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Proceedings/Summaries

SECOND
EASTERN FORAGE
IMPROVEMENT CONFERENCE

held -at
Tie. ennsylvanta State University
University Park, Pennsylvania

I Lye a tel 77

ARS-NE-90
FEBRUARY 1978

AGRICULTURAL RESEARCH SERVICE e U.S. DEPARTMENT OF AGRICULTURE

PROCEED INGS/ SUMMARIES

of

SECOND EASTERN FORAGE IMPROVEMENT CONFERENCE

The Pennsylvania State University
University Park, Pennsylvania

July 14-15, 1977

Heinz Gasser, Chairman
Morris Decker, Vice Chairman
Jim Elgin, Secretary

Agricultural Research Service
United States Department of Agriculture

CONTENTS

Page
ENTRODUGTION .....- SEN GUSOaS TOO GRD O OOOO OCOaHA GL Seoeo mom Cop GUGUC aie cre erent V
SYMPOSIUM: A Forage Systems Approach to Grassland Production -
Chairman - A. M. Decker
The Application of Systems Analysis to Forage Research -
Eos babtenneimer, “iw a «rene s © «5+ Sacrenstees ts Diovwicy aie yevb ya's siehe's es Siaieisrerote 1
What Would the Parameters Look Like Should We Return to Grazing -
Siebee WATICH, % x12 Siacore cw Rutee ie relateleteis oisysrer wee ae. Pes Cate eat aes eae 9
Forage Production 20 Years from Now - Daniel P. Knievel ......... ae 21
CONTRIBUTED PAPERS: Session Chairman - Heinz Gasser
Forage-Animal Systems for Efficient Raising of Calves -
Re Ge eHammes, J©f., Re He Blaser, Hs fT. Bryant, J.P. Fontenot,
AMG IEUIEMO Oe mete ero se oe eels erctsie rate whe aiele sos Bia ialie a aves se eietece sats eo 32
Forage Systems for Fattening Steers with a Minimum of Grain
Feeding - H. T. Bryant, R. C. Hammes, Jr., R. E. Blaser,
Je P.. Fontenot, Frank McClaugherty, and Ralph Kline .......... cee WO
Progress in Developing Al-Tolerant Alfalfa - J. H. Elgin, Jr.,
an aisn eb MCMUEERCY AMC © cnc fava cicpa wo crseieheonens sis oie) evecs rere chohotevercnete aie 34
Measuring N Fixation in Seven Alfalfa Cultivars - J. H. Elgin, Jr.,
and We Or Legg eeeeece cececaeevoeevceeer eee ee eeee eee eee eeoeeeeceeee ee ee eee 35
Initiation of a Work Program to Isolate Disease Resistance in
Alfalfa in the Republic of Argentina - S. A. Ostazeski ...... ee SO
Contributions of Resistance to Anthracnose, Bacterial Wilt and
Phytophthora Root Rot to Persistence and Yield of Alfalfa under
Irrigation - G. R. Buss eecrececeecereeeeceeeeeoeeo eee e ee eee eee eeoeceeseaee Si
Ecological Factors Influencing Infection and Development of
Colletotrichum trifolii in Alfalfa - Ronald E. Welty ......... ee 38
Effect of Different Levels of Expression of the Multifoliolate
Character and Leaf-Stem Ratio on Forage Quality and Performance
of Alfalfa Synthetics - C. C. Lowe, R. P. Murphy, and
Mew Hey SUMP OL Oy cre) sig sa soo owls ore oS Soe S Soeeye elere) eee 8 sie fol sdavenerventyeletete 76 dieters 39

The Present Status of Verticillium Wilt in the United States -
J- H. Grahame R. N- Peaden, D. W. Evans, and J. H. Elein, Jr. ... 40

Effect of Root Lesion Nematodes on Yield of Forage Legumes and
Grasses Seeded Alone and in Mixture - C. B. Willis .......... eee!

PLT

BUSINESS MEETING

GONTERENCE RIGG PS TIAN TS os: ieve a0: «aires 6: on ne wie: scei-ee Se re egeee es

IV

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INTRODUCTION

The second Eastern Forage Improvement Conference held on the campus of The
Pennsylvania State University, University Park, Pennsylvania, was opened at
8:30 a.m., July 14, 1977, by Chairman Heinz Gasser. Dr. W. I. Thomas, Assoc-
iate Dean, College of Agriculture, The Pennsylvania State University, welcomed
participants.

The conference began with a symposium entitled "A Forage Systems Approach to
Grassland Production," for which three excellent papers were presented. These
Symposium papers are reproduced in full in this report.

In the afternoon following the symposium, the conference participants toured
The Penn State Rock Springs Agricultural Research Center. Many interesting
research studies were observed.

On the morning of July 15, 10 excellent contributed papers were presented.
Summaries are included in this report. The conference business meeting was
held in the afternoon.

The papers in this report are reproduced essentially as they were supplied
by the authors. The views of the participants are their own and do not
necessarily reflect the views of the U.S. Department of Agriculture.

Trade names are used in this report solely for the purpose of providing
specific information. Mention of a trade name does not constitute a guarantee
or warranty of the product by the U.S. Department of Agriculture or an endorse-
ment by the Department over other products not mentioned.

Left
THE APPLICATION OF SYSTEMS
ANALYSIS TO FORAGE RESEARCH «

E. J., Partenheimer*
Ue

Systems analysis had its origin in operations research programs of
World War II. Groups of scientists were assembled to tackle particularly
troublesome military problems. Since they were unfamiliar with many dimen-
sions of the problem, they had to acquaint themselves with all parts of an
operation. In doing so, they often began to question things that military
men had long accepted as fact. This questioning often led to solutions that
had escaped the military men.

One problem that perplexed these scientists was that there were often so
many highly interrelated parameters that no human mind could keep track of all
of them. Thus an improvement in one part of a system might lead to greater
problems in another part. The development of computers with large data stor-
age and retrieval capacities opened another avenue to attack this problem.
Mathematical models could be used to describe (simulate) the interrelation-
ships between the components of the system. Although mathematical models in
themselves were not new, their complexity could now be increased prodigiously
because of the computational and data handling capabilities of computers.

Thus systems analysis was born.

Early applications of systems analysis were in tactical and strategic
planning and gaming in the military. The space program brought it into the
public sector and large firms soon applied it to management problems. But the
job of the manager is similar to the job of the researcher. Both operate in an
environment of complex systems, both must deal with imperfect knowledge and
uncertainty, and both must perform the same tasks:

1. Problem recognition and definition (hypothesis formulation)

2. Observation (data gathering)

3. Analysis (hypothesis testing)

4. Make decisions (reach conclusions)

5. Take action (publish)

6. Accept responsibility for the decisions (stand peer review. We

might add that if the research is of any positive or negative

consequence there will eventually be a public review.)

Thus researchers soon found that they could benefit from an application of
the systems concepts to their research.

*Professor of Agricultural Economics, The Pennsylvania State University.

What is a System?

Churchman(1) says that "a system is a set of parts coordinated to accom-
plish some goal." Note that the definition emphasizes objectives. The
boundaries of a system are determined by its objectives. If an item contri-
butes to or limits the attainment of the objectives of the system it is a
part of the system. Objectives not only set the boundaries of the system but
they also determine the measures of performance used to evaluate the system.

We will return to the objectives later, but first let us describe the
other four basic considerations that Churchman(1) says we must keep in mind
when thinking about a system:

1. System environment

2. Resources of the system
3. Components of the system
4. Management of the system

The systems environment is made up of the fixed constraints of the system. In
other words they are beyond the control of the manager of the system. If the
Manager can do something about the item it is not a part of the environment,
it is a resource of the system. If we erroneously label one of these
resources as a part of the environment, we unnecessarily limit the means we
can use to reach the system's objectives. The resources are the means the
manager of the system uses to attain his objectives. The components of the
system are the parts or subsystems of the system we are studying. The manager
tries to determine the contribution of each component of the system. He must
constantly keep in mind that these subsystems interact with each other, and
that the performance of one subsystem affects the performance of others.

The function of the manager of a system is to control the operations of
the components of a system. If systems analysis is applied to the operation
of a firm the task of a manager is fairly obvious. But who performs the
manager's role in’the application of systems analysis to research? The
researcher himself performs the managerial function. The researcher, using
systems analysis, builds a system which is a model of a real world system.
Although the model does not duplicate reality, it must capture the essential
elements of reality. The model's objectives, environment, resources, and
components must correspond with the real world situation he is modeling.

Why Use Systems Analysis in Forage Research?

Forage research was conducted for a long time before the term "Systems
analysis'' entered our language. Even a cursory examination would lead to the
conclusion that much of it was very valuable. In fact many astute researchers
employed certain systems analysis concepts long before the term was used.
However the conscious application of the technique would have avoided many
errors and might have made the good researcher even more effective.

A major error that the systems analysis approach should help us avoid is
the choice of too small of a system within which to work. Each system is made
up of subsystems which are in turn systems made up of even smaller subsystems.
As knowledge has expanded researchers have divided themselves into narrower
and narrower fields, i.e., experts in smaller and smaller subsystems. Since
we feel more comfortable working in areas in which we are expert, we may tend
to define our objectives too narrowly. Let us choose a very narrow minded
alfalfa breeder to pick on. He might observe very low alfalfa yields on dairy
farms on a certain type of soil. Here is an opportunity for him to make a
real contribution by breeding an alfalfa that would produce better on this
soil type! His system, the plant itself, is too small a system to begin the
analysis. He is considering present alfalfa production practices and soil
conditions as a part of the environment of his system, when he should consider
them as components of an alfalfa production system. Starting from this larger
system he might decide that increased fertilization, alternative establishment
practices, or soil drainage are much more promising routes to improved yields.

We have expanded our thinking system from the alfalfa plant to an alfalfa
production system in which the plant is a subsystem. Although we are unlikely
to find an alfalfa breeder as narrow minded as our first example, we might
find one who thinks in terms of an alfalfa production system at times. The
goal towards which he directs his efforts is increased alfalfa yields. But no
farmer, except possibly some of those in five-acre alfalfa-yield contests, has
alfalfa yield as a major goal of his farm business. If we expand our thinking
from an alfalfa production system we open up many other alternatives, one of
which might be having our alfalfa breeder work on birdsfoot trefoil. Of
course we might also find that a lower alfalfa production on a larger acreage
might be more profitable than higher yields on a more limited acreage.

If we continued the expansion of our horizons we would find that the
first logical stopping place is the farmer himself. He is the first conscious
decision maker we meet. The objectives of our system must be compatible with
his objectives. Our research can contribute to the attainment of only one of
his objectives, a highly constrained income maximization goal. He wants to
obtain the highest income he can, subject to constraints imposed by his
physical and financial resources, his skills and abilities, and the attainment
of what are to him more important goals. Note that when we call the person a
dairy farmer we assume (1) he has decided his goals can best be attained by
devoting at least a part of his resources to farming and (2) the environment

and resources of his farm business require that a dairy herd be a major sub-
system of his farm business. Forage procurement is a subsystem of the dairy
subsystem. Alfalfa production is only one of many components of the forage
procurement subsystem. Not only could we produce many other forages but we
might purchase some of them. Of course we might meet the nutritional require-
ments with different forage and grain mixtures and there are alternative
levels of total nutrients that might be fed. Even if the feeding system
included alfalfa there are alternative levels of alfalfa production and yields,
alternative cultural and harvest practices, and products with different
nutrient compositions to consider. Not only are there many alternatives but
the alternatives interact. The optimum selection in one subsystem affects the
selection of alternatives in other subsystems. Therefore all systems must be
optimized simultaneously.

To apply systems analysis to forage research our model must reflect the
objectives, environment, resources and components of the system in which the
users of the research operate. Failure to do so cannot only lead to research
of little value but it can also lead to wrong conclusions. In the early
1950's some agricultural economists in the Northeast gathered the latest
broiler feeding data from poultry nutritionists. Using perfectly correct
economic analytical techniques they came to the conclusion that profits per
batch of birds were maximized when broilers were fed to weights over six
pounds. Under conditions existing at that time their conclusion was correct,
but their recommendation that farmers feed their birds to these weights was
absolutely wrong for two reasons:

1. Although feeding birds to these weights maximized returns per batch
of broilers, it reduced the number of batches that could be raised
per year. The added net return per batch was far less than the
income sacrificed by reducing the number of batches.

2. The demand for birds of this weight was relatively small. If
significant numbers of producers had followed this advice, the price
for heavy birds would have decreased drastically.

These researchers had defined an objective that was different from the objec-
tive of the users of the research results. Consequently they optimizec a
subsystem of the system that should have been optimized.

Implementing a Systems Approach

We have seen that the first task in implementing systems analysis is to
define a relevant system. The next step is to construct a model of the system.
The system and thus the model will usually include many subsystems outside of
any one person's area of specialization. Going back to our dairy farm example
we would have, as a minimum, systems involving one or more specialities in
plant science, animal science, engineering and economics. One might get the

necessary information from these fields by reviewing literature, but often
mistakes are made in interpreting information from research in other fields.
Consultation with scientists in these fields is a better alternative than a
literature review only, but bringing specialists together to work in groups
will usually give superior results for two reasons. First by bringing the
person into the group he is likely to put more thinking and effort into the
project. More importantly, it allows the researchers to interact with each
other in a mutual learning process. If I have a question on alfalfa produc-
tion I can come to you and get the question answered, but I know so little
about alfalfa that there is a strong likelihood I will not ask all the rele-
vant questions. Thus a cooperative effort by specialists from relevant
fields is the ideal.

The area of emphasis will determine the detail with which each subsystem
will be modeled. For example, the initial emphasis in NE-111 will be on pro-
duction of alternative forages and the interaction of these alternative
forages with dairy cow nutritional requirements. To do this we must of course
incorporate a corn silage harvesting system. However the harvesting system
will initially be modeled with less detail than the production system. We
will incorporate only one or two corn silage harvesting alternatives selected
on the basis of work done under NE-/70.

Models of significant systems are usually so complex that they require
the data handling and computation capabilities of a computer. Two kinds of
models are commonly used for the types of systems we are discussing here.

The first is called simulation.1/ We write down each relationship within each
subsystem in mathematical form. We then do the same for the interrelation-
ships between the subsystems. Relationships can be linear or non-linear and
discrete or continuous. Input data can be deterministic or stochastic. Such
simulators do not optimize. They only compute the results obtained from a
specific set of input data. For example such a simulator could predict net
farm income with a specific crop production and feeding program for a 40-cow
dairy herd. We could find which of a number of such organizations gave the
greatest return but we could not tell if any of them were the most profitable
organization for the farm. Linear programming is the second type of model
commonly used. This is an optimizing model which selects the optimum combina-
tion of a set of activities subject to a set of constraints. Despite the fact
that the objective function and constraints are linear and all variables are
continuous, there are techniques for both approximating non-linear functions
and incorporating discrete variables. Although coefficients and constraints
are constants, we can use the model to determine the effect on the objective
function of alternative values for one or more of these constants. Inter-
temporal relations can also be included.

ty,

— The terms "simulation" and "simulation models" are used with a number of
meanings. Any good systems analysis model is a "simulation model" because
it simulates the most important aspects of reality. As I have used the term
"simulation" it refers only to non-optimizing models.

A systems model is verified by examining its internal logic. The ques-
tion asked is, "Are the relationships expressed consistent with the theory and
empirical data in the disciplines concerned with the various subsystems?" We
also test the model by using input data from observable real world situations
and seeing if model results compare with the actual results. Although we
would expect the computed and real world results to be similar we would not
expect them to be identical. The real world is infinitely complex while our
models must be finite. However major divergencies mean there is a conceptual
or modeling error which must be corrected.

Use of the Systems Model

One of the greatest values of systems analysis arises from the model
construction and verification process itself. Hallberg and Manchester(2)
state that:

Systems analysis provides us with a method of looking at the
complex web of interrelationships characteristic of economic

systems which could not be understood through introspection
alone. . . If we accomplish nothing more than putting such a
model together, it would be useful in providing a mechanism
for understanding how the complete system works--an important
contribution in Lts own rishe.

The completed model also functions as a learning device and as a testing
device. The first question one would likely ask is, "Which constraints and
coefficients have important impacts on the objective functions?" We could
parameterize these values to measure their impact on net income. This evalua-
tion of potential impact, plus the researcher's evaluation of the possibility
of attaining such changes, gives a measure of where research results are most
likely to be of importance. It is a guide to where research should be done in
each subsystem. In the same manner it can be used to evaluate a new alterna-
tive before time, money, and effort are devoted to developing the new sub-
system. For example, a person interested in a grass for midsummer pasture
might find that yields would have to be two tons of dry matter per acre after
deducting for trampling and contamination losses before it could compete with
stored forage. This information along with some knowledge of the yield
potential of the grass would give him an idea as to whether he should work
with this grass or devote his efforts to other areas.

After research within a subsystem is completed, the model can be used to
determine its impact. Parameterization of prices, yields, quantities of
resources, and resource ratios would show the types of situations in which the
research results should be applied.

The model can also be used to measure the impact of changes in the
environment of the system. For example it would measure the impact on income
and farm organization of a doubling of fuel prices, a rationing of fuel or
fertilizer, or the banning of a pesticide.

I believe that a conscious effort to think in terms of systems and to
apply systems analysis procedures will improve the productivity of our
research. As the complexity of farms increases, and as increased knowledge
forces greater specialization on researchers, it becomes even more important
to have a method of integrating research. I am certain that in this case the
whole will be worth more than the sum of its parts.

Literature Cited

(1) Churchman, C. W. The Systems Approach. Dell Publishing Co., N.Y., 1968.

(2) Hallberg, M. C., and A. C. Manchester. "Strategy for Development of
Systems Analytic Models--A Dairy Experience." Journal for the Northeast-

ern Agricultural Economics Council, Vol. II, No. 2, 1973.

ay
WHAT WOULD THE PARAMETERS LOOK LIKE

SHOULD WE RETURN TO GRAZING |

J.E. Winch
Department 6f Crop Science
University of Guelph

Introduction

During the 1950's corn was reintroduced into the northeast. This intro-
duction signalled the beginning of a trend towards an intensification in
farming never before witnessed. The pendulum swung towards corn. Farms were
reequipped, silos appeared, year-round feedlots developed and under many
situations monoculture became a byword. Although requiring higher production
energy inputs than the traditional forage crops, the relatively low cost of
nitrogen, fuel and machinery and the high yield made it profitable to produce
and feed silage and grain corn.

Concomitant, however, with the increased use of corn, attention was paid
to the production of quality stored feed from the traditional forage crops.
Production and feeding systems evolved utilizing a high grain component in
rations of dairy and steer finishing. Milk production per cow increased
markedly and offset the 50% reduction in cow numbers, 40% of which was
attributed to the increased use of concentrates and 22% to the increase in
forage quality (Reid 1977). Only the cow-calf operations remained pasture and
forage oriented.

The use of high grain rations and stored feeding systems are now being
examined particularly in view of the increasing scarcity and prices of fossil
fuel and recent high grain prices. As well, soil compaction has become a
problem with the use of heavy equipment and corn monoculture.

To assess the role pasture could play in reducing energy needs, the energy
inputs of high moisture corn, corn silage, hay and pasture were estimated and
were integrated into four feeding systems for finishing beef steers: 1) feed-
lot; 2) overwinter to pasture and feedlot; 3) overwinter to pasture and 4)
overwinter to pasture with grain. The energy inputs per pound of beef were
estimated on growing and finishing 400-pound steers. Assumptions were made on
buildings, equipment, cropping practices and feeding systems. Rates of gain
were set and the necessary feed requirements for the rate of gain were derived
from those set out by the National Research Council.

9

Table 1. Production Energy Inputs into Growing and Finishing Steers Under
Four Feeding Systems.*

__ -'---- + --—O017”0nmnWv SEES

Overwinter Overwinter Overwinter
Pasture Grain on Pasture
Feedlot Feedlot Pasture
Energy/1b. Beef (Kcal/1b) 3011 1908 1224 1292
Beef (lb/ac.) 857 35 472 201
Ac/Animal 0.70 1.69 Lay ATl Pap ALS:
Feed Costs ($/1b) 0.27 0.28 0.20 0.23

twinch, Je BE. et al, 1976. Notes on Agric, Univ. of Guelph XII No. 4.

Despite the many assumptions made in these calculations, the energy
inputs were sufficiently different under the four systems that some implicat-
ions could be made on the role of pasture in both beef and dairy production.

The use of corn silage and high moisture grain corn resulted in a high
level of energy input into beef (Table 1). However, in terms of land require-
ment and production per acre the "corn-feedlot" system was by far the most
efficient. Approximately three times the amount of land was required to
finish steers on pasture. Thus, the use of a feedlot and high energy rations
may be justified in areas where arable land is scarce and high in price. The
use of a partial feedlot system resulted in much lower energy inputs per pound
of product than the total feedlot system.

A combination of pasture and grain on pasture, however, markedly reduced
energy inputs. Grain feeding cannot be dismissed as unnecessary or
inefficient. For, grain in rations on pasture resulted in a higher rate of
gain; the energy input per pound of beef was as low; a reduction in pasture
acres occurred and the cost per pound gain was slightly less than with pasture
alone. All of these advantages agree with the findings of Mott et al, (1968),
Coleman (1977) and Hendrix (1975).

As the above implications can be applied to most livestock situations,
pastures and forages can be considered as a means of reducing energy inputs
into beef and milk. However, in order to attain maximum returns from forages
in systems good practices must be followed. Thus,the following 10 parameters
should be of concern.

Livestock 1. Design cropping and feeding systems for the type of livestock.
2 Set animal production levels.

3. Use proper grazing management.

4, Utilize excess production effectively.

5) Plan for a long grazing season.

6 Choose productive species.

7

Fertilize and control weeds.

Agronomic

10

Land 8. Use arable and roughland in livestock programs.
9. Use rotations.
10. Improve roughland.

I. LIVESTOCK PARAMETERS

Requirements for energy and protein vary with the size, type and product-
ion of the animal. With cows, the requirements increase from gestation
through to where the calf begins consuming additional feed. From that point
to weaning, the energy requirements of a beef cow remain fairly level. As any
increase in milk production requires an increase in energy and protein, it
follows that the requirements of a dairy cow would be higher than those of a
beef cow. As well as dairy calves are weaned early, the requirements of a
dairy cow would follow the lactation curve which would peak shortly after
calving. With growing and finishing beef the energy requirements gradually
increase with age. Total protein requirements are not as high as those of a
dairy cow.

On a herd basis, the requirements of these three classes of livestock
differ. With dairy cattle, as a constant flow of milk is required, breeding
will be staggered throughout the year. Thus, the cropping program must be
designed to provide the necessary nutrients at a level close to the peak
requirements throughout the year. On the other hand, with a beef cow herd,
usually one breeding date is used (spring or fall) and a "cyclic" nutrient
requirement may occur over the year. Likewise, with growing and finishing,
beef requirements for growing are relatively low but marked increases in
energy are required for finishing. These marked differences in animal
requirement among the livestock types points to the first parameter:

Parameter 1: Design cropping and feeding systems for the type of livestock,

As there is a high nutritive requirement for dairy cattle, there is a
greater need of high quality stored feed than in beef cow-calf enterprises.
As a result, it is difficult to fit a dairy system to the pattern or "rhythm"
of high-low crop production during the year. As such, a greater emphasis
must be placed on early cutting of perennial forages, preservation as silage,
the use of corn silage and the production of grain for feeding. The stored
feed will be used during the period when pasture is not available and to
supplement feed requirements when cattle are on pasture. Pastures consequently
should be highly productive and well managed. A series of pasture mixtures to
give continued supply of the quantity and quality of feed should be used.

In contrast, with beef cow-calf operations, the cyclic feed requirements
can be fitted into the "rhythm" of crop production that occurs throughout the
year. The necessity for high quality forage is not as important as that in
the dairy industry. During early gestation a 50-55% TDN hay crop and during
late gestation and early lactation a 60% TDN hay crop would be adequate for
nutrition. This quality would be supplied by late cut hay (late June, early
July) from a legume-grass mixture. The aftermath could be used as part of the
pasture program. The higher energy requirements would occur during early
spring (for spring calving) and could be supplied from early pastures as well.

ETE

If pastures were managed correctly adequate nutrition would be available
until the calf was weaned in the fall. Therefore, pastures would form the
major quality component of the system.

To the cow-calf system, however, should be added that of the growing and
finishing of beef cattle. The addition of this component in a cow-calf
program would not add greatly to the need for high quality feed except perhaps
grain. The weaned calves can be carried over winter, placed on pasture in the
spring and sold when pasture is short (July-August) or kept and finished with
grain.

Pasture in all cases should supply all the requirements for maintenance
and as much as possible of the production requirements. However, whether or
not pastures will supply the energy and protein requirements for production
will depend upon the level of animal production desired. This choice of the
level of production is the second parameter:

Parameter 2. Set animal production levels.

With dairy it has been the practice to "go to maximum" production in
North America. In Europe, farm operators appear to be more satisfied with
less than maximum. Maximum production will require grain in addition to
pasture herbage and with milk quotas often high milk production is justified
and economical as dairy operators have a "guaranteed price.'' This is not true
either with the beef finishing or beef-cow industry.

In addition to this complex question of the economics and energy
implications of high level production, there also remains the question of herd
health. It is assumed that the number of lactations over the life span of the
cow is reduced with high levels of production.

It is suggested therefore that thought be given to lowering levels of
production per animal in order to place greater reliance on pastures which in
turn would offset the dependence on grain. This focuses attention on the
potential of pasture.

Reid (1977) suggested that the ultimate output of milk possible from
pasture or forage would be 34 kg per day (74 1b.). This would require a 70%
D.E. forage and be consumed at a rate of 3.3% of body weight. With growing
and finishing cattle a level of 1.25 kg/day (2.6 1b.) of body weight is
possible on an all-forage diet. There is no doubt that a 1000-pound beef cow
could produce the necessary milk for a calf on good quality pasture. These
upper limits therefore should be in place and it must be managed properly. It
is known that the digestibility of forages decreases with maturity. In all
cases where herbage is grazed at the proper stage (approx. 8-10") the digest-
ibility is approximately 70 to 75% IVD with a protein content of about 25%.
If it were possible to present forage to the animal at this level, the upper
production limits could be attained.

Presenting herbage to the animal at this stage or level is complicated
and suggests the third parameter.

2

Parameter 3. Use proper grazing management.

It is suggested that some selectivity be permitted to the animals in any
one grazing. By so doing the probability of maintaining a production level
would be greater as Hardison et al. (1954) suggested that some selectivity in
grazing would increase energy intake by 10-25%. However, the selectivity per-
mitted should not be as great as to lower productivity on an acre basis to any
great extent. The degree of selectivity permitted therefore must be a
function of "grazing judgement" by the operator, adequate planning and pasture
management.

Grazing judgement involves the number of animals, when animals should be
placed on and removed from a pasture. Planning is concerned with the develop-
ment of a pasture system including fencing. Pasture management includes fert-
ilizing application, clipping and harrowing.

Parameter 4. Utilize excess production effectively.

In operations where pastures are integrated with crops on arable or
machine land, the excess can be harvested as hay or silage and used as part
of winter feed or as a "feed back"' during the short pasture season of July and
August. This production which is in excess of that required by the production
herd could serve as a means of expanding from a beef-cow to a beef stocker
operation. The calves could be overwintered at a reasonable rate of gain and
fed this excess during May and June. When the pasture becomes short, the
cattle could be "sold light" or grain could be fed to decrease pasture con-
sumption and cattle could be finished; a greater efficiency of land use, cost
per pound gain and a reduction in the time to finish cattle would occur.

II. AGRONOMIC PARAMETERS

The length of the grazing season varies considerably from north to south.
In Ontario and the northern states of United States the period of grazing
varies from 120 to 180 days. In the more southerly regions the period may
extend up to 225 days in Missouri (Matches and Tevis 1973) to 365 days in the
far south. However, regardless of the length of grazing seasons throughout
the continent there is a need to provide adequate quantity and quality of
herbage from pasture over the grazing season.

This will involve developing a pasture program or system which consists
of a series of mixtures or crops that will provide the quantity and quality of
feed over the longest period possible within any geographical area. Usually
such a plan requires the development of a "core'’ pasture on which the cattle
are grazed for most of the season and the provision of early and late forage
mixtures or other crops. This sets the fifth parameter.

Parameter 5. Plan fora long grazing season.

Any extension of the grazing season into early spring and late fall
imposes two problems; the restriction posed by soil conditions and the

13

provision of feed during periods when production from the commonly available
species is either limiting or nonexistent. Animals should not be allowed on
land that is "wet" in the early spring or late fall. Land that is to be used
for early or late pasture must be well drained.

Few species save fall wheat, fall rye, fall rape and kale and some peren-
nial grasses produce during these periods. Fall wheat is a cash crop and as
spring grazing can be detrimental to yield of grain, this crop should not be
used during this period. Some grazing could be obtained in the fall. Fall
rye can provide excellent grazing from early April in the northern regions.
This crop could be grazed in the fall. Crops like rape and kale will provide
excellent fall pasture. The major disadvantage of these crops however, is that
if their production is intended for pasture only, they would require the use
of arable land for most of the year - no other crop could be produced on the
land.

Parameter 6. Choose productive species.

In order to be economical and provide feed at low cost, high production
is necessary. Thus, legumes should be the basis of all mixtures in the
program. They provide midsummer production and generally result in higher
intake and higher rates of gain than grasses (Lechtenberg et al.1975). There
are areas, however, where legumes may not be available and grasses will have to
be used. Although production from grasses can be economical (Sheard 1976),
the use of grass will increase the energy input into production markedly.

They require from 40 to 60 kg/ac nitrogen per year and fossil energy required
to manufacture nitrogen ranges from 20 to 24 Mcal per kg (Reid 1977).

There are two major legumes for use in the pasture programs in the north-
east; alfalfa and birdsfoot trefoil. Each of these species have character-
istics which make them useful. Generally alfalfa is "short lived" under
pasture conditions and will cause bloat. However, the high yield and early
spring growth and midsummer production (Table 2) make the species one of the
first to be considered. Alfalfa is adapted and used in the northeast where
soils are well drained and near neutral. Alfalfa should be used primarily
where high quality winter feed is required but can be utilized when aftermath
pasture is decreased. Experiments at Guelph indicated that grazing or
clipping early in the spring and in the fall was detrimental to persistence
(Fulkerson 1976). Alfalfa fits into the crop rotations and under hay/silage
aftermath pasture management systems alfalfa will persist sufficiently long to
satisfy the requirements of the rotation.

Birdsfoot trefoil is a key legume on imperfectly drained soil or on land
where long-term pastures are required. It does not cause bloat, has a reason-
able production during the midsummer but yields about 20% less than alfalfa on
"sood'"' alfalfa soil (Table 2). The domestic varieties such as Empire, Leo or
Carroll do not produce in early spring and must be considered for midsummer
and fall production of stockpiled forage. Matches (1976)* reported that
Cascade, a European type variety, performs better for "stock piling" than Leo
or Empire in Missouri. Trefoil remains green and reasonably high in quality
in the fall after growth stops in mid-September.

+Personal communication.

14

Table 2. Distribution of production of some perennial forages at Guelph.

Ib DM. /Ac.

Early Pasture Hay Pasture

May 20 July 15 OGE, 15

Alfalfa 1950 4260 2400
Birdsfoot Trefoil 570 4080 2400
Brome 2550* 5040* 1950
1248** 862%* 384

Tall Fescue 1460* 2800%* 2270
Orchard 1050%* 3160* 1400

x75: Ib/ac -N.
**No nitrogen applied.

Trefoil or alfalfa may not be used in all locations or under all condi-
tions. They do not produce or persist under shallow soil conditions (Watkin
and Winch 1974). Crown vetch appears to be better adapted to these situa-
tions. Recent work at Guelph indicates that cicer milk vetch (Astragalus
cicer L.} may be suited to such situations. It has a high yield, is earlier
in growth in the spring and has a wider range of adaptability to soil drainage
conditions than crown vetch. Astragalus glycophillis L. also appears to have
merit under very dry soil conditions.

The use of grasses should not be dismissed for they provide the best
method of preventing weed encroachment into pasture; they do not cause bloat
and in general begin growth earlier in the spring than most pasture legumes.

Southern bromegrass (Cv. Saratoga) is productive early in the spring if
nitrogen is applied. In contrast, tall fescue is somewhat less productive in
the spring than brome but provides higher yields of quality pasture in the
fall (Table 2). Tall fescue has been recognized as an ideal grass for stock-
piled pasture in many southern areas (Matches and Tevis 1973). Other grasses
such as perennial ryegrass, meadow foxtail and creeping foxtail have produced
very well in the spring under preliminary test. Altai wild rye and inter-
mediate wheat grass have produced as much stockpiled pasture as tall fescue
in Guelph (Winch 1976).

Any grass chosen to extend the season should be included in mixtures with
a legume and a suitable management system applied to insure the maintenance of
both species. Tall fescue, reed canary and southern bromegrass under a hay
Management system were found to be too aggressive for Empire trefoil. However,
managed as early pasture, late hay and late stockpiled pasture, both species
were maintained in the mixture. The spring growth was primarily grass and the
aftermath consisted mainly of trefoil. A reasonable proportion of grass to

15

legume occurred (40-60) in the stockpiled feed. The quality of each of these
mixtures at each period of the year was reasonably high (Table 3).

Table 3. Trefoil-Grass Mixtures for Early and Late Pasture, Guelph, Ontario.

Pasture Hay Stockpile
to mid-May mid-July mid-Oct.
Mixture (1b/ac)+ (ZIVD) (1b/ac)+ (ZIVD) (1lb/ac)t+ (%IVD)
Empire with:
Tall Fescue 1570 deo gk 3100 59.3 2540 65.8
Reed Canary 1670 1650 2/50 60.3 1790 60.9
Brome 1900 78.9 3030 56,0 1900 DOLL

taverage 4 stations 2 years.

On this basis, a mixture - management scheme could be envisaged as part
of a cropping and feeding system. Such a management system, however, would
necessitate the use of arable land.

The use of mixtures of legumes and grasses alone will not guarantee high
production. Legumes provide nitrogen but not potassium and phosphorus. In
addition in many areas lime may be necessary. Soils must be limed where
needed and levels of phosphorus and potassium should be applied.

As well, broadleaf weeds do invade stands of pasture, particularly in
long-term pastures or if they are overgrazed. Research has shown that the
inclusion of a grass will retard this invasion (Anderson and Winch 1974).
Clipping and/or herbicides should be employed to control weeds. These two
aspects suggest the next parameter.

Parameter 7. Fertilize and control weeds.

III. LAND PARAMETERS

Agriculturally, land has been classified into land use types. There are
two broad groups of land that are colloquially termed "machine" and "animal".
Both types of land should be considered as part of the total crop and feeding
program. This suggests the eighth parameter.

Parameter 8. Use arable and roughland in livestock programs.

Under the Canada Land Use classification "machine" land is considered to
be composed of classes 1, 2 and 3. There are no restrictions to the use of
modern machinery. The land is considered to be the most productive and offers
the flexibility of growing cereals, corn and forage crops.

16

Machine land has an opportunity value, and the inclusion of forages and,
in particular, pasture must be justified on the basis of returns of forage
crops to other crops that can be grown in the area (Petritz 1975).

However, despite the fact that in most cases, pasture will result in
lower returns than other crops, there is a complementary value which for the
most part has been ignored in this area of intensification of farming.
Forages improve soil tilth, add fertility and prevent erosion. In addition,
there is a potential saving in input energy that can be achieved through the
use of forage crops or arable or machine land.

In view of these considerations it is suggested that greater attention
should be paid to rotations. This suggests the ninth parameter.

Parameter 9. Use Rotations.

A rotation would permit stored feed to be produced (corn silage, hay or
hay crop silage) which is needed for most livestock feeding systems in the
northeast. In addition, grain could be purchased for feeding or for sale
depending upon prices. Likewise, the use of various crops would tend to off-
set the alterations that do occur in the opportunity values of any one.

It is feasible to arrange a series of forage mixtures that would provide
hay and/or pasture within the rotation. Likewise within the series, mixtures
could be devised to provide early and late pastures. Such mixtures would be
short-term and be composed of high-yielding legumes and grasses.

In contrast to machine land, the animal land (classes 4, 5 and 6, Canada
Land Inventory) cannot be used for the production of grain or intertilled
crops. There is much land of this type in the northeast. There is no
opportunity value. Production must be from forage and utilized through
grazing livestock.

At present the productivity from this type of land is low and the
distribution of production from the native species is poor. Sixty percent of
the total yield is produced in May and June (Table 4). This land has a much
higher potential following improvement.

Table 4. Distribution of Production from Unimproved and Improved Natural
Roughland Pastures, Ontario.

lb/ac D.M.
Mid-May July - end
and June August
Unimproved 1083 635
Improved (Trefoil) 2695 2199

taverage 24 locations over 4 years.

17

Parameter 10. Improve roughland.

The use of animal land, however, will not be without problems. The
inability to use modern machinery and equipment will create problems in the
improvement, in fertilization, weed control and the clipping of pastures.
Likewise, fencing will be a major concern.

Methods are available for "chemical improvement" of this type of land.
However, much more research is needed in this area. Under some situations the
use of renovator drills can be used. Under severe conditions, oversowing
methods must be employed. At the present time both of the methods of
establishment are less reliable than the conventional techniques. Less costly,
simple oversowing techniques employing grazing livestock should be investi-
gated. Preliminary work has shown that a satisfactory establishment of birds-
foot trefoil can be obtained under conditions where heavy grazing has been
employed during the establishment year (Table 5).

Table 5. Grazing on Establishment of Trefoil - Guelph.

Plants/sq. ft.

Grazing Dalapon No Dalapon Ave.t
Heavy 45 23 34
Light 9 Ly 10

+ :
Average 3 locations.

Likewise these lands; contain many species of perennial weeds; are low
in fertility and in eastern U.S. the soils are acid. Overcoming these
problems will require new methods and perhaps equipment for the application
of lime, fertilizer and weed control.

The use of aircraft for applications of fertilizer and broadleaf
herbicides may be feasible if the area to be improved is sufficiently large
to justify the use of an aircraft and sufficiently remote to permit the aerial
application of herbicides.

SUMMARY

Ten parameters have been derived which depict three major areas of con-
cern: livestock, agronomy and land. Each parameter is an important component
of developing the pasture program of a cropping and feeding system if we
should return to grazing or if we are to place a greater reliance on pasture
in the production of milk and meat. The overall objective of the system
should be to provide the quantity and quality of feed.

18

Parameters

hr
°

Design cropping and feeding systems for the type of
livestock.

Set animal production levels.

Use proper grazing management.

Utilize excess production effectively.

Plan for a long grazing season.

Choose productive species.

Fertilize and control weeds.

Use arable and roughland in livestock programs.
Use rotations on arable land.

Improve roughland.

Livestock

Agronomic

°

Land

OOON DUNK W
°

od

LITERATURE CITED

Anderson, G. W., and J. E. Winch. 1974. Effect of mixtures, herbicides and
management on weed invasion of trefoil pastures. Crop Sci. Dept.,
University of Guelph. Unpublished data.

Coleman, S. W. 1977. Energy supplementation of grazing cattle. Am. Forage
& Grassland Conf. Proc. 10th Conf. Columbia, Mo.

Fulkerson, R. S. 1976. Alfalfa management and reserves. Crop Sci. Dept.,
University of Guelph. Unpublished data,

Hendrix, K. S. 1975. Feeding grain to cattle on pasture. Agric. Exp. Sta.
W. Lafayette, Indiana Proc. Beef-Forage Day.

Hardison, W. A., J. T. Reid, C. M. Martin, and P. G. Woolfolk. 1954. Degree
of herbage selection by grazing cattle. J. Dairy Sci. 3/7:89-102.

Lechtenberg, U. L., W. H. Smith, and D. GC. Petritz. 1975. Performance of
cows and calves grazing orchardgrass, tall fescue and tall fescue-legume
pastures. Agric. Exp. Sta. W. Lafayette, Indiana Proc. Beef-Forage Day.

Matches, A. G., and J. B. Tevis. 1973. Yield and quality of tall fescue
stockpiled for winter grazing. Univ. Mo.-Columbia Misc. Publication 73-5.

Moti GeOs5, °C. L. Rhykerd, R. W. Taylor, T. W. Perey, and D. A. Huber. 1968.
Techniques for measuring the nutrition of pasture in pasture-grain feeding

systems. Am. Soc. Agron. Special Pub. 13.

Petritz, D. 19/75. Economics of feeding cattle on pasture. Agric. Exp. Sta.
W. Lafayette, Indiana Proc. Beef-Forage Day.

Reid, J. T. 19/77. Potential for increased use of forages in dairy and beef
rations. Am. Forage & Grassland Conf. Proc. lOth Conf. Columbia, Mo.

1S)

Sheard, R. W. 1976. Nitrogen fertilization of grasses. University of
Guelph. Unpublished data.

Watkin, E. M., and J. E. Winch. 1974.

An assessment of shallow soil
pastures in Ontario.

Ministry of Agriculture & Food, Toronto, Ontario.

Winch, J. E. 1976. Early and late mixtures for beef cattle.

Crop ser:
Dept., University of Guelph. Unpublished data.

20

oF fez
FORAGE PRODUCTION 20 YEARS FROM NOW?

Daniel P. evel

In an attempt to project what forage production might be 20 years from
now or around the year 2000, my approach will be 1) to review the importance
of forages in today's food supply, 2) to assess the expected demand for food
and forages in the future, 3) to review important economic relationships asso-
ciated with forage production and utilization, and 4) to project how these
factors might interact to influence forage production over the next two
decades.

Forages are vegetative parts of plants consumed by animals. Nearly 100
different plant species contribute to forages utilized in the United States.
The more traditional forages, such as grass and legume hay, silage, rotation
pasture, permanent pasture, and range are well known to many of us. We are
generally less familiar with crop residues and by-products of the food and
feed industries, but they can be important sources of forage in certain re-
gions of the country. As agronomists, our immediate concerns are frequently
associated with the production, management, physiology, or breeding of the
forage crop. However, we cannot forget that forages have little value until
they are converted by ruminant livestock into edible products. Utilized in
this way, forages have a tremendous economic value and can contribute to the
world food supply.

Demand for Food

It is impossible to adequately evaluate the future values of forage pro-
duction without considering the overall food and feed production and utiliza-
tion system in which forages revolve.

It has been said that there are only two absolutes in our society --
death and taxes. Over the next few decades it is safe to include a third
absolute; increasing worldwide demand for food. We have all heard of various
projections of world population growth and subsequent food shortages. A gen-
erally accepted estimate is that world population will be 6.5 to 7 billion
(vs. approximately 4.5 billion now) by the end of this century (National

1 : :

“< Invitational paper presented at the 2nd Eastern Forage Improvement Conference
Symposium: A Forage Systems Approach to Grassland Production, held at The
Pennsylvania State University, July 14-15, 1977.

* Journal Series Paper No. of The Pennsylvania Agric. Exp. Sta., Univ.
Park, PA 16802.

3 P :
Associate Professor of Crop Physiology, Dept. of Agronomy, The Pennsylvania
State University, Univ. Park, PA 16802.

20

Science Board 1974). Achievement of "zero'' population growth in the next 15
years would still result in an ultimate population 2.5 to 3 times larger than
at present. In its Third World Food Survey, FAO (United Nations Food and
Agriculture Organization) concluded that one-half of the world population
suffered from hunger, malnutrition, or both (FAO, United Nations 1963). in-
creased per capita demand for agricultural products by undernourished peoples
(Handler 1975) along with population growth was estimated by a University of
California food task force to require a near doubling of current world food
production over the next 25 years (Hodgson 1976b).

Forages and the Food Chain

Although humans are frequently considered to form the apex of the food
pyramid, other major components such as ruminant and nonruminant animals,
seed and grain crops, and forages provide the base that supports that apex.
This fact is represented diagrammatically in Figure 1. We have already noted
that forages do not support human nutrition needs directly, but are consumed
by ruminants which are subsequently consumed by humans. Grain crops, on the
other hand, are consumed by ruminant, nonruminant animals and humans. Of all
the components represented in the food pyramid, only nonruminant animals can
potentially be removed without causing an immediate collapse of the food pro-
duction system. Elimination of nonruminant animals as a source of animal
protein would require major changes in food consumption patterns in developed
countries. This could probably be accomplished over a several-year period
without seriously disrupting the quantity and nutritional quality of the total
food supply if present day feed grain production were shifted to production
of food grains. The other components of the food pyramid, grain crops, for-
ages, and ruminants will be an essential part of the world food supply through
this century and probably much longer. The importance of forages, and there-
fore ruminants, in future world food supplies becomes clear when one considers
present day and projected agriculture reality.

Current Forage Production and Utilization

Large land areas of the United States are presently devoted to the pro-
duction of forages (Table 1). Much of the permanent pasture and rangeland
(244.6 million hectares) is not suited for grain crop production because of
physical, edaphic or climatic limitations. These lands are best used by con-
tinuous management for forage production.

The importance of forages in our economy is further stressed by the fact
that a large land area suitable for grain crop production in the United States
is devoted to the production of hay and cropland pasture (Table 1). Almost
as much grain cropland was devoted to forage production (60.8 million hec-
tares) as. to grain production (65.5 miliion hectares).

On a broader basis, every major region of the world except Europe has
more land permanently devoted to forage production than to crop production
(Table 2). In addition, much of the cropland throughout the world is farmed
in rotations that include forage crops as part of the rotation. It can be
argued that some of the benefits of crop rotations could be maintained by
changing from legume forages in the rotation to edible seed producing legumes.

ae

Forage

Figure 1. Diagrammatic food pyramid representative
of developed countries.

Table 1. Land use for forage production in
the United States, 1973 (Adapted
from data presented by Hodgson 1976b) .*

Forage Million Hectares
Corn silage 555
Hay (all) 2D c2
Cropland pasture 55.0
Permanent pasture & range 244.6

Total $038.9

*Total land use for grain crop production was 63.5
million hectares.

23

Table 2. World land use for crops and forage produc-
tion (Adapted from data presented by Hodgson

1976b).
Permanent Meadows

Country Cropland and Pastures*

Million Hectares
Africa 209 797
North §& Central America 273 555
South America 87 385
Asia 482 557
Europe 144 91
Oceania 47 468
USSR DS? 375
USA* 190 244

World Total 1475 3,005

*Includes rangelands, but not forestlands that may be
grazed.

**A1lsSo included in North and Central America.

However, production and utilization of such crops would require more intensive
management, new market structures, and significant changes in food consumption
patterns. Although changes in this direction will probably occur in the fu-
ture, it is not likely to happen in the next 20 years.

The importance of forages to our economy is not overstated by figures on
land use. Production and utilization data support land use information. H. J.
Hodgson (1976a) recently calculated that 27% of the food nutrients consumed by
the average American each year have their origin in forages. With increasing
demands on grains for world markets and subsequent substitution of high energy
forage for grain in ruminant diets, it is likely this percentage will increase.
Beef and dairy animals, the primary consumers of forage, supply more than half
the protein consumed per person in the U.S. In addition, they supply to hu-
mans about 33% of the total energy intake, 50% of the fat, 80% of the calciun,
62% of the phosphorus, and significant quantities of other minerals and vita-
mins (Hodgson 1976b). It is clear from these figures that forages and their
ruminant ''partners' play an important role in today's economy. How can we
expect this relationship to change over the next two decades as worldwide
pressure increases for more human food?

Frequently in reports dealing with present and future world food require-
ments, discussions center around reducing animal numbers and increasing pro-
duction of grain for direct human consumption. To the uninformed, animals are
considered "wasteful"' elements of the human food chain. More grain production
will certainly be needed for more food. However, reducing ruminant animal
numbers will limit food supplies, not increase them.

24

We have already noted that significant land areas in the U.S. and the
world are likely to remain in forage production due to various physical limi-
tations. We have also seen that large cropland areas in the U.S. are devoted
to forage production. The ability of forages to compete with grain for these
lands will depend on several production factors. Four major considerations
are: 1) Future demand for animal products, 2) comparative dry matter and
nutrient yield ability of forages and grains, 3) comparative energy cost of
forage and grain production, and 4) efficiency of conversion of forage nutri-
ents to edible animal products.

Future Demand for Animal Products

The demand for animal products of meat, milk, wool, and hides and for
food and feed grain will undoubtedly increase throughout the world due to
increases in population. In addition, per capita consumption of these prod-
ucts has been projected to increase worldwide (Handler 1975).

Table 3 presents data showing recent trends in production of livestock
products in the United States. A high demand, as indicated by the 1972 pro-
duction level, exists for milk and beef. The 36% increase in demand for beef
suggests a per capita rise in demand of nearly 0.5 kg per person per year over
the next decade (Wedin et al. 1975). Production of nonruminant animal prod-
ucts also increased dramatically over the 1963 to 1972 period, pointing out
that demand for feed grain will also increase.

Table 3. Trends in production of livestock products in the U.S.
from 1963 to 1972 (Adapted from statistics presented
by: Wedanvet alt= 1975).

1972 Production

Commodity (10° kg) % Change
Milk 545507, - 4
Beef IS heat +36
Veal 208 -50
Lamb and mutton 246 -23
Pork Onley +10
Turkey E100 +44
Broiler 5,206 +58
Eggs (no.) 69,804 + 9

Higher demands for both beef and nonruminant livestock products will
result in increased demand for forages in two ways: 1) By increased numbers
of beef animals and 2) by the inevitable substitution of high quality forage
for concentrates in ruminant diets as concentrate prices increase. At the
present time, considerable amounts of concentrate are fed to dairy and beef
animals (Table 4). Concentrates made up 16% of beef and 37% of dairy animal
diets. Therefore, replacement of concentrates by forage will greatly add to
total forage demand.

25

Table 4. Forage and concentrate consumption by livestock in the
U.S. in 1974. Data are in millions of tons of feed
units.!/ (Adapted from Hodgson 1977).

Total Total %
Concentrate Forage Forage
Dairy 2602 46.0 63
Beef 56.6 189.4 84
Sheep and goats 0.8 6.7 90
All livestock 174.0 264.8 60
% by ruminants 36 91

1/

— A feed unit is the nutritional equivalent of 1 pound of corn.

Yields of Forage and Grain

Land resources needed to provide projected forage demand in the future
will also be sought for grain crop production. The comparative economics of
forage and grain production will ultimately determine how the land resources
will be used. Most of the crop land pasture and some of the land devoted to
hay production on U.S. farms is poorer in condition and less fertile than
that used for corn and other feed grains. Under these conditions highest
returns of energy and protein may be obtained from forage rather than grain
crops. Table 5 compares representative production data for corn and alfalfa
from moderately productive crop land subjected to good management. Yields of
dry matter and crude protein were highest when the land was managed for forage
than when managed for grain. Although these results may not represent all
crop land now in pasture, they emphasize that grain production may not be the
most efficient agricultural system for all lands now classified as crop land.

Table 5. Comparative dry matter yields and crude protein
from forage and grain crops grown on moderately
productive land with good management (Adapted
from:Cast Specialy Publ, Nowo4):.

Crude

Crop Dry Matter Protein
Lb/A Lb/A

Corn grain 4830 493
Corn silage 7667 636
Alfalfa hay 6805 a7:
Alfalfa silage FOOT 724

26

Energy Costs

Requirements for fossil energy and energy costs will be a major factor in
determining forage vs. grain production as prices of fossil energy increase

over the next decades.

47% to 56% of the total
Fertilizers account for
Crain eine re. US slat tlle
agriculture will become

Heichel (1973) calculated that fuel alone accounts for
cultural energy expended for modern crop production.
an additional 0.05% for soybeans to 19% for corn

doubt that the efficiency of fossil energy use in

more important to farmers and to the nation.

Table 6 lists digestible energy returned by various grain and forage
crops in relation to fossil fuels expended for their production. Grain crops
in the U.S. returned the least amount of digestible energy per unit of fossil
fuel energy consumed (fossil fuel efficiency). Lowest efficiency of 1.8 was
calculated for modern rice production in Louisiana. In contrast, rice pro-
duction in the Philippines under a nonmechanized, labor intensive system of
management achieved a fuel efficiency of 17.3. The difference in energy
efficiency between the two rice production systems represents the cost of
substituting mechanization in modern agriculture for hand production methods.
The return for this added fossil fuel cost to the Louisiana farmer was a
grain yield 3 times higher, and a labor requirement only 6.1% as high as that

in the Philippines.

Table 6. Digestible energy content of economic yield per
unit of fossil energy input for various crop
production systems (Adapted from data of Reid
1975 and Heichel 1973).

Crop

Soybean seeds
Rice (Louisiana - 1970)

Corn grain
Oats

Corn silage
Hay

Grass silage

Rice (Philippines - 1970)2/ 1
Pasture herbage 40 -

Digestible Energy
Fossil Energy Inputl/

(Mcal/Mcal)

Mm Wh Oe OF & © ©

00

1/ Inputs include energy costs of machinery construction

and repair,

fuel, fertilizer, seeds, pesticides, drying,

electricity, transportation, and food of workers.

2! Major inputs are labor.

yaa

Similar effects of increased use of mechanization are evident for forage
production. Forage harvested in the form of hay or silage produced 4.1 to 8.2
Mcal digestible energy per Mcal fossil fuel. This was 2 to 3 times more effi-
cient than that of grain crops. Forage managed for pasture had energy effi-
ciencies of 40 to 100, depending on the length of the grazing season. Values
for range would undoubtedly be higher still. Rising energy costs over the
coming decades will encourage a shift to less fuel intensive agricultural sys-
tems such as those involving forages.

Animal Feed Conversion Efficiency

Expanded use of animal based agricultural systems will depend on the
efficiency with which various types of animals can convert consumed feed nu-
trients to desirable animal products. Table 7 contains relative efficiencies
of conversion of feed nutrients to edible animal products by various classes
of livestock. The dairy cow ranks highest among both ruminant and nonruminant
livestock in efficiency of conversion of dietary nutrients to both energy and
protein. During lactation almost 90% of the feed intake is converted to gross
edible product. Nonruminants rank next highest in conversion of feed to food
nutrients, while meat producing ruminants rank lowest. It is clear that dur-
ing periods of severe grain shortage, it will be difficult to justify feeding
grain to meat producing ruminants. Depending on the severity of the shortage,
grain feeding to nonruminants may also be prohibitive. It is under these very
conditions that the ability of grazing ruminants to produce quality protein
from forage assumes major importance.

Table 7. Estimate of relative percentages of feed nutrients
converted to edible animal products by various
species (From R. E. Hodgson 1970).

Conversion Conversion Gross Edible Product

Animal to to Output as % of
Product Energy Protein Feed Intake

Milk 20 30 90

Beef 8 15 10

Lamb 6 10 7

Pork iS 20 30

Bogs 15 20 53

Broilers 10 25 45

Turkey 10 20 29

Table 8 compares the efficiency and energy cost of protein production
from various sources under "intensive" and "extensive" management systems.
Present day production practices are representative of the intensive system
where grains make up a Significant part of animal diets and fossil energy
plays a major role in crop production. Of the animal products, milk requires

28

Table 8. Efficiency of protein production under intensive and
extensive management systems (From Reid 1975).

Intensive: Sesnsaee! a
gm Protein Energy gm Protein Energy
Food Source Mcal DE Subsidy Mcal DE Subsidy
Mcal/kg Mcal/kg
Milk L258 14.9 12.8 6.3
Beef 27 5320 234 S156
Pork (hae 66.7
Corn grain Sey7:
Soybeans 6.0

teoneenenates providing 25%, 80% and 100% of DE to dairy cows,
feedlot cattle, and pigs, respectively, after weaning.

2/

— All forage diets to dairy and beef after weaning.

the least subsidy of fossil energy and is most efficient at using dietary di-
gestible energy for protein production. Beef and pork are inefficient in

these processes. The energy subsidy for protein production in milk was slight-
ly lower than that for corn production, but was still considerably hig’ °r than
the subsidy for soybean protein.

In the extensive management system, beef and dairy are fed all forage
diets from grazed and harvested forage. The fossil energy required to produce
milk and beef protein was considerably lower than for the intensive system.
The subsidy for milk protein was similar to that for soybean protein in the
intensive system. The energy subsidy for beef protein in the extensive system
is still high compared to plant protein. However, beef systems provide a
mechanism whereby low quality forages from pastures, crop residues, and food
and feed by-products can be converted to edible food.

Developing Forage Technology

At the present, time, /utilization of crop residues and cellulosic by-
products from industry for beef production is limited. Research on modern
day production systems utilizing these forage resources hes only recently
been initiated. Harvestable grain represents only about half of the above
ground dry matter of most grains. The remaining residue represents a vast
resource potential for conversion to edible food by ruminants.

There undoubtedly exists today the potential to develop artificial cellu-
lose digestion systems. Certain crop and many industrial residues could serve
as an energy source for microbial conversion to edible food. It is doubtful
that such a technology, even if highly efficient, would replace ruminant ani-
mals, however, because of the cost of gathering and transporting low value
residues to centrally located digesters.

29

Extraction of plant leaf protein for human consumption will probably be
an important food industry by the end of this century. The concept isn't a
new one as research on leaf protein concentrates has been in progress in vari-
ous countries for thirty years (Pirie 1971). Pilot plants implementing this
developing technology are already in operation (de Fremery and Kohler 1975).
The fibrous residue remaining after the soluble plant proteins are extracted
contains 76% of the original plant dry matter and makes excellent silage.
Chemical composition, silage quality, and dairy cow performance were shown to
be similar between protein extracted alfalfa residue and low-moisture alfalfa
Silage (Ream et al. 1975). Utilization of the fibrous residue is an important
part of the leaf protein concentrate system.

Oiiee expe ered Deve OpnentS

Due to the increasing value of harvested forage and the demand for high
energy forage in the future, production systems now in use will be improved.
New machine designs will be developed to reduce energy requirements for forage
harvesting and storing. Methods will be devised to significantly reduce dry
matter and quality losses during harvest, storage and feeding. Rapid methods
of assessing forage quality will gain widespread use in the near future.
Quality analysis will form the basis for marketing and feeding forage. Forage
yields will increase over the next 20 years, but no major yield breakthrough
will probably be obtained because of the genetic complexity and diverse nature
of forages.

Conclusions

1. Ruminant animals will remain an important part of the food production
system because of their ability to convert forages, crop residues,
and industrial cellulosic by-products to edible food.

2. Demand for high quality forages will increase over the entire period
as availability of concentrates for animal feeds declines.

3. a. Strong pressure will develop to go from intensive to extensive
forage utilization systems.

Extensive beef systems will be common in 10 years.

Few intensive systems will exist in 20 years.

Beef animal numbers will increase over the entire period.

Crop residues will form a major feed source for beef systems.
Dairy management will remain intensive over the period.

moanddsd

4. Most forage crops will be shifted to less fertile soils to make room
for grain crops by the end of this century. Corn as forage will
still be an important feed source for dairy systems.

30

LITERATURE CITED

Council for Agricultural Science and Technology. 1975. Ruminants as food
producers. Special Publ. No. 4.

de Fremery, Donald, and George O. Kohler. 1975. Alfalfa leaf protein con-
centrate. In Proc. Fifth Ann. Alfalfa Symp., pp. 45-54. Hershey, Pa.

FAO, United Nations. 1963. Third World Food Survey. Rome, Italy.
Handler, P. 1975. On the state of man. BioScience 25:425-432.

Heichel, G. H. 1973. Comparative efficiency of energy use in crop produc-
tion. *'Gonn. “(Storrs)” Agric. “Exp. Sta. Bull. 739.

Hodgson, H. J. 19/76a. The economic value of forage for livestock. In Proc.
Ninth Res. Ind. Conf. AFGC, pp. 83-86.

Hodgson, H. J. 1976b. Forages, ruminant livestock, and food. BioScience
26:625-630.

Hodgson, H. J. 1977. Forage research has taken a back seat. Hoard's Dairy-
man 122:591.

Hodgson, R. E. 1970. Place of animals in world agriculture. J. Dairy Sci.
54:442.

National Science Board. 1974. Science and the Challenges Ahead. Washington,
DIGs

Pirie, N. W. 1971. Leaf protein: its agronomy, preparation, quality and
use. IBP Handbook No. 20. Blackwell Scientific Publications, Oxford.

Ream, H. W., R. G. Koegel, N. A. Jorgensen, and D. A. Rohweder. 1975. Prog-
ress report - Harvesting, processing and feeding alfalfa juice protein con-
centrate and pressed alfalfa silage and utilizing deproteinized plant
juice. In Proc. Fifth Ann. Alfalfa Symp., pp. 55-69. Hershey, Pa.

Reid, J. T. 1975. Comparative efficiency of animals in the conversion of
feedstuffs to human foods. Proc. 1975 Cornell Nutrition Conference.

Wedin, W.¥Foj eis J.- Hodgson;-and N. L. Jacobson. 1975. Utilizing plant and
animal resources in producing human food. Animal Sci. 41:667-686.

Bik

x
Forage-Animal Systems for Efficient Raising of Calves.
R. C. Hammes, Jr., R. E. Blaser, He T. Bryant, J. P. Fontenot, and Jim Moore
Virginia Polytechnic Institute and State University, Blacksburg, Virginia

Forage-animal systems are being evaluated for beef calf production and
herd maintenance. The forage systems are: (A) bluegrass-white clover (Poa
pratensis L.-Irifolium repens L.) for April to December pasture and alfalfa-
orchardgrass (Medicago Sativa L.-Dactylis glomerata L.) for hay, herd and
creep grazing, (B) bluegrass- -white clover for April to December pasture and
tall fescue-red clover (Festuca arundinacea Schreb.-I. pratense L.) for hay,
herd and creep grazing and autumn stockpiling for winter grazing, and (C) same
as (B) except tall fescue-ladino clover for pasture. There are two calving
seasons for the Aberdeen Angus cows for each forage system (fall = Sept. to
Nov. and winter = Jan. to Mar.), two stocking rates (9 cows/7.3 ha and 6.1 ha)
for (A) and (B) and one stocking rate (9 cows/6.1 ha) for (C). Each system is
divided, 56% and 44% for the April to December pasture and hay or winter graz-
ing, respectively. Each system is managed for optimum forage and cattle pro-
duction. In (A) the herds are wintered on the bluegrass-white clover pasture.
Alfalfa-orchardgrass hay for winter calving cows is fed at a 5.9 kg/cow daily
until February 1 and then 9.5 kg until spring pasture. The procedure is re-
versed for fall calving cows. Fall born calves receive alfalfa-orchardgrass
hay ad libitum during winter on (A) and on (B) and (C) graze stockpiled fescue-
red clover and receive fescue-red clover hay ad libitum when needed. Winter
born calves receive no feed prior to spring pasture other than that available
to the cows. Cows remain on a system until removed for reproductive failure or
other health reasons. Maintenance P and K fertilizer is 0-34-65 kg/ha annually
for the tall fescue-red clover and bluegrass-clover and 0-44-84 plus 30 kg
borax/ha for alfalfa-orchardgrass. In addition, the fescue-red clover receives
78 kg N in August. The red clover is broadcast overseeded (5.6 kg/ha) each
March. Autumn growth has averaged 4,783 kg/ha (86.5% dry matter) hay equiva-
lent and 85-90% of available forage is utilized. Winter calving cows on (B)
light stocking and (C) have grazed year-round for three consecutive years.
System (B) heavy stocking, fall and winter calving and (C) fall calving have
needed hay each winter in addition to the stockpiled fescue. Daily weight
losses have been similar for (B) winter calving cows grazing stockpiled fescue
(heavy and light stocking) (0.70 kg) and for fall calving cows (B) and (C)
heavy stocking (0.60 kg). Body weight losses for cows (A) winter and fall
calving have been 0.64 and 0.52 kg, respectively. Body weight losses have been
regained on all systems during summer grazing except for winter calving cows on
(C) whose April to July gains are slower and average body weight tends to de-
cline annually. No reproductive problems have been encountered related to
forage system, calving season or stocking rate. Average daily gains 0.80 kg
(birth weight excluded) and weaning weights 254 kg for winter born calves have
been similar for (A) and (B) and stocking rates. Daily gains have averaged
0.78 kg and weaning weights 227 kg for (C). Fall born calves have responded to
forage systems similar to winter calves with daily average gains (0.06 kg) and
weaning weights (4.0 kg) lower than for winter born calves. Lower daily gains
for fall born calves are not fully reflected in weaning weights due to a longer
suckling period made possible by ample spring forage. A creep grazing proce-
dure has provided high-quality grazing for winter and fall born calves. Alfal-
fa stands have diminished under creep grazing. Pesticides limit flexibility in

creep grazing alfalfa in spring. A higher stocking level is indicated for (C)
than (B) but lower gains can be expected for winter or fall born calves.

OZ

oT
Cee Systems for Fattening Steers with a Minimum of Grain Feeding .
Heel. BEyanes hk. Go Hammes. Jn... R. E. Blaser, J; Ps. Fontenot,
Frank McClaugherty, and Ralph Kline
Virginia Polytechnic Institute and State University, Blacksburg, Virginia

The forage systems are based on the following three grass-legume forages:
(A) Kentucky 31 fescue (Festuca arundinacea Schreb.) and Kenstar red clover
(Trifolium pratense L.) at 13 and 9 kg/ha, respectively, (B) Kentucky bluegrass
(Poa pratensis L.) and Tillman ladino clover (I. repens L.) at 17 and 2 kg/ha,
respectively, and (C) Virginia 70 orchardgrass (Dactylis glomerata L.) and
Weevlchek alfalfa (Medicago sativa L.) at 6 and 17 kg/ha, respectively. To-
gether these forage mixtures provide year-round grazing. The fescue-red clover
mixture is grazed during the winter months, harvested for hay during the flush
spring growth, grazed, and beginning in early August allowed to accumulate for
winter grazing. The Kentucky bluegrass-white clover mixture is grazed during
the spring, summer, and fall. Alfalfa-orchardgrass when not needed for supple-
mental pasture is harvested for winter feed. The relationship between the
opportunity for selective grazing and live weight gains per animal and per
hectare is being studied. Five groups of cattle rotationally graze the forage
mixtures, two of the five groups of cattle rotationally graze approximately
half of the canopy (first grazers), and the remaining three groups of cattle
rotationally graze nearly all of the whole canopy (typical rotational grazers).
Therefore, the 'first grazers' have a greater opportunity for selective grazing
than the 'whole canopy grazers.' The effect on live weight gains of the cattle
when fed shelled corn on pasture at 0, .5, and 1% of their body weight is being
evaluated. The live weight gains of calves 9 months old, average weight at
start of experiment 249 kg, grazing four forage systems were compared with live
weight gains of yearlings 13 months old, average weight at start of experiment
261 kg, grazing three forage systems. The average daily live weight gains of
first grazers without corn supplements grazing fescue-red clover from November
to May were .64 and .8/7 kg per day for the calves and yearlings, respectively.
The same calves and yearlings rotationally grazing bluegrass-white clover and
fescue-red clover pastures without corn supplement, from May to July 19, had
average daily live weight gains of .67 and .58 kg, respectively. For calves
rotationally grazing the whole canopy of fescue-red clover, not supplemented
with corn, average daily live weight gain was .74 kg for the period November
to May. Their average live weight gain was .66 kg for May to July 19, when
Kentucky bluegrass-white clover pastures were included in the grazing rotation.
Calves and yearlings rotationally grazing the whole canopy of fescue-red clover
supplemented with corn at .5% of their body live weight during November to May
gained an average of .6/ and .89 kg a day. Increasing the corn level to 1% of
their body live weight, while rotationally grazing Kentucky bluegrass-white
clover and fescue-red clover from May to July 19 gave an average daily live
weight gain of 1.08 and 1.29 kg for the calves and yearlings, respectively.
Calves (first grazers) on stockpiled fescue-red clover, supplemented with corn
at .5%4 of body weight, had average daily live weight gains during November to
April of .91 kg; the same calves, rotationally grazing Kentucky bluegrass-white
clover and fescue-red clover from May to July 19, had average daily live weight
gains of .93 kg. The average daily gain was .94 kg and carcass grade was
‘average good' for yearling steers slaughtered in May after grazing stockpiled
fescue-red clover, supplemented with grain at 1% of. their body live weight from

November. Slaughter data will be obtained on yearlings in July and weanlings
in October and February.

33

\
mw a oe, >
Progress in Developing eae Alfalfa tC g@

J. H., Bletn, Jdr., and J. 5b. MeMurtrey Tit
Agricultural Research Service, USDA
Field Crops Laboratory, PGGI
| Beltsville, Maryland

[Aluminum \toxicity is believed to be a factor restricting root growth in the
acid subsoils of the Eastern U.S. Alfalfa is normally a deep-rooting crop
capable of utilizing both moisture and minerals in the lower soils, thereby
resulting in high levels of production even during short periods of drought.
Where toxic levels of aluminum occur, effective rooting is prevented and
alfalfa production is disappointing. Liming of the surface soils has little
effect on the acidity of the subsoils. Development of Al-tolerant alfalfa
is the logical solution.

Screening of Arc-related germplasm for tolerance to low pH Al-toxic condi-
tions began in July 1973 in wooden flats filled with Tatum soil. Tatum soil
is characteristically low in pH (4.0-4.5) and contains toxic levels of Al.
Approximately 3,000 seedlings were screened. After 2 weeks, seedlings with
the most vigorous root systems were selected, were allowed to interpollinate,
and seed was collected. A second cycle of screening was conducted in
February 1974 and seed was subsequently produced.

For the screening of the third cycle, a nutrient solution culture technique
was used. Approximately 3,000 seedlings were grown in nutrient solution
adjusted to pH 4.2-4.5 with 3 ppm Al. After 4 weeks, the tallest, most
vigorous seedlings were selected and intercrossed seed was produced.

Following the three cycles of screening, an evaluation of the progress of our
screening was conducted in 1976, using the nutrient solution culture tech-
nique. Entries included the original population, cycles 1, 2, and 3, and
Williamsburg as a check. Results indicated that when grown at pH 4.2-4.5
with 3 ppm Al, plant heights, top weights, root lengths, and root weights of
cycle 3 seedlings were 35-67% greater than those of the original population.
Although gradual progress was noted for cycles 1 and 2, particularly in root
length and weight, the greatest progress toward Al tolerance was made in
cycle 3. Seedling growth of Williamsburg was generally poorer than the
original population.

Screening of cycle 4, using the nutrient solution technique, has recently

been completed. In addition to laboratory evaluations, field plots will be
established with cycle 4 seed in Al-toxic soils in Virginia in 1977.

34

cv
12 sasuine N Fixation in Seven Alfalfa Cultivars,
X
Hee Elieane Irs rand \ Ji. 0... Lege
Agricultural Research Service, USDA
Field Crops Laboratory, PGGI, and Biological
Waste Management and Soil Nitrogen Laboratory, AEQI
Beltsville, Maryland

An isotope dilution method was used to detect differences in N fixation among
seven alfalfa cultivars and also among plants within cultivars. Plants were
grown in the field in soil-filled cement cylinders 61 cm (24 inches) in diam-
eter. Three cylinders (reps) were used for each cultivar. The soil in each
cylinder had been previously labeled by incorporating 15N into soil organic N.
The isotopic composition of the mineralized soil N was determined from the N
uptake by a non-fixing plant, tall fescue, grown in each cylinder. Any
decrease in the respective isotope ratio in the alfalfa plants was attributed
to fixation of atmospheric N.

In 1976, all of the alfalfa plants in a given cylinder were bulked and analyzed
together for the first three harvests, but were analyzed individually for the
fourth harvest.

N fixation rates averaged across cultivars were not significantly different
between harvests 1 and 3, with 61 and 65%, respectively, of the nitrogen
present in the plant tops attributed to fixation. However, harvest 2 was sig-
nificantly lower, with 55% fixation, possibly due to severe drought conditions
resulting from our failure to supply sufficient moisture during hot, dry
weather.

Significant differences in N fixation were found among cultivars. Vernal,
Ranger, Saranac AR, Arc, and Moapa 69 had 73, 70, 69, 66, and 65% fixation,
respectively. They were not different from each other but were significantly
higher than DuPuits and Lahontan, with 45 and 34% fixation. It is unclear why
the latter two cultivars were lower in fixation. Each cultivar performed
relatively well in one of the three cylinders; however, the other two cylinders
were very poor in growth and N fixation. No harvest x cultivar interaction was
observed. A highly significant correlation (r = 0.73, n = 63) was obtained
between forage yield and percent N fixation.

A highly significant correlation (r = 0.53, n = 199) between forage yield and
percent N fixation was also obtained for the plants of Arc, Saranac AR, Ranger,
Vernal, and Moapa 69 which were cut, weighed, and analyzed individually in
harvest 4, indicating that the larger plants are related to higher levels of

N fixation. Percent N fixation ranged from 43.7 to 93.4 for the 199 plants
analyzed. Our results suggest that, although alfalfa cultivars presently fix
two-thirds to three-fourths of their N from the atmosphere, significant varia-
tion in N fixation exists and progress toward breeding more efficient N-fixing
cultivars should be possible.

3D

AS
Initiation of a Work Program to Isolate Disease
Resistance in Alfalfa in the Republic of Argentina

1

S. A. Ostazeski
Agricultural Research Service, USDA
Field Crops Laboratory, PGGI
Beltsville, Maryland

With the exception of bacterial and possibly Verticillium wilt, the same
alfalfa diseases can be found in the Republic of Argentina as occur in the
U.S. Diseases, insects, and some physical factors are believed to be the
cause of a decline in hectarage, longevity and productivity of existing
alfalfa stands. At the present time, the Food and Agriculture Organization
and the Republic of Argentina are engaged in a joint project "Recovery of
Alfalfa Productivity" in an attempt to reverse the trend.

During the period 18 August-30 October 1976, staff scientists and I conducted
limited surveys to determine the extent of diseases in the country and to
select a disease amenable to control by improved management, or by breeding
for resistance. The crown and root rot problem is their most important
disease but its complexity ruled it out as a problem with a ready solution.

As a group, blackstem diseases and anthracnose appeared to be second ranked in
importance, followed by other foliar diseases, stem nematode, and all other
diseases.

a

Anthracnose was selected for immediate attention since screening for resis-
tance to this disease is quickly and efficiently accomplished in the seedling
stage. Resistance evaluations of 12 Argentine and 17 U.S. cultivars were
conducted at Anguil, Argentina, in a series of three inoculations. Percentage
survival for the entries ranged from 0 to 86% with the U.S. cultivars Arc (86%)
and Saranac AR (65%) having the greatest survival. In general, Argentine
alfalfas were quite susceptible, ranging from 0 to 18% survival. However, it
was concluded that a phenotypic recurrent selection program for anthracnose
resistance in Argentine alfalfas would be highly successful.

36

Contributions of Resistance to Anthracnose, Bacterial Wilt and
Phytophthora Root Rot to Persistence and Yield of Alfalfa
Ze under Irrigation

?

G. R.j Buss
Virginia Polytechnic Institute a State University, Blacksburg, Va.

Previous experience with alfalfa, primarily the Williamsburg variety,
has shown that persistence is very poor under irrigation. It was assumed
that the irrigation made more favorable conditions for development of
diseases and the consequent thinning of stands. However, it was difficult
to determine which diseases might be most detrimental.

In 1974 an experiment was planted at Orange, Virginia, with the
objective of determining the relative importance of three diseases--
anthracnose, bacterial wilt and Phytophthora root rot--in stand depletion
under irrigation. Twenty-one varieties with various degrees of resistance
to different combinations of the three diseases were planted in broadcast
plots. The experimental design was a split plot with irrigation vs. no
irrigation as the main plot treatments and varieties as sub-plots. Eighteen
and 40 inches of water were applied in 1975 and 1976, respectively. No
water was applied before first harvest in any year. The data collected
included yields (4 harvests/year) and plants per square foot (once each
season).

Irrigation effects were not significant in 1975 and 1976 but were in
1977, due to a carryover of soil moisture from irrigation in late 1976 and
probably a better overwintering condition of the plants. All other harvests
except the last one in 1975 showed significant yield increases from
irrigation. Significant plant stand differences due to irrigation were not
detected until 1977.

Variety differences were significant for all data except the 1975 first
harvest. The irrigation x variety interaction was not significant for any
yield data and was significant at the 10% level for plant stand data in
1976 only. This information would indicate that all varieties behaved
similarly under irrigation. However, closer observation of the data
revealed some trends from which tentative conclusions could be drawn.
Resistance to anthracnose appeared to have the largest effect on persistence
and yield with Phytophthora root rot having somewhat less effect. Bacterial
wilt did not appear to be present since wilt symptoms were not observed and
the performance of wilt susceptible varieties was similar to resistant
varieties.

oy

cy
aah collogt call Factors Influencing Infection and Development of

Colletotrichum trifolii in alfalfa

a

Ronald E. Welty
ARS, USDA, N. C. State University, Raleigh, N. C. 27607

Anthracnose limits alfalfa production in southeastern and mideastern USA.
Generally the Flemish alfalfas are susceptible, but procedures have been devel-
oped for screening populations and resistant cultivars are available. Recent
studies evaluated the effects of temperature and light on infection and dis-
ease development, the effects of temperature on resistance, and how culture
age affects spore viability. Three-week-old plants (cultivar 'Team' unless
stated otherwise) were inoculated with C. trifolii (106 spores/ml) and incu-
bated 1-3 days at 100% RH. After 3 weeks, plants were given disease scores
of 1-5; 1 and 2 resistant, 3, 4, and 5 susceptible. A disease severity index
(DSI) and a survival percentage (score 1 & 2) were determined. Experiments
included 4 to 9 replications and each experiment was repeated.

In the first study, inoculated plants were incubated at 16 or 24 C during
infection and moved to growth chambers at 14/10, 18/14, 22/18, 26/22, and
30/26 C day/night temperatures for disease development. The DSI was signifi-
cantly larger (P = 0.01) when infection occurred at 24 (4.3) than at 16 C
(3.9) and significantly increased (P = 0.01) when the infection period in-
creased from 1-3 days (3.5, 4.3, and 4.5, respectively). The DSI of plants
at 5 temperatures for disease development ranged from 4.0 to 4.2 and were not
Statistically different. Temperature influences anthracnose more during in-
fection than during disease development.

The effects of 3 combinations of light intensity during infection and dis-
ease development were studied in 2 combinations of temperatures. The DSI of
plants incubated at 26.4, 7 and 1.6 Klux during infection were 3.3, 3.4 and
3.4, respectively, and were not statistically different. The DSI of plants
incubated for infection at 26 C day/22 C night and 14 C day/10 C night were
4.1 and 2.4, respectively, and were different statistically (P = 0.001). The
DSI of plants incubated at 26 C day/22 C night and 14 C day/10 C night during
disease development were 3.4 and 3.2, respectively, and were not different.

Three resistant and 2 susceptible cultivars were inoculated and incubated
at 16 or 24 C for infection. The DSI for all cultivars but one was larger at
24 than at 16 C (DSI of Arc was 2.3 at both temperatures). The average DSI of
Team and Saranac were 4.4 and 4.7, respectively. DSI of 'Arc', ‘Saranac AR’,
and 'Victor' were 2.3, 2.6, & 2.4, respectively.

The virulence of C. trifolii isolates from North Carolina (NC) and
Pennsylvania (PA) was compared using 6 susceptible and 6 resistant alfalfa
cultivars. Survival of resistant cultivars averaged and ranged, 58% and
45-76%, and 60% and 46-81% for NC and PA isolates, respectively. The survival
of susceptible cultivars averaged and ranged 3% and 0-8% and 5% and 0-14% for
NC and PA isolates, respectively.

Germinability of C. trifolii spores from cultures 5 to 25 days old was
determined after incubation at 24 C for 48 hours. Also, survival was deter-
mined for Saranac and Saranac AR seedlings inoculated with spores from these
cultures. Spore germinability from cultures 5 to 11 days old averaged 33%
and ranged 27-42%; germinability of spores from 13- to 25-day-old cultures
averaged less than 1%. Seedling survival of both cultivars increased when
inoculated with spores from cultures of increasing age.

38

a om
Effect of Different Levels of Expression of the Multifoliolate Character and
Leaf-Stem Ratio on Forage Quality and Performance of Alfaifa Synthetics -

C. C. Lowe, R. P. Murphy, and J. E. Sumberg
Cornell University, Ithaca, N.Y.

Six experimental synthetics developed from parental clones previously screened
for leaf-stem ratio (leaf %), multifoliolate expression (ifL), and yield were
evaluated to determine the effect of leaf % on the forage quality and perform-
ance. Parent clones were grouped to give synthetics with the following char-
acteristics: 1) ML - high leaf %, 2) ML - low leaf %, 3) ML - high leaflet
number, 4) ML - low leaflet number, 5) trifoliolate - high leaf 7%, and

6) trifoliolate - low leaf %. Cage-produced seed was used to establish
broadcast seeded plots in 1972, and these were harvested on a 3-cutting
schedule in 1973, 1974 and 1975. Leaf %, crude protein content (CP), and in
vitro true digestibility (IVID) were determined for each harvest in 1974 and
UOT

Significant differences in leaf % were observed among entries in each harvest
in 1974 and 1975. Significant differences in IVID and CP were measured among
entries for 2 of 3 harvests in both 1974 and 1975. Variation among entries
was strikingly less for IVID and CP than for leaf %. Check varieties,
Saranac and Iroquois, tended near the mean of the range of entry values.

IVID was correlated with leaf % for 4 of 6 harvests. Regression coefficients
ranged from .10 to .43 and approximated .30. These suggest that about a
3-unit change in leaf % is needed to effect a l-unit change in IVID. CP was
also correlated with leaf % for all harvests in 1974, but not in 1975.
Regression coefficients ranged from .04 to .29. Average values indicate about
a 5-unit change in leaf % is needed to effect a l-unit change in CP.

Synthetics with high leaf % or strong expression of the multifoliolate char-
acter were distinctly lower yielding than Saranac and Iroquois. Strong selec-
tion has probably narrowed the germplasm base of these synthetics.

It is apparent that average leaf % can be altered, but rather dramatic changes
in leaf % are necessary to effect economically important gains in IVTID or CP.
The use of leaf % as a primary selection criterion for nutritional quality

does not exploit genetic variation in the composition of the stems which are
the major forage component. Breeding for improved nutritional value in alfalfa
should probably be based on screening techniques such as IVID, cell wall or
crude protein determinations which reflect nutritional value of the whole
plant. Expected gains in nutritional value are small; therefore yield
potential must be maintained through the use of large diverse parent
populations.

39

of
The Present Status of Verticillium Wilt in the United States —

—

J. H. Graham, R. N. Peaden, D.W,.. Evans, and J, Hy Elgin, Jr:
Formerly PPHL, ARS, USDA, Beltsville, Md. (now Waterman-Loomis
Co., Columbia, Md.); ARS, USDA, Prosser, Wash.; Washington
State University, ‘Prosser, Wash.; and Field Crops Laboratory,
PGGI, ARS, USDA, Beltsvillé, Md., respectively.

Verticillium wilt of alfalfa, caused by the nonsclerotial fungus Verticillium
albo-atrum, has been found in the United States. The prevalence and impor-
tance of the disease in this country have not yet been determined. However,
the fungus was isolated from chlorotic and wilting plants in central and
western Washington and north central Oregon during 1976 and early 1977. The
disease has been known in Europe since 1918. Frequently, stands are non-
productive by the end of 2 or 3 years.

Typical symptoms of Verticillium wilt include yellowing of leaves which later
become whitish and desiccated. In the advanced stage of the disease, plants
are noticeably stunted. Internally, the xylem tissues become orange-brown.
The fungus is difficult to isolate from roots but is easily recovered from
infected stems, petioles, and leaves. In the field, Verticillium wilt is
difficult to distinguish from Fusarium wilt.

In inoculation tests at Beltsville, Md., and Prosser, Wash., resistant
European cultivars were found to be resistant; U.S. cultivars were susceptible.
A composite of approximately 30 U.S. cultivars selected for resistance to
Verticillium wilt in Italy (PL 480 Project) had a low level of resistance.
There was a negative correlation between plant vigor and internal root
discoloration.

40

vit cs
Une tect of Root Lesion Nematodes on Yield of Forage Legumes and Grasses
Seeded Alone and in Mixture

C. B. Willis, Research Station, Agriculture Canada, Chaerlcttetown,
Prince Edward Islanc, Carada C1A 7M8

The effects of the root lesion nematode, [Pratylerchus Penetrans] on yield
of forage legumes and grasses seeded alone and in mixture were™studied in
the greenhouse and field. Nematodes were controlled in the greenhouse by
methyl bromide fumigation or by phenamiphos treatment prior to seeding and
in the field by a pre-plant application of phenamiphos. Forage yields of
alfalfa, red clover, and birdsfoot trefcil seeded alone were reduced
significantly by nematode infestation, while yields of timothy and brome-
grass seeded alone were unaffected or reduced slightly only. Yield cf
legume-grass mixtures was reduced significantly and generally of the same
order es the legume species in the mixture. The yield of legumes in
legume-grass mixtures, however, was reduced more by nematode infestation
than when the same legume was seeded alone. At the same time, the yield of
grasses was substantially greater in legume-grass mixtures growing in
nematode-infested soil. The differential effects of the nematode on
legumes and grasses resulted in a significantly higher proportion of
grasses as comporents of mixtures when large numbers of nematodes were
present.

41

ie BUSINESS MEETING

Second Eastern Forage Improvement Conference

J. O. Keller Conference Center
The Pennsylvania State University
University Park, Pennsylvania

Judy: 155 2977
The meeting was called to order at 1:20 p.m. by Chairman Heinz Gasser.
Minutes of the first Eastern Forage Improvement Conference held July 16-18,
1975, at the University of Guelph, Guelph, Ontario, Canada, were not read but

were approved as printed in the proceedings of that conference.

The following committees were appointed by Chairman Gasser:

Nomination Committee Resolutions Committee
John Baylor, Chairman Glenn Buss, Chairman
Dick Hill Norman Lawson

Harry Bryant Jim Elgin

There was no old business so the meeting was opened for new business.

There was considerable discussion regarding the possible affiliation of the
EFIC with the Northeast ASA. Some members felt the EFIC was not sufficiently
large and all-encompassing to justify the travel, meeting arrangements, etc.,
and suggested that an affiliation with another group, like NE-ASA, would
increase attendance and participation while reducing the administrative

chores. Others felt that an affiliation with another group was not desirable
at this time; however, they would consider the possibility of an occasional
summer meeting with a regional technical committee every second or third
meeting. Dick Hill moved, seconded by Ken Leath, that the conference not
affiliate with any other group and leave EFIC as it now exists. Motion passed.

Dick Hill discussed proposed changes in the contents of the Eastern Alfalfa
Nurseries Report and the way it is compiled and distributed. He proposed that
the report be expanded from alfalfa alone to include all cool-season forages
in keeping with the recent change in the name of our conference. Also
proposed was that he compile and distribute the report only for the Eastern
United States and that the forage crops committee for each Canadian Province
send out the report for their own Province. Thirdly, he proposed that he
maintain the mailing list for the entire Eastern Forage Improvement Conference
and run off all labels for distribution of the U.S. and Canadian reports. The
mailing labels would be sent to appropriate persons responsible for distribut-
ing the reports. These proposed changes will expand the content of the
nurseries reports and greatly facilitate their distribution. The conference
unanimously approved these changes. The conference secretary will request
from the Canadian representatives the mailing lists used for distribution of
their reports. These mailing lists will be provided to Dick Hill.

42

A note was read from Don Barnes, secretary of the National Alfalfa Improvement
Conference, indicating that the 26th NAIC will be held at South Dakota State
University, Brookings, S. Dak., June 6-8, 1978. The executive committee will
meet at the Agronomy Meetings in Los Angeles on November 15 to develop program
plans. A letter will be sent to members in late November announcing program
plans and asking for volunteer papers. Any program planning suggestions
should be communicated to Morris Decker, Jim Elgin, Mel Rumbaugh, or Don
Barnes prior to November 10.

Regarding future EFIC meetings, a suggestion was made from the floor that

speakers be asked to bring summaries of their papers for distribution to the
audience instead of having to wait for publication of the proceedings.

Committee Reports

Nominating Committee - The nominating committee proposed the following slate
of officers:

Chairman - Morris Decker, University of Maryland, College Park, Md.
Vice Chairman - Jim Elgin, USDA, Beltsville, Md.
Secretary - Jack Winch, University of Guelph, Guelph, Ont., Canada

Nominations were closed and a unanimous ballot was cast for the nominees.

Resolutions Committee - The resolutions committee submitted the following
resolution:

Whereas Dr. R. R. Hill, Jr., and others from the U.S. Regional Pasture
Research Laboratory in cooperation with members of The Penn State
University Agronomy Department served as hosts for the second Eastern
Forage Improvement Conference, including doing an outstanding job of
making local arrangements for the~-conference, the field tour, and
picnic, be it resolved that we, the participants of the conference,
extend our sincere thanks to these individuals for their efforts in
making our stay at Penn State enjoyable and productive.

The resolutions committee report was unanimously approved.

Meeting Location - No invitation for the third EFIC had been received; however,
meeting somewhere in Canada was suggested. Also mentioned was the University
of Maryland in conjunction with the Beltsville Agricultural Research Center.
The executive committee will make the final decision on the meeting location.

The business meeting was adjourned at 2:03 p.m.

James H. Elgin, Jr.
Secretary, Second Eastern Forage
Improvement Conference

CONFERENCE REGISTRANTS

STEVE J. BALUCH, FFR Coop., 4112 E. State Road 225, W. Lafayette, IN 47906

DONALD K. BARNES, USDA-ARS, Dept. of Agronomy, Univ. of Minnesota, St. Paul,
MN 55108

ROBERT F. BARNES, USDA-ARS, NPS, Rm. 411/005, BARC-West, Beltsville, MD 20705

JOHN E. BAYLOR, Penn State Univ., 106 Ag. Admin. Bldg., University Park, PA
16802

LUCIUS BELZILE, Quebec, Canada

CLYDE C. BERG, Penn State Univ., University Park, PA 16802

H. IT. BRYANT, Virginia Forage Res. Sta., Rt..2, Box 9, Middleburg, VA 22117

GLENN R. BUSS, Agronomy Dept., VFI & State Univ., Blacksburg, VA 24061

RICHARD CLEVELAND, Penn State Univ., 312A Tyson Bldg., University Park, PA
16802

DON COTTON, United Cooperatives of Ontario, F.O. Box 527, 151 City Centre Dr.,
Mississauga, Ont., Canada

BRUCE E. COULMAN, Plant Science Dept., MacDonald Campus of McGill Univ.,
Ste-Anne-de-Bellevue, Quebec, Canada

A. M. DECKER, Agronomy Dept., Univ. of Maryland, College Park, MD 20742
EARLE DeMERCHANT, New Brunswick Dept. of Agric., P.O. Box 5001, Sussex, N.B.

JAMES H. ELGIN, JR., USDA-ARS, Field Crops Lab., Rm. 335/001, BARC-West,
Beltsville, MD 20705

GUY W. FISSEL, U.S. Regional Pasture Res. Lab., University Park, PA 16802
DANIEL D. FRITTON, Penn State Univ., 318 Tyson Bldg., University Park, PA
16802

HEINZ GASSER, Complexe Scientifique, 2700 rue Einstein D-1-14, Ste-Foy,
Quebec C.P. GIP 3W8 Canada

JOSEPH GRAHAM, Waterman-Loomis Co., 2000 Century Plaza, Suite 110, Columbia,
MD 21044

CHARLES F. GROSS, U.S. Regional Pasture Res. Lab., University Park, PA 16802

ROY C. HAMMES, Virginia Forage Res. Sta., Rt. 2, Box 9, Middleburg, VA 22117

C. H. HANSON, 766 Barlowe Drive, Gettysburg, PA 17325

NAYNE HARTMAN, Waterman-Loomis Co., 2000 Century Plaza, Suite 110, Columbia,
MD 21044

BOB HEISEY, Dept. of Plant Breeding, Cornell Univ., Ithaca, NY 14853

R. R. HILL, JR., U.S. Regional Pasture Res. Lab., University Park, PA 16802

FLOYD P. HORN, USDA-ARS, SW Livestock & Forage Res. Sta., Rt. 3, El Reno, OK
73036

GERALD JUNG, U.S. Regional Pasture Res. Lab., University Park, PA 16802
NORMAN JUSTUS, Univ. of Missouri SW Center, RR 3, Box 87, Mt. Vernon, MO 65712

W. A. KENDALL, U.S. Regional Pasture Res. Lab., University Park, PA 16802

JOHN KUGLER, Waterman-Loomis Co., 2000 Century Plaza, Suite 110, Columbia, MD
21044

44

N. C. LAWSON, MacDonald College of McGill Univ., Ste-Anne-de-Bellevue, Quebec,
Canada

K. T. LEATH, U.S. Regional Pasture Res. Lab., University Park, PA 16802

G2) Gs LOWE;. Dept... of Plant Breeding, Cornell Univ., Ithaca, NY 14853

WES MASON, Quebec, Canada

MARK McCASLIN, Dept. of Plant Breeding, Cornell Univ., Ithaca, NY 14853
JAMES E. McMURTREY, USDA-ARS, Field Crops Lab., BARC-W, Beltsville, MD 20705
REAL MICHAUD, Canada Agriculture, Ste-Foy, Quebec, Canada

R. P. MURPHY, Dept. of Plant Breeding, Cornell Univ., Ithaca, NY 14853

HANS NEW, South African Embassy, Suite 300, 2555 M Street, N.W., Wash., DC

S. A. OSTAZESKI, USDA-ARS, Field Crops Lab., Rm. 331/001, BARC-West,
Beltsville, MD 20705

H. M. SCHAAF, Dept. of Plant Breeding, Cornell Univ., Ithaca, NY 14853

JOHN SHENK, Dept. of Agronomy, Penn State Univ., University Park, PA 16802
BiLL STRINGER, Dept. of Agronomy, Penn State Univ., University Fark, PA 16802
JIM SUMBERG, Dept. of Plant Breeding, Cornell Univ., Ithaca, NY 14853

WILLIAM TEMPLETON, JR., U.S. Regional Pasture Res. Lab., University Park, PA
16802
M. B. TESAR, Crop & Soil Sciences, Michigan State Univ., E. Lansing, MI 48823

DAVID WALKER, New Brunswick Dept. of Agric., P.O. Box 6000, Fredericton, N.B.,
Canada

RONALD E. WELTY, USDA-ARS, Plant Pathology Dept., N.C. State Univ., Raleizh,
NC 27607

J. E. WINCH, Dept. of Crop Science, Univ. of Guelph, Guelph, Ont., Canada

DALE WOLF, Agronomy Dept., VPI & State Univ., Blacksburg, VA 24061

SHENG-TIAN YEN, Dept. of Plant Breeding, Cornell Univ., Ithaca, NY 14853
BRUCE YOUNG, Penn State Univ., University Park, PA 16802

45