of the program has been shown to be 
inefficient due to lack of replication, and the associated confounding effects of the environment. In 
Australia, the introduction of mobile weighing machines made it possible to implement family 
selection. Several research projects demonstrated that family selection when followed by mass 
selection was superior in terms of genetic gain and more cost effective than either family or mass 
selection alone. This combination of family and mass selection is now used routinely in all the 
Australian programs. Families are evaluated using replicated plots for cane (mechanically harvested 
and weighed) and sucrose yield in the plant crop. Individual clones are selected (mass selection), 
based mainly on visual appraisal for cane yield, from selected families in the first ratoon crop. 
Family selection is usually liberal with about 30 - 40 % of families selected. More clones are 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

selected from the best families with progressively fewer clones being selected from the moderate to 
average families. The availability of objective family data makes it possible to estimate the breeding 
value of parents using the Best Linear Unbiased Predictor (BLUP). This information is used to retain 
or drop parents from the crossing program and to plan better cross combinations. 



Assessment of Trends and Early Sampling Effects on Selection Efficiency in Sugarcane 

S.J. Edme, P.Y.P. Tai, and J.D. Miller 

USDA-ARS 
Canal Point, FL 

Quantitative data on agronomic traits are normally affected by field trends or spatial 
heterogeneity, which often mask the genetic potential of the tested varieties. To identify promising 
selections from Stage II clones with some degree of confidence, a moving means analysis was 
performed on 754 experimental sugarcane clones (CP 2000 Series) tested along with five check 
varieties distributed across three fields with unequal frequencies. The data were subjected to three 
different methods (linear, quadratic, and row x column) to remove any potential field trend, as 
revealed by the variance of the checks, and to approximate the true genotypic values of the clones 
under selection. The best method was chosen as the one that accounts for the greatest variance of 
trends and the least variance of checks. In field A (16 blocks of 43 plots each), cane (TCA) and 
sugar tonnage (TSA) were more efficiently assessed by the quadratic method (2 neighbors). For the 
clones in fields B (16 blocks of 23 plots each) and C (14 blocks of 10 plots each), a row x column 
method was more appropriate in analyzing TCA and TSA. The ranking of varieties changed 
significantly when comparing the adjusted values with the field data. Though positive and significant 
(^=0.44 and r brix =0.28, p=0.001), the correlation between early and late sampling revealed that the 
former is not indicative and predictive of the latter. Consequently, a late March sampling yielded 
32 additional clones for advancement to Stage HI, with Brix values ranging from 18.6 to 22.3. 
Further analyses are warranted to ascertain the benefit of these approaches as prediction methods for 
identifying the most promising clones. 



Selection and Advancement of Sugarcane Clones in the Louisiana "L" Sugarcane Variety 

Development Program 

K. P. Bischoff and K. A. Gravois 

LSU AgCenter Sugar Research Station 
St. Gabriel, LA 

The primary objective of the Louisiana "L" Sugarcane Variety Development Program is to 
efficiently develop improved sugarcane cultivars for the Louisiana sugarcane industry. Each year, 
300 to 600 crosses are made at the sugarcane breeding facilities of Louisiana State University Ag 
Center's Sugar Research Station located in St. Gabriel, La. This begins a process of selection, 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

advancement and testing which spans a period of 12 years culminating with the release of new 
sugarcane varieties to growers of the Louisiana sugar industry. Although the main goal of the 
program has never changed, procedures and techniques have evolved and improved over the years 
to the extent that this program is operating more economically efficient than ever. 

This paper will outline the procedures and techniques used by LSU personnel in the seedling 
production through infield testing phases of the Variety Development Program. For purposes of 
discussion, the numbers of clones moving through the program during the year 2001 will be used. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

MANUFACTURING ABSTRACTS 

The Florida Sugar Industry: Trends and Technologies 

J. F. Alvarez and T. P. Johnson 

Sugar Cane Growers Cooperative of Florida 
Belle Glade, FL 

The Florida Sugar Industry has been consistently improving the operation and efficiency of 
several sugar mills. The trends in operation and efficiency are first discussed followed by a survey 
of technologies and applications that cumulatively have contributed to these improvements in 
operation. The Florida Sugar Industry has consistently increased the processing rate while at the 
same time improving the overall recovery of sugar. No attempt is made to formulate cause and effect 
of the technologies, but general comments are made on the experience of some of the technologies 
and the possible trends that these technologies may take the industry in the future. The technologies 
covered are in the areas of milling, processing, and the power plant as well as quality control and 
information technology. The industry has benefited by borrowing and implementing technologies 
from other industries as well as from other sugarcane growing areas such as Australia and South 
Africa. The technologies involved range from computational fluid dynamics, new materials, digital 
and electronic devices and equipment, larger and more efficient sugar processing equipment, 
computer automation and information technologies. Technologies that are being developed that may 
change the sugar process are still years away from commercial implementation. The economic 
pressure of globalization will continue to force the Florida sugar industry to continue the 
technological trend. 

Versatility of the Antibody Dextran Test Method 

D. F. Day 1 , J. Cuddihy 2 and J. Rauh 2 

'Audubon Sugar Institute, LAES, Baton Rouge, LA 
2 Midland Research labs, Inc., Lenexa, KS 

The monoclonal antibody test (Sucrotest™, Midland Research Labs, Inc.) has proven be a 
versatile means of determining dextran. It can handle any dextran containing liquid sample and 
give a value in about one minute. It correlates very well with the Haze test. Samples ranging from 
the raw factory, to the refinery, to white sugar can be rapidly analyzed. The source of the sample 
is not important, whether it is from Mauritius or Louisiana this test produces reliable 
information. The test is being used in both raw factories and refineries world wide. Results 
showing the scope of uses, and correlations with existing methods will be presented. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Evaluation of a Near Infrared Spectrometer for the Direct Analysis of Sugar Cane 

L. R. Madsen II, B.E. White and P.W. Rein 

Audubon Sugar Institute, LSU AgCenter 
Baton Rouge, LA 

A Foss InfraCana Near Infrared (NIR) spectrometer was installed at Cinclare mill in 
Louisiana for the 2001/02 crushing season, to assess its suitability for direct analysis of cane 
delivered to the mill. The system prepared core-sampled cane in a Jeffco shredder and measured 
reflectance over a range of wavelengths. Analyses of cane by wet disintegration and by the existing 
core press method were used as the primary measurements. Calibration equations for pol, brix, fiber, 
moisture and ash in cane were produced. Values of standard errors were excellent, and prospects 
for the use of such an instrument for accurate direct analysis of cane look promising. 

Effect of pH and Time Between Wash-outs on the Performance of Evaporators 

G. Eggleston 1 , A. Monge 2 and B. Ogier 1 

'USDA-ARS-Southem Regional Research Center, New Orleans, LA 

2 Cora Texas Manufacturing Co., White Castle, LA 

Factory staff must consider all costs to make good economic decisions on how to improve 
the performance of evaporators. These include knowing optimum pH levels to minimize sucrose 
losses, and knowing when to wash-out evaporators to reduce the impact of scaling on sucrose losses. 
A comprehensive study was conducted at a factory during the 2001 grinding season, to determine 
the effects of time between evaporator wash-outs and pH on sucrose losses and overall evaporator 
performance. The factory operated Robert's Type calandria evaporators, with two (30,000 and 
25,000 ft 2 , respectively) pre-evaporators in parallel and three sets of triple-effect evaporators in 
series. In this investigation the second set of triple-effect evaporators was studied and each body was 
12,500ft 2 . Retention times were 11.4 and 9.5 mins in the two pre-evaporators, respectively, and 
increased from 1 0.0 to 2 1 .8 mins across the triple-effect evaporators. Gas chromatography was used 
to determine glucose, fructose, and sucrose concentrations in and out of the evaporators. Changes 
in Brix adjusted pH, Brix, color and turbidity, as well as chemical analyses of condensates were 
monitored. Most sucrose losses to inversion occurred in the pre-evaporators and were more a 
function of temperature, heating surface, and pH than retention time. Sucrose inversion occurred 
in the first and second evaporator bodies only when scale had built up -3-4 days after a wash-out 
and, generally became worse until the next wash-out. Although color formed in the pre-evaporators, 
it was relatively less than what occurred in the first and second evaporators. Increasing the factory 
target pH of the clarified juice (CJ) or final evaporator syrup (FES) systematically reduced losses of 
sucrose and a target FES pH of -6.3-6.4 is recommended. A target CJ pH of 6.7, giving an 
equivalent FES target pH of 5.9, caused approximately 1 .97-3.05 lbs sucrose lost/ton of cane in the 
pre-evaporators from mid to late season, whereas a target CJ pH of -7.1 and FES pH of 6.3 reduces 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

this loss to 1 .46-2.28 lbs sucrose lost/ton of cane. More sucrose losses occur at the beginning of the 
season. Further recommendations are discussed. 



Maximize Throughput in a Sugar Milling Operation using a Computerized Maintenance 

Management System (CMMS) 

K. A. Elliott 

Maintenance Systems Technology (MST) (Pty) Ltd 
Pretoria, South Africa 

The sugar industry relies on expensive mechanical plant for sugar production. Loss of 
production during the crushing season due to downtime means huge revenue losses. Excessive 
downtime and high maintenance costs can be avoided if a throughput focused CMMS Software 
system is implemented. The CMMS provides valuable information to base decisions on, but also 
enables valuable operational tools to ensure an optimized availability and sustained throughput. 

This paper presents a success story about a CMMS implementation at 14 sugar mills in 
Southern Africa, for a leading, global, low cost sugar producer and a significant manufacturer of 
high- value downstream products. The group has extensive agricultural and manufacturing operations 
in Southern Africa. Group sugar production of almost 2.0 million tons of sugar derives from South 
Africa at 1 .25 million tons, Malawi 240 000 tons, Swaziland 220 000 tons, Zambia 205 000 tons and 
Tanzania 75 000 tons. 

By implementing a focused and effective Maintenance Management System, the Group was 
able to ensure operational reliability during the crushing season, and improved uptime, without 
sacrificing maintenance expenditure. The paper highlights the challenges that the business faced, 
provides a roadmap to the implementation, as well as the realized benefits as a result of the 
implementation. 

The steps to adopting a philosophy of Scientific Maintenance Management and Total Quality 
Management (TQM) for the two distinct phases of Plant Maintenance namely, Production Season 
and Off-crop, demand the following key elements that will direct Maintenance in the business: 

Taking a life cycle long term view. 

Defining key performance indicators that are measurable. 

Ensuring Quality at the source of work execution. 

Basing decisions first on factual information and cross checking it with historical information. 

Challenge past maintenance practices. 

Focusing on prevention rather than cure. 

All maintenance work done in both the crushing season and the off-crop, have as its primary 
objective the reduction of Lost Time Available during season and effective planning and 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 



management of off-crop maintenance, to reduce maintenance spend. This paper is based on the 
experience gained by the author and his associates from CMMS implementations over a period of 
15 years. 



Experiences with the First Full Scale Plate Evaporator in the North American Cane Sugar 

Industry 

N. Swift 1 , T. D. Endres 2 and F. Mendez 2 

'Alfa Laval, Richmond, VA 
2 Raceland Raw Sugar, Raceland, LA 

An Alfa Laval EC 700 plate evaporator was installed at Raceland Raw Sugar Corp during 
the 2001 crop. The evaporator was installed as a second effect booster. The unit ran for the last 34 
days of the 2001 crop with excellent results. On average 1500 TCD more was ground after the 
evaporator had been installed compared with the previous period. Steam economy improved by up 
to 1 30 pounds steam per ton cane. A heat transfer coefficient of around 390 BTU/ft 2 /F °(2.2 W/m 2 /C 
°) was achieved on average for the operating period. 



Organic Acids in the Sugar Factory Environment 

D. F. Day and W. H. Kampen 

Audubon Sugar Institute, Louisiana Agricultural Experiment Station, 

Baton Rouge, LA. 

Volatile and non-volatile organic acids (ranging from acetic, through lactic to higher acids) 
can be found in raw sugar process streams. They are products both of microbial degradation and 
decomposition of cane waxes. The concentrations increase from the primary juice to significant 
levels by the end of the separation process. The specific sources of some of these acids are traced and 
implications of their presence on corrosion and sugar recovery are highlighted. 



Experiences with Unwashed Cane at Raceland 

T. D. Endres 

Raceland Raw Sugar 
Raceland, LA 

Cane washing was stopped on the fifth day of grinding and remained off for around 70% of 
grinding. The performance of the plant in the extraction, steam generation and clarification various 
areas was monitored in order to assess the impact of this modus operandi. Overall sugar recovery 
was enhanced by 1 3 pounds of sugar per ton cane whilst operational difficulties in the extraction and 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

steam generation areas were minimal. Clarification of juice improved during periods of no washing 
whilst increased mud quantities experienced during this period could be handled if anticipated in 
good time. Attempts have been made to estimate the effect on recovery by comparing results during 
periods of washing and no washing. Work done by Birkett and Stein during 2000 suggests that the 
value of additional sugar to the industry by not washing cane is USD 1 8 million or USD 1 .2 per ton. 
This provides sufficient incentive to both growers and millers to work together to ensure that this 
practice remains sustainable. 






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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

POSTER SESSION 



Soil Erosion Research on Alluvial Soils Planted to Sugarcane: 
Experimental Approach and Preliminary Results 

T. S. Kornecki, B. C. Grigg, J. L. Fouss and L. M. Southwick 

USDA-ARS, Soil and Water Research Unit 
Baton Rouge, LA 

Each spring, quarter-drains are installed to carry runoff from sugarcane fields. Each meter 
length of quarter-drain requires removal of about 0.065 m 3 of soil, which is discharged on the ground 
surface. High intensity storms can cause soil erosion from these drains. The loose soil discharged 
during their construction is often washed into quarter-drains causing their drainage capacity to 
diminish by sedimentation. To address the quarter-drain soil erosion problem, a field experiment is 
being conducted on our research site in St. Gabriel, LA to study the effectiveness of applying 
polyacrylamide (PAM) to the soil-walls of the drain channel in reducing erosion. PAM has been 
shown to be effective in controlling soil erosion induced by irrigation water flows in surface 
channels. In March of 2002, PAM was applied as a spray directly to the soil-walls of the quarter- 
drains at a rate of 18 kg/ha in a split application with a concentration of 500 ppm. Soil erosion and 
sedimentation were measured after each storm event to develop a 3-D view of changes in cross- 
sectional shape of the quarter-drains. Preliminary data show that PAM preserved the original shape 
of semicircular quarter-drains through four consecutive storms in March and April 2002, totaling 19 
cm of rain. Where PAM was not applied, a gradual deterioration of the side-walls of the quarter- 
drain was visible including at transition points where erosion up to 3.0 cm was recorded. 
Comparison of quarter-drains with and without PAM showed that the average soil loss was 1 kg/m 
less for plots treated with PAM, and soil erosion from quarter-drains without PAM was 1 1 % higher. 
These preliminary results in using PAM to minimize soil erosion are encouraging, however, only 
results from the early spring storms have been recorded. The experiment is ongoing and more data 
will be collected during the current sugarcane season. 



Laboratory Rearing of the Parasitoid Cotesia flavipes on Sugarcane Borer Diatraea 

saccharalis 

G. Hannig and D. G. Hall 

United States Sugar Corporation 
Clewiston, FL 

The parasitic wasp Cotesia flavipes is being used as a biological control agent of an 
extremely important pest of sugarcane, the sugarcane borer Diatraea saccharalis. Cotesia are reared 
and then released into the field. The sugarcane borer is reared as well as a host in which Cotesia are 
oviposited and develop. This biological control program has been very successful in controlling 
sugarcane borers in the field. The percent acreage where sugarcane borer problems were solved 
exclusively with the parasitoid Cotesia flavipes increased by 32.7 % and 24.9 % in 1999 and 2000, 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

respectively. Acreage scouted where insecticide sprays were recommended went from 12,310 acres 
in 1998 to 4,041 acres in 1999 to 460 acres in 2000, which is a significant decrease in insecticide 
use. 



Disease Incidence and Yield Comparisons of KLEENTEK® Seedcane to Traditional 
Sources in Four Commercial Varieties in South Florida. 

J. L. Flynn 1 , K. Quebedeaux 1 , L. Baucum 2 , and R. Waguespack 3 

'Certis USA, Baton Rouge, LA 

2 U.S. Sugar Corp., Clewiston, FL 

3 Certis USA, Moore Haven, FL 

Replicated field plots were planted using seedcane from either Kleentek (KT), a 
commercially available healthy seedcane based on meristem culture, or progeny of hot water treated 
material (HT) for varieties CP89-2143, CP 85-1382, CP 80-1 827, and CP 70-1 133. Forthe latter two 
varieties, an on-farm field run (FR) source of seed cane was obtained (no recent heat treatment 
history). Disease incidence and yield evaluations were performed over a 3 -year crop cycle. The FR 
CP80- 1827 had a 1 00% incidence of RSD. All other sources tested negatively for RSD in plant cane. 
HT and FR material for all varieties except CP 70- 1133 were virtually 1 00% infected with Sugarcane 
yellow leaf virus (ScYLV). KT plots tested clean in plant cane. By second ratoon, ScYLV incidence 
in KT ranged from 10% in CP 70-1 133 to 27% in CP80-1827. 

Stalk counts were significantly higher for KT compared to HT for CP 89-2143 and CP85- 
1382 with overall advantages of 18.4% and 35%, respectively. Cane tonnage and sugar per acre 
yields averaged highest in the KT plots for all varieties. Significant increases in cane tonnage in KT 
over HT were noted for all varieties except CP 70- 1 1 3 3 . Percent sugar yields were lower for the KT 
vs. HT for CP 85-1382. KT and HT % sugar yields were lower than FR in the CP 80-1827. 
Significant advantages in sugar per acre were found for KT vs. HT for CP 89-2 143 and CP 85-1 382 
and for KT vs. FR for CP 80-1 827. Over the crop cycle, sugar per acre yields of KT were 25.3% and 
39.4% higher than HT for CP 89-2143 and CP 85-1382, respectively. Forthe older varieties (CP 80- 
1827 and CP 70-1133) KT yielded 18.1% and 20.4% more sugar per acre than HT and FR, 
respectively. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

AMERICAN SOCIETY OF SUGAR CANE TECHNOLOGISTS 

EDITORIAL POLICY 

Nature of papers to be published: 

Papers submitted must represent a significant technological or scientific contribution. Papers 
will be limited to the production and processing of sugarcane, or to subjects logically related. 
Authors may submit papers that represent a review, a new approach to field or factory problems, or 
new knowledge gained through experimentation. Papers promoting machinery or commercial 
products will not be acceptable. 

Frequency of publication: 

The Journal will appear at least once a year. At the direction of the Joint Executive 
Committee, the Journal may appear more frequently. Contributed papers not presented at a meeting 
may be reviewed, edited, and published if the editorial criteria are met. 

Editorial Committee: 

The Editorial Committee shall be composed of the Managing Editor, Technical Editor for 
the Agricultural Section, and Technical Editor for the Manufacturing Section. The Editorial 
Committee shall regulate the Journal content and assure its quality. It is charged with the authority 
necessary to achieve these goals. The Editorial Committee shall determine broad policy. Each editor 
will serve for three years; and may at the Joint Executive Committee's discretion, serve beyond the 
expiration of his or her term. 

Handling of manuscripts: 

Four copies of each manuscript are initially submitted to the Managing Editor. Manuscripts 
received by the Managing Editor will be assigned a registration number determined serially by the 
date of receipt. The Managing Editor writes to the one who submitted the paper to inform the author 
of the receipt of the paper and the registration number which must be used in all correspondence 
regarding it. 

The Technical Editors obtain at least two reviews for each paper from qualified persons. The 
identities of reviewers must not be revealed to each other nor to the author during the review process. 
Instructions sent with the papers emphasize the necessity for promptness as well as thoroughness in 
making the review. Page charges will be assessed for the entire manuscript for non-members. 
Members will be assessed for those pages in excess often (10) double spaced Times New Roman 
(TT) 12 pt typed pages of 8 1/2" x 11" dimension with one (1) inch margins. 

When a paper is returned by reviewers, the Technical Editor evaluates the paper and the 
recommendations of the reviewers. If maj or revisions are recommended, the Technical Editor sends 
the paper to the author for this purpose, along with anonymous copies of reviewers' 
recommendations. When the paper is returned to the Technical Editor, he/she will judge the 
adequacy of the revision and may send the paper back to any reviewer for further review. When the 

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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

paper has been revised satisfactorily, it is sent to the Managing Editor for publishing. A paper sent 
to its author for revision and held more than 6 months will be given a new date of receipt when 
returned. This date will determine the priority of publication of the paper. 

A paper rejected by one reviewer may be sent to additional reviewers until two reviewers 
either accept or reject the paper. If a paper is judged by two or more reviewers as not acceptable for 
the Journal, the Technical Editor returns it to the author along with a summary of the reasons given 
by the reviewers for the rejection. The registration form for the paper is filled out and returned to 
the Managing Editor along with copies of the reviewers' statements and a copy of the Technical 
Editor's transmittal letter to the author. The names of all reviewers must be shown on the registration 
form transmitted to the Managing Editor. 

If the paper as received is recommended by two reviewers for publication in the Journal, it 
is read by the Technical Editor to correct typographical, grammatical, and style errors and to improve 
the writing where this seems possible and appropriate, with special care not to change the meaning. 
The paper is then sent by the Technical Editor to the Managing Editor who notifies the authors of 
the acceptance of the paper and of the probable dates of publication. At this time, the Managing 
Editor will request a final version in hardcopy and on diskette in WordPerfect format from the 
corresponding author. 

Preparation of papers for publication: 

Papers sent by the Technical Editor to the Managing Editor are prepared for printing 
according to their dates of original submittal and final approval and according to the space available 
in the next issue of the Journal. 

The paper is printed in the proper form for reproduction, and proofs are sent to the authors 
for final review. When the proofs are returned, all necessary corrections are made prior to 
reproduction. The author will be notified at the appropriate time to order reprints at cost. 

Any drawings and photographs for the figures in the paper are "scaled" according to their 
dimensions, the size of lettering, and other factors. They are then sent to the printer for camera work. 
Proofs of the illustrations are sent to the authors. Any changes requested at this stage would be 
expensive and authors will be expected to pay the cost of such changes. 

Reprinting in trade journals has the approval of the Editorial Committee provided: a) no 
article is reprinted before being accepted by the Journal; b) credit is given all authors, the author's 
institutions, and the ASSCT; and c) permission of all authors has been obtained. Summaries, 
condensations, or portions may be printed in advance of Journal publication provided the approval 
of the Editorial Committee has been obtained. 









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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

RULES FOR PREPARING PAPERS TO BE PRINTED IN THE 
JOURNAL OF THE AMERICAN SOCIETY OF SUGAR CANE TECHNOLOGISTS 

Format 

Unless the nature of the manuscript prevents, it should include the following sections in the 
order listed: ABSTRACT, INTRODUCTION, MATERIALS and METHODS, RESULTS, 
DISCUSSION (OR RESULTS AND DISCUSSION), CONCLUSIONS, ACKNOWLEDGMENTS, 
and REFERENCES. Not all the sections listed above will be included in each paper, but each 
section should have an appropriate heading that is centered on the page with all letters capitalized. 
Scientific names shall be italicized. 

All material (including tables and figures) shall be submitted on 8V2 X 11 inch paper 
with one inch margins on all sides. If using WordPerfect, set the bottom margin at 0.5 inches. 
This will set the page number at 0.5 inches and the final line of text at 1 inch from the bottom 
margin. Exactness in reproduction can be insured if electronic copies of the final versions of 
manuscripts are submitted. Authors are encouraged to contact the managing editor for specifics 
regarding software and formatting software to achieve ease of electronic transfer. 

Authorship 

Name of the authors, institution or organization with which they are associated, and their 
locations should follow the title of the paper. 

Abstract 

The abstract should be placed at the beginning of the manuscript, immediately following the 
author's name, organization and location. The abstract should be limited to a single self-contained 
paragraph of about 250 words. State your rationale, objectives, methods, results, and their meaning 
or scope of application. Be specific. Identify the crops or organisms involved, as well as soil type, 
chemicals, or other details that figure in interpretation of the results. Do not cite tables, figures, or 
references. Avoid equations unless they are the focus of the paper. 

Tables 

Number the tables consecutively and refer to them in the text as Table 1 , Table 2, etc. Each 
table must have a heading or caption. Capitalize only the initial word and proper names in table 
headings. Headings and text of tables should be single spaced. Use TAB function rather than 
SPACE BAR to separate columns of a table. 

Figures 

Number the figures consecutively and refer to them in the text as Figure 1, Figure 2, etc. 
Each figure must have a legend. Figures must be of sufficient quality to reproduce legibly. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Drawings & Photographs 

Drawings and photographs must be provided separately from the text of the manuscript and 
identified on the back of each. Type figure numbers and legends on separate pieces of paper with 
proper identification. Drawings and photographs should be of sufficient quality that they will 
reproduce legibly. 

Reference Citations 

The heading for the literature cited should be REFERENCES. References should be arranged 
such that the literature cited will be numbered consecutively and placed in alphabetical order 
according to the surname of the senior author. In the text, references to literature cited should be 
made by name of author(s) and year of publication from list of references. Do not use capital letters 
in the titles of such articles except in initial words and proper names, but capitalize words in the titles 
of the periodicals or books. 

Format Example 

ITCHGRASS (ROTTBOELLIA COCHINCHINENSIS) CONTROL 
IN SUGARCANE WITH POSTEMERGENCE HERBICIDES 

Reed J. Lencse and James L. Griffin 

Department of Plant Pathology and Crop Physiology 

Louisiana Agricultural Experiment Station, LSU Agricultural Center 

Baton Rouge, LA 70803 

and 

Edward P. Richard, Jr. 

Sugarcane Research Unit, USDA-ARS, Houma, LA 70361 

ABSTRACT 

INTRODUCTION 

MATERIALS AND METHODS 

RESULTS AND DISCUSSION 

Table 1. Visual itchgrass control and sugarcane injury as influenced by over-the-top herbicide 
application at Maringouin and Thibodaux, LA, 1989. 

CONCLUSIONS 

ACKNOWLEDGMENTS 

REFERENCES 

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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

GUIDELINES FOR PREPARING PAPERS FOR JOURNAL OF ASSCT 

The following guidelines for WordPerfect software are intended to facilitate the production 
of this journal. Authors are strongly encouraged to prepare their final manuscripts with WordPerfect 
6.0 or a later version for Windows. Please contact the Managing Editor if you will not use one of 
those software packages. 

Paper & Margins : All material (including tables and figures) shall be submitted on 854 X 11 inch 
paper with one inch margins on all sides. To achieve this with WordPerfect, set the top, left, and 
right margins at one inch. However, set the bottom margin at 0.5 inches. This will place the page 
number at 0.5 inches and the final line of text at one inch. 

Fonts: Submit your document in the Times New Roman (TT) 12pt font. If you do not have this 
font, contact the Managing Editor. 

Alignment: Choose the full alignment option to prepare your manuscript. The use of SPACE BAR 
for alignment is not acceptable. As a general rule SPACE BAR should only be used for space 
between words and limited other uses. Do not use space bar to indent paragraphs, align and indent 
columns, or create tables. 

Do not use hard returns at the end of sentences within a paragraph. Hard returns are to be 
used when ending paragraphs or producing a short line. 

Place tables and figures within the text where you wish them to appear. Otherwise, all 
tables and figures will appear after your References section. 

Styles: Italicize scientific names. Do not use underline. 

Tables: Use Tab stops and the Graphics line draw option when constructing tables. Avoid the 
space bar to separate columns (see alignment). All lines should begin with the left most symbol in 
their left most column and should end with the right most symbol in their right most column. 

Citations: When producing Literature Citations, use the indent feature to produce text as below. 

1. Smith, I. M., H. P. Jones, C. W. Doe, 1991. The use of multidiscipline approaches to control 
rodent populations in plants. Journal of American Society of Plant Management. 10:383- 
394. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

CONSTITUTION OF THE 
AMERICAN SOCIETY OF SUGAR CANE TECHNOLOGISTS 

As Revised and Approved on June 21, 1991 
As Amended on June 23, 1994 
As Amended on June 15, 1995 

ARTICLE I 

Name. Object and Domicile 

Section 1. The name of this Society shall be the American Society of Sugar Cane Technolo-gists. 

Section 2. The object of this society shall be the general study of the sugar industry in all its 
various branches and the dissemination of information to the members of the 
organization through meetings and publications. 

Section 3. The domicile of the Society shall be at the office of the General Secretary-Treasurer (as 
described in Article IV, Section 1). 

ARTICLE H 

Divisions 

The Society shall be composed of two divisions, the Louisiana Division and the Florida 
Division. Each division shall have its separate membership roster and separate officers and 
committees. Voting rights of active and honorary members shall be restricted to their respective 
divisions, except at the general annual and special meetings of the entire Society, hereinafter 
provided for, at which general meetings active and honorary members of both divisions shall have 
the right to vote. Officers and committee members shall be members of and serve the respective 
divisions from which elected or selected, except the General Secretary-Treasurer who shall serve the 
entire Society. 

ARTICLE m 

Membership and Dues 

Section 1. There shall be five classes of members: Active, Associate, Honorary, Off-shore or 
Foreign, and Supporting. 

Section 2. Active members shall be individuals residing in the continental United States actually 
engaged in the production of sugar cane or the manufacture of cane sugar, or research 
or education pertaining to the industry, including employees of any corporation, firm 
or other organization which is so engaged. 

Section 3. Associate members shall be individuals not actively engaged in the production of sugar 
cane or the manufacture of cane sugar or research pertaining to the industry, but who 
may be interested in the objects of the Society. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

Section 4. Honorary membership shall be conferred on any individual who has distinguished 
himself or herself in the sugar industry, and has been elected by a majority vote of the 
Joint Executive Committee. Honorary membership shall be exempt from dues and 
entitled to all the privileges of active membership. Each Division may have up to 15 
living Honorary Members. In addition, there may be up to 5 living Honorary members 
assigned to the two Divisions jointly. 

Section 5. Off-shore or foreign members shall be individuals not residing in the continental 
United States who may be interested in the objects of the Society. 

Section 6. Supporting members shall be persons engaged in the manufacturing, production or 
distribution of equipment or supplies used in conjunction with production of sugar cane 
or cane sugar, or any corporation, firm or other organization engaged in the production 
of sugar cane or the manufacture of cane sugar, who may be interested in the objects 
of the Society. 

Section 7. Applicants for new membership shall make written application to the Secretary- 
Treasurer of the respective divisions, endorsed by two members of the division, and 
such applications shall be acted upon by the division membership committee. 

Section 8. Minimum charge for annual dues shall be as follows: 

Active Membership $10.00 

Associate Membership $25.00 

Honorary Membership NONE 

Off-shore or Foreign Membership $20.00 

Supporting Membership $50.00 

Each Division can assess charges for dues more than the above schedule as 
determined by the Division officers or by the membership at the discretion of the 
officers of each Division. 

Dues for each calendar year shall be paid not later than 3 months prior to the 
annual meeting of the member's division. New members shall pay the full amount 
of dues, irrespective of when they join. Any changes in dues will become 
effective in the subsequent calendar year. 

Section 9. Dues shall be collected by each of the Division's Secretary-Treasurer from the members 
in their respective divisions. Unless and until changed by action of the Joint Executive 
Committee, 50 percent of the minimum charge for annual dues, as described in Section 
8 for each membership class, shall be transmitted to the office of the General Secretary- 
Treasurer. 

Section 10. Members in arrears for dues for more than a year will be dropped from membership 
after thirty days notice to this effect from the Secretary-Treasurer. Members thus 
dropped may be reinstated only after payment of back dues and assessments. 

Section 1 1 . Only active members of the Society whose dues are not in arrears and honorary 
members shall have the privilege of voting and holding office. Only members (all 
classes) shall have the privilege of speaking at meetings of the Society. 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

ARTICLE IV 

General Secretary-Treasurer and Joint Executive Committee 

Section 1. The General Secretary-Treasurer shall serve as Chief Administrative Officer of the 
Society and shall coordinate the activities of the divisions and the sections. He or she 
will serve as ex-officio Chairperson of the Joint Executive Committee and as General 
Chairperson of the General Society Meetings, and shall have such other duties as may 
be delegated to him or her by the Joint Executive Committee. The office of the 
General Secretary-Treasurer shall be the domicile of the Society. 

Section 2. The Joint Executive Committee shall be composed of the elected members of the two 
division Executive Committees, and is vested with full authority to conduct the 
business and affairs of the Society. 

ARTICLE V 

Division Officers and Executive Committee 

Section 1. The officers of each division of the Society shall be: a President, a First Vice-President, 
a Second Vice-President, a Secretary-Treasurer or a Secretary and a Treasurer, and an 
Executive Committee composed of these officers and four other members, one from 
each section of the Division (as described in Section 3 of Article VH), one elected at 
large, and the President of the previous Executive Committee who shall serve as an Ex- 
Officio member of the Division Executive Committee. The office of the Secretary- 
Treasurer in this constitution indicates either the Secretary-Treasurer, or the Secretary 
and the Treasurer. 

Section 2. These officers, except Secretary-Treasurer, shall be nominated by a nominating 
committee and voted upon before the annual division meeting. Notices of such 
nominations shall be mailed to each member at least one month before such meeting. 
Ballots not received before the annually specified date will not be counted. 

Section 3. The Secretary-Treasurer shall be appointed by and serve as a non- voting member at the 
pleasure of the Division Executive Committee. The Secretary-Treasurer may not hold 
an elected office on the Executive Committee. 

Section 4. The duties of these officers shall be such as usually pertain to such officers in similar 
societies. 

Section 5. Each section as described in Article VII shall be represented in the offices of the 
President and Vice-President. 

Section 6. The President, First Vice-President, and Second Vice-President of each Division shall 
not hold the same office for two consecutive years. Either Section Chairperson (as 
described in Section 3 of Article VII) may hold the same office for up to two 
consecutive years. The terms of the other officers shall be unlimited. 

Section 7. The President shall be elected each year alternately from the two sections hereinafter 
provided for. In any given year, the Presidents of the two Divisions shall be nominated 
and elected from different sections. The President from the Louisiana Division for the 
year beginning February, 1970, shall be nominated and elected from the Agricultural 
Section. The president from the Florida Division for the year beginning February, 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

1970, shall be nominated and elected from the Manufacturing Section. 

Section 8. Vacancies occurring between meetings shall be filled by the Division Executive 
Committee. 

Section 9. The terms "year" and "consecutive year" as used in Articles V and VI shall be 
considered to be comprised of the elapsed time between one annual division meeting 
of the Society and the following annual division meeting of the Society. 

ARTICLE VI 

Division Committees 

Section 1. The President of each division shall appoint a committee of three to serve as a 
Membership Committee. It will be the duty of this committee to pass upon 
applications for membership in the division and report to the Secretary-Treasurer. 

Section 2. The President of each division shall appoint each year a committee of three to serve as 
a Nominating Committee. It will be the duty of the Secretary-Treasurer of the Division 
to notify all active and honorary members of the Division as to the personnel of this 
committee. It will be the duty of this committee to receive nominations and to prepare 
a list of nominees and mail this to each member of the Division at least a month before 
the annual meeting. 

ARTICLE VII 

Sections 

Section 1. There shall be two sections of each Division, to be designated as: 

1. Agricultural 

2. Manufacturing 

Section 2. Each active member shall designate whether he or she desires to be enrolled in the 
Agricultural Section or the Manufacturing Section. 

Section 3. There shall be a Chairperson for each section of each Division who will be the member 
from that Section elected to the Executive Committee. It will be the duty of the 
Chairperson of a section to arrange the program for the annual Division meeting. 

Section 4. The Executive Committee of each Division is empowered to elect one of their own 
number or to appoint another person to handle the details of printing, proofreading, 
etc., in connection with these programs and to authorize the Secretary-Treasurer to 
make whatever payments may be necessary for same. 

ARTICLE VIII 

Meetings 

Section 1 . The annual General Meeting of the members of the Society shall be held in June each 
year on a date and at a place to be determined, from time to time, by the Joint 
Executive Committee. At all meetings of the two Divisions of the Society, five percent 
of the active members shall constitute a quorum. The program for the annual meeting 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

of the Society shall be arranged by the General Secretary-Treasurer in collaboration 
with the Joint Executive Committee. 

Section 2. The annual meeting of the Louisiana Division shall be held in February of each year, 
at such time as the Executive Committee of the Division shall decide. The annual 
meeting of the Florida Division shall be held in September or October of each year, at 
such time as the Executive Committee of that Division shall decide. Special meetings 
of a Division may be called by the Executive Committee of such Division. 

Section 3. Special meetings of a Section for the discussion of matters of particular interest to that 
Section may be called by the President upon request from the respective Chairperson 
of a Section. 

Section 4. At Division meetings, 1 percent of the active division members and the President or 
a Vice-President shall constitute a quorum. 

ARTICLE DC 

Management 

Section 1. The conduct and management of the affairs of the Society and of the Divisions 
including the direction of work of its special committees, shall be in the hands of the 
Joint Executive Committee and Division Executive Committees, respectively. 

Section 2. The Joint Executive Committee shall represent this Society in conferences with the 
American Sugar Cane League, the Florida Sugar Cane League, or any other association, 
and may make any rules or conduct any business not in conflict with this Constitution. 

Section 3. Four members of the Division Executive Committee shall constitute a quorum. The 
President, or in his or her absence one of the Vice-Presidents, shall chair this 
committee. 

Section 4. Two members of each Division Executive Committee shall constitute a quorum of all 
members of the Joint Executive Committee. Each member of the Joint Executive 
Committee, except the General Secretary-Treasurer, shall be entitled to one vote on all 
matters voted upon by the Joint Executive Committee. In case of a tie vote, the 
General Secretary-Treasurer shall cast the deciding vote. 

ARTICLE X 






Publications 

Section 1 . The name of the official journal of the Society shall be the "Journal of the American 
Society of Sugar Cane Technologists." This Journal shall be published at least once 
per calendar year. All articles, whether volunteered or invited, shall be subject to 
review as described in Section 4 of Article X. 

Section 2 . The Managing Editor of the Journal of the American Society of Sugar Cane 
Technologists shall be a member of either the Florida or Louisiana Divisions; however, 
he or she shall not be a member of both Divisions. The Division affiliation of 
Managing Editors shall alternate between the Divisions from term to term with the 
normal term being three years, unless the Division responsible for nominating the new 
Managing Editor reports that it has no suitable candidate. The Managing Editor shall 

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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

be appointed by the Joint Executive Committee no later than 6 months prior to the 
beginning of his or her term. A term will coincide with the date of the annual Joint 
Meeting of the Society. No one shall serve two consecutive terms unless there is no 
suitable candidate from either Division willing to replace the current Managing Editor. 
If the Managing Editor serves less than one year of his or her three-year term, another 
candidate is nominated by the same Division, approved by the other Division, and 
appointed by the General Secretary-Treasurer to a full three-year term. If the appointed 
Managing Editor serves more than one year but less than the full three-year term, the 
Technical Editor from the same Division will fill the unexpired term of the departed 
Managing Editor. In the event that the Technical Editor declines the nomination, the 
General Secretary-Treasurer will appoint a Managing Editor from the same Division 
to serve the unexpired term. 

Section 3 . The "Journal of the American Society of Sugar Cane Technologists" shall have two 
Technical Editors, which are an Agricultural Editor and a Manufacturing Editor. The 
Managing Editor shall appoint the Technical Editors for terms not to exceed his or her 
term of office. Any Technical Editor shall be a member of either the Louisiana or 
Florida Division. Each Division will be represented by one technical editor at all times 
unless the Executive Committee of one Division and the Managing Editor agree that 
there is no suitable candidate willing to serve from that Division. 

Section 4 . Any member or nonmember wishing to contribute to the Journal of the American 
Society of Sugar Cane Technologists shall submit his or her manuscript to the 
Managing Editor. The Managing Editor shall then assign the manuscript to the 
appropriate Technical Editor. The Technical Editor shall solicit peer reviews until, in 
the opinion of the Technical Editor, two responsible reviews have been obtained that 
either accept (with or without major or minor revision) or reject the manuscript. For 
articles accepted with major revision, it shall be the responsibility of the Technical 
Editor to decide if the authors have satisfactorily completed the major revision(s). The 
Technical Editor may solicit the opinion of the reviewers when making this decision. 
The Technical Editors shall not divulge the identity of any reviewer. The Managing 
Editor shall serve as Technical Editor of any manuscript which includes a Technical 
Editor as an author. 

ARTICLE XI 

Amendments 

Section 1. Amendments to this Constitution may be made only at the annual meeting of the 
Society or at a special meeting of the Society. Written notices of such proposed 
amendments, accompanied by the signature of at least twenty (20) active or honorary 
members must be given to the General Secretary-Treasurer at least thirty (30) days 
before the date of the meeting, and he or she must notify each member of the proposed 
amendment before the date of the meeting. 

ARTICLE XII 

Dissolution 

Section 1 . All members must receive notification from the General Secretary-Treasurer of any 
meeting called for the purpose of terminating the Society at least thirty (30) days prior 
to the date of the meeting. After all members have been properly notified, this 
organization maybe terminated at any time, at any regular or special meeting called for 



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Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

that purpose, by an affirmative vote of two-thirds of the total honorary and active 
members in good standing present at the meeting. Thereupon, the organization shall 
be dissolved by such legal proceedings as are provided by law. Upon dissolution of the 
Joint Society, its assets will be divided equally between the two Divisions of the 
Society. Dissolution of the Joint Society will not be cause for automatic dissolution 
of either Division. Upon dissolution of either Division, its assets will be divided in 
accordance with the wishes of its members and in conformity with existing IRS 
regulations and other laws applicable at the time of dissolution. 

ARTICLE Xffl 

Assets 

Section 1. No member shall have any vested right, interest or privilege of, in, or to the assets, 
functions, affairs or franchises of the organization; nor any right, interest or privilege 
which may be transferable or inheritable. 



126 



Journal American Society of Sugarcane Technologists, Vol. 23, 2003 

AUTHOR INDEX 



Alvarez, J. F 108 

Bacon, T. L 99 

Baucum, L 114 

Bennett, A. C 96 

Bischoff,K.P 106 

Bressiani, J. A 40, 105 

Chandramohan, S 101 

Charudattan, R 101 

Cherry, R 98 

Comstock, J. C 71, 102 

Cox, M. C 20 

Cuddihy,J 108 

daSilva, J. A 40, 103, 105 

Day,D.F 108,111 

Deren, C. W 97 

Duchrow, M. J 101 

Edme,S. J 61,104,106 

Eggleston, G 109 

Elliot, K. A 110 

Endres, T. D Ill 

Flynn,J.L 114 

Fouss, J. L 113 

Glasgow, L 96 

Glaz, B 97, 98 

Gravois, K. A 106 

Grigg,B. C 113 

Grisham, M. P 102, 103 

Hall,D. G 8,99,113 

Hallmark, W. B 97 

Hannig, G 113 

Hawkins, G. L 97 

Hentz, M. G 100 

Jackson, W 93 

Johnson, R. L 93 

Johnson, M 96 

Johnson, T. P 108 

Kampen,W.H Ill 

Kimbeng, C. A 20, 105 

Kornecki, T. S 113 

Madsen, L. R 80, 109 

Martin, S 96 

Matichenkov, V. V 97 

McAllister, CD 99 

Mendez, F Ill 



Miller, J. D 61, 71, 102, 104, 106 

Monge,A. C 109 

Morris, D. R 97 

Muchovej, R. M 94 

Mullahey, J. J 94 

Newman, P. R 94 

Nuessly, G. S 100 

Obreza, T. A 94 

Ogier, B 109 

Pan,Y.-B 102,103 

Perdomo, R 97 

Posey, F. R 99 

Powell, J 96, 97 

Quebedaux, K 114 

Rauh, J 108 

Rawls, E. K 96 

Reagan, T. E 99 

Rein, P. W 80,109 

Richard, E. P 93,103 

Rosskopf, E. N 101 

Schnell,R.J 102 

Shine, J. M 61,96,101 

Snyder, G. H 97 

Southwick, L. M 113 

Swift, N Ill 

Tai,P.Y.P 61,106 

Tew,T. L 95,103 

Ulloa, M. F 97 

Vencovsky, R 40 

Veremis, J 103 

Viator, B 93 

Viator, C 93 

Waguespack, H 93 

Waguespack, R 114 

Watson, B 96 

White, B.E 80,109 

White, W.H 103 

Wiedenfeld, Bob 48 

Williams, G. J 97 



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