GENOTYPIC AND ENVIRONMENTAL EFFECTS ON
FATTY ACID COMPOSITION, IODINE VALUE AND OIL
CONTENT OF PEANUT (Arachis hypogaea L.)

BY

MARILENE L. A. BOVI

A DISSERTATION PRESENTED TO THE GRADUATE COUNCIL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA
1982

1

ACKNOWLEDGEMENTS

The author expresses her sincere gratitude to her major
advisor. Dr. A.J. Norden, for his constructive guidance in
the research and preparation of this manuscript. Sincere
appreciation is likewise extended to Dr. E.S. Horner,
Dr. D.W. Gorbet, and Dr. P.M. Lyrene , members of her super-
visory committee, for their helpful suggestions in this
dissertation.

Special thanks are extended to Dr. F.G. Martin, member
of the supervisory committee, for his invaluable help in
the analysis of the data, as well as for his suggestions
to improve the manuscript.

The author also expresses appreciation to the Brazilian
Agency for Agricultural Research (EI4BRAPA) for the financial
support given during the graduate program.

Sincere thanks are expressed to the members of the
author's family for their patience, understanding and
encouragement .

TABLE OF CONTENTS

Page

ACKNOWLEDGEMENTS ii

LIST OF TABLES iii

ABSTRACT vi

INTRODUCTION 1

LITERATURE REVIEW 5

MATERIALS AND METHODS 31

RESULTS AND DISCUSSION 47

SUMMARY AND CONCLUSIONS 107

BIBLIOGRAPHY Ill

BIOGRAPHICAL SKETCH 119

iii

1

LIST OF TABLES

Table Page

1 Genotypes Involved in the Oil Composition
Analysis 32

2 Planting and Harvest Dates During the

Ten-Year Period (1966-1974 and 1978) 38

3 Climatic Parameters from Pegging Initiation
to Harvest in a Ten-Year Period (1966-1974

and 1978) 42

4 Fatty Acids, Iodine Value and Oil Content of
100 Peanut Genotypes. Mean Over Ten Years
(1966-1974 and 1978) 48

5 Mean Squares from the Analysis of Variance,
Coefficients of Variation (C.V.) and Means of
Fatty Acids, Iodine Value and Oil Percentage

of 40 Peanut Genotypes 53

6 Least Square Means, Standard Errors and Geno-
type Grouping of Oil Components of 40 Peanut
Genotypes 56

7 Mean Squares from the Analysis of Variance
and Coefficients of Variation (C.V.) of Fatty
Acids, Iodine Value and Oil Percentage for the
Different Maturity Groups 67

8 Mean Squares from the Analysis of Variance
and Coefficients of Variation (C.V.) of Fatty
Acids, Iodine Value and Oil Percentage for the
Different Commercial Types 70

9 Mean Oil Composition of Peanut Genotypes for
the Different Maturity Groups and Commercial
Types 75

10 Least Square Means (LSM) , Standard Errors
(Std Error) , and Genotype Grouping for the
Different Maturity Types 79

iv

Table Page

11 Least Square Means (LSM) , Standard Errors
(Std Error) , and Genotype Grouping for the
Different Commercial Types 65

12 Correlation Coefficients Among Climatic
Parameters and Oil Components of 40 Peanut
Genotypes 94

13 Correlation Coefficients Among Climatic
Parameters and Oil Components of Different
Maturity Groups 95

14 Correlation Coefficients Among Climatic
Parameters and Oil Components of Different
Commercial Types 98

15 Correlation Coefficients Among Oil Components

of 40 Peanut Genotypes 105

/

V

Abstract of Dissertation Presented to the Graduate Council
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

GENOTYPIC AND ENVIRONMENTAL EFFECTS ON
FATTY ACID COMPOSITION, IODINE VALUE AND OIL
CONTENT OF PEANUT (Arachis hypogaea L.)

By

MARILENE L. A. BOVI
December 1982

Chairman: A.J. Norden
Major Department: Agronomy

A hundred genotypes from the Peanut Breeding Project of
the University of Florida were chemically analyzed for oil
content, fatty acid composition and iodine value, during a
ten-year period, in an attempt to determine, quantify and
utilize chemical data as criteria for genetic selection of
superior peanut material in plant breeding work.

The results showed that peanut oil is comprised
primarily of oleic, linoleic and palmitic acids, with the
first two accounting for about 80% of the total.

A large variation in fatty acid composition and iodine
value (IV 75 to IV 105) was found among the genotypes. The
magnitude of this variation should permit the development of
new varieties with improved oil quality. Oil percentage
varied from 46.2 to 53.4%.

vi

A subdivision of the genotypes into maturity and market
types indicated that there are relatively high levels of
genetic variability for oil components within each group.
It should be possible to select varieties that best suit
industrial and/or nutritional purposes in each group.

The findings indicate that classification of peanut
genotypes into specific maturity groups or market types
based on characteristics of the oil would be hazardous.

Year effects were highly significant for the combined
genotypes, market types and maturity groups. Eicosenoic, a
minor fatty acid, seems to be particularly affected by
climatic variations.

Correlation coefficients calculated among climatic
parameters and oil components showed negative correlations
for iodine value (r=-0.35**) and oil percentage (r=-0.42**),
especially with soil temperatures. The significant iodine
value association with temperature found in this study might
help explain the higher levels of the polyunsaturated fatty
acids, such as linoleic, reported in oils from crops grown
in cooler locations. Based on this association it should
be possible to alter the chemical composition of peanut
genotypes by varying the planting date within a given loca-
tion to coincide with cooler or warmer temperatures during
the seed filling period.

Oleic acid was shown to be negatively correlated with
linoleic acid (r=-0.30**), suggesting that selection of
genotypes with improved industrial or nutritional qualities
should be possible.

vii

INTRODUCTION

Worldwide, peanuts (Arachis hypogaea L.) are mainly an
oilseed crop grown primarily for crushing into oil and meal.
About two-thirds of the world's peanut crop is used for oil.
Peanut supplies about a fifth of the world's edible oil
production and comprises a third of the world's trade in
edible oils and oil-bearing materials (Woodroof , 1973) .

Since 1960 there has been a sharp increase in peanut
production with the leading countries being India, Mainland
China, Nigeria, the United States and Senegal. Crops in
Sudan, Argentina, Burma and Brazil have increased steadily,
which was reflected largely in oil production. About 70% of
the oil seed crops of India consist of peanuts. China is
another country where peanuts are produced mainly for oil.

Brazil has been showing a strong increase in peanut
production since 1977. In that year Brazil produced
323,600 tons of raw peanuts. Subsequently, the figures
were 342,100 tons in 1978, 461,000 in 1979, 480,900 in 1980,
and 331,100 to August of 1981 (Informacoes Agricolas, 1981).
Among the factors responsible for this large increase in
production are increased area of planting, better varieties,
development of farming machinery and equipment specifically
for peanut planting, cultivating and harvesting, two crops

1

2

per year, and the establishment of minimum prices for
foreign markets.

About 80% of the peanut production in Brazil is
exported to Spain, Italy, France, the United Kingdom,
Hungary, Singapore, the Netherlands, West Germany, Portugal
and Japan. Peanuts are exported shelled and unshelled and a
large percentage as peanut oil. France is the largest
purchaser of Brazilian peanut oil. Of the 20% of the peanut
crop remaining in Brazil, 80% goes into oil, with the
remaining 20% used in confectioners products, peanut butter,
roasted peanuts and as seed.

The United States is one of the few countries in the
world where peanuts are used mainly for domestic food
consumption. A 1979 report (USDA Agricultural Statistics)
shows that over 70% of the peanut crop in the United States
goes for human consumption. The rest is used for seed,
animal feed and oil.

Due to competition from other vegetable oils and
increased demand for edible nuts, relatively smaller
quantities of peanuts are crushed for oil, generally the
lower quality kernels. Since 1950, the quantity of peanuts
crushed for oil in the United States has decreased to about
half. This is due to a higher price for edible peanuts,
decreases in demand for vegetable oils, upgrading the
quality of peanuts, and better handling and storing
practices for peanuts (Woodroof , 1973) .

3

With over 70% of the crop directed to human consump-
tion, it is no surprise that there are several ways of
consuming peanuts in the United States. Peanuts can be
consiamed as a vegetable, canned, frozen, toasted, etc; but
it is the roasted peanut that is most acceptable due to its
pleasant and unique flavor. There is a large variety of
roasted peanut products, especially peanut butter, that
accounts for over 60% of the total edible peanut production
in this country (Woodroof , 1973) .

Many factors contribute to the final quality of peanuts
and its products, including storage, processing and curing.
But the principal factor is the chemical composition of the
seeds of different varieties. Lipids, amino acids, and
carbohydrates play primary roles in the overall quality of
peanut cultivars.

The major implications of lipids in the final quality
of peanuts and derived products are in relation to
industrial quality and human health, especially as related
to essential fatty acids and physiological effects of
certain fatty acids in the development of human diseases.

Since fatty acid composition is important, both from
the standpoint of product quality, and possible
physiological aspects of some of the fatty acids, this
factor should be considered in the development of new
varieties of peanuts. Although there are reports on the
fatty acid composition of peanuts grown in other areas of
the United States, especially Georgia and North Carolina,

4

there is no complete report on breeding lines, introductions
and commercial varieties grown in Florida.

The present study was undertaken to screen peanut
genotypes from the breeding program of the University of
Florida in an attempt to determine, quantify and utilize
chemical data as criteria for genetic selection of superior
peanut material in plant breeding work. As there are
reports of large yearly variation in the chemical
composition of peanut oil (Holley and Hammons, 1968;
Worthington et al. , 1972), breeding lines, introductions and
commercial varieties were examined from one to ten growing
seasons to determine possible relationships involving yearly
variation and fatty acid composition of peanut genotypes.

LITERATURE REVIEW

Peanut oil is composed of mixed glycerides of
approximately 80% unsaturated and 20% saturated fatty acids
(Cobb and Johnson, 1973) . The oil obtained from peanuts is
more saturated than the oils obtained from corn, cottonseed,
or linseed, but considerably less saturated than coconut,
palm or butter oils (Robinson, 1980) .

The main problem of lipids in the industrial quality of
peanuts and its products is related to oil stability.
Although peanut oil is relatively stable in comparison with
many other vegetable oils, it is susceptible to the
development of oxidative or hydrolitic rancidity. Oxidative
rancidity is the more serious problem in most lipids. The
rancidity appears when the unsaturated fatty acids are
oxidized and undergo a series of reactions at the double
bonds. The initial step in oxidation is the addition of
oxygen to form peroxides at or near the points of
unsaturation (double bonds) . Since peroxides are highly
reactive compounds, they readily decompose into various
acids, alcohols, aldehydes, ketones, and other hydrocarbons,
which are the substances responsible for the off-flavors and
rancid odors (St. Angelo and Ory, 1973) . The higher the

5

6

degree of total unsaturation in the oil, the lower is the
oil stability.

Several parameters, including peroxide and iodine
numbers, free fatty acid content, oven keeping time (oven
stability) of expressed oils, and the oleate/linoleate (0/L)
ratio of the oils, have been used to predict the stability
of peanut oils (Holley and Hammons, 196 8; Worthington et
al. , 1972) . The iodine number method was first proposed by
Huebl in 1884, and in 1898 Wijs introduced a faster method
to determine this parameter (Hilditch, 1956) . Since then
this method has been used extensively for measuring
unsaturation of fats.

The iodine number, or value, reflects the melting point
of a fat, as well as the resistance of oil to oxidation and
consequent oil stability. The higher the iodine number, the
greater is the unsaturation of a fat and, generally
speaking, the susceptibility to oxidation. The iodine
number is defined as the number of grams of iodine absorbed
by 100 grams of the substance (Kirschenbauer , 1960) . Of the
many methods developed for the estimation of unsaturation,
the Wijs method has found the widest use. This method
employs an excess of iodine monochloride . The unreacted
portion of the iodine solution is titrated back with sodium
thiosulfate solution, and the absorption is computed taking
a blank test into consideration.

Worthington et al. (19 72) studied four independent
variables as indicators of oil stability. They concluded

7

that, although the iodine number does not take into account
the much greater susceptibility of polyenes to autoxidation ,
it still is a good indicator of oil stability. A high
statistical correlation was noted between iodine value and
such parameters as oil content, refractive index, keeping
time, oil stability, shelf-life and oleic/linoleic ratio
(Holley and Hammons, 1968) . VVith the advent of the gas
chromatograph, iodine number, in research studies, has been
calculated directly, assuming purity and complete
esterif ication of the oil. Although in practice (quality
control in industry) the iodine value is determined from the
refractive index of the expressed oil (French, 1962) or Wijs
method (A.O.A.C., 1970), a good agreement between the iodine
values calculated from the gas-liquid chromatograph and
those obtained by the Wijs method has been found
(Worthington et al. , 1972).

' Oil composition is also important from the standpoint
of nutritional properties and physiological effects of fatty
acids and certain other oil components. For example,
ingestion of linoleic, linolenic and arachidonic acids has
been found essential for health, as the animal and human
bodies apparently are unable to synthesize these fatty
acids. The value of polyunsaturated fatty esters has long
been recognized to be like that of vitamins (Burr and Burr,
1929; Holman, 1968). Recently a new dimension has been
added since it was established that linoleic acid and its
esters were precursors for a group of chemically similar

8

hormones called prostaglandins. These compounds help regu-
late vital functions of the body. Other reports indicate
that polyunsaturated fatty esters, such as linolenate, have
an important function in the protection of the central
nervous system and might be helpful in multiple sclerosis
(Bernsohn and Stephanides, 1967).

• Considerable attention has also been directed in recent
years to the effect of saturated fatty acids on heart
disease and related disorders of the circulatory system.
Arachidic (C20:0) and behenic (C22:0) acids have been
implicated circumstantially with abnormal cardiovascular
conditions in laboratory animals (Kristchevsky et al. ,
1970) .

Accumulation of cholesterol in the lining of the
arteries has been shown to be the cause of atherosclerosis,
also known as hardening of the arteries. Indications are
that in the absence of the essential fatty acids, the higher
melting, less unsaturated fatty acids are absorbed in the
cholesterol complexes, a fact which may be important
regarding cholesterol deposits. Repeated short-term
experiments showed that a reduction of saturated fatty
acids, such as palmitic and stearic, and an increase in
polyunsaturated acids, such as linolenic, in the diet, lower
the cholesterol content of the blood (National Diet Heart
Study, 1967; Grande et al. , 1970).

Atherosclerotic plaques from heart attach sufferers
contain cholesterol and cholesterol fatty esters. The exact

9

» relation between diet and the circulatory problems has not
yet been established, but reports show that linoleic, in
addition to being an essential fatty acid, is also
hypocholesterimic (Grande et al. , 1970). Vergroesen (1977)
pointed out that there is accumulating evidence that
linoleic acid diets can provide effects such as decreased
thrombotic tendency of platelets, preventive and curative
effects in sodium-induced hypertension, improvement of
physiological function of the heart, and normalization of
the biochemical abnormalities in obesity and maturity onset
diabetes .

The component acids of a number of peanut oils from
different regions have been reported since 1921 (Jamieson et
al. , 1921) . Varied and sometimes conflicting results can be
found in most of the papers and extreme differences were
reported involving varieties, locations, storage,
laboratories, seed maturity, etc. Cobb and Johnson (1973)
pointed out that at least six major factors could affect the
results in the compositional make up of peanuts. Variety,
individual seeds within an aliquot, yearly climatic
variations, the portion of the seed tissue analyzed, seed
abnormalities, and lack of accuracy and precision in testing
methods were recognized by these authors as the major
factors responsible for composition variation of peanut oil.

As early as 1921 Jamieson and coworkers reported
variations in gross composition among Spanish and Virginia
market type peanuts. The authors reported that oil in

10

Spanish peanuts contained slightly less oleic and more
linoleic glycerides than Virginia oil. They found a
linoleic content of 25% for the Spanish type and 22% in the
Virginia market type.

Higgins et al. (1941) reported a wide variation in the
linoleic and oleic content of some selected strains of
Spanish and Runner type peanuts. Examination of their data
shows that, as a group. Runner type peanuts are lower in
percentage of linoleic acid than the Spanish type peanuts.

Crawford and Hilditch in 1950 summarized the
information reported on composition of peanut oils by
various workers between 1920-1950. They called attention to
the extreme differences from about 65% to 40% in oleic acid
content and from about 18% to nearly 40% in linoleic acid
content of peanut oils, and concluded that those differences
might be expected to influence the relative susceptibility
of a peanut oil to oxidative rancidity. In their study of
the component glycerides of African peanut oil, the authors
confirmed on the whole the results obtained by previous
workers. They again emphasized the rather wide range of
oleic and linoleic acid contents which may be encountered in
peanut oils from different sources, but were unable to
relate these differences to genetic or environmental
factors .

Pickett and Holley (1951) , upon examining raw and
processed peanut oils for several years, reported that
somewhat higher peroxide values were found in the Spanish

than in the Runner or Virginia types. The greater
susceptibility of the oil from Spanish type peanuts toward
peroxide formation was evident whether the expressed oils
were directly aerated and heated or the peanuts were aerated
and heated prior to expression. The authors explained the
greater susceptibility to rancidity oxidation by Spanish oil
in comparison with Runner and Virginia type peanut oil based
on physical differences of the seeds. They commented that
the Spanish nut seems to have a much softer texture, and the
oil appears to flow more readily upon pressing than in
either the Runner or Virginia types. This apparent physical
difference may allow oxygen to contact the oil in the
Spanish more readily and thereby influence rancidity
development.

Fore et al. (1953) investigated the oils of
16 varieties of raw shelled peanuts, including both the
Bunch and Runner types, in relation to oil composition and
stability. They found that there appears to be a correla-
tion between the linoleic acid contents and stabilities of
the oils studied. Oils from Runner peanuts contained less
linoleic acid and had higher stabilities than oils of either
Spanish or Virginia peanuts. In general, oils of Virginia
peanuts contained less linoleic acid and were more stable
than oils of Spanish peanuts. In addition, the authors
reported a discernible trend toward increasing stability
with decreasing linoleic acid content among the individual
oils. Fisher and coworkers (1947) had previously observed

12

a similar phenomenon with regard to the relationship between
linoleic acid contents and stabilities of various refined
vegetable oils. The stability values obtained by Fore et
al. (1953) were approximately twice those reported by Fisher
and coworkers (1947) for a freshly refined, bleached,
deodorized oil of similar linoleic acid and tocopherol
content. As a result of these and other observations, Fore
et al. suggested that the rate of autoxidation of crude
peanut oil is influenced by antioxidants and/or synergists
other than tocopherols, and that these components are
removed in refining. Years later, French (1962) and
Worthington and Holley (1967) also reported considerable
variation among peanut genotypes for both major and minor
fatty acids.

Holley and Hammons (1968) in a study of 66 different
varieties or strains, grown during one season and analyzed
for linoleic acid content, reported a correlation
coefficient of -0.92 between linoleic acid content and oil
stability. The authors demonstrated definite genotype
differences in such characteristics as protein, oil content,
and oil stability.

Worthington and coworkers (1972) investigated 82 peanut
genotypes in order to determine the variability in fatty
acid composition as well as oil stability among genotypes of
diverse genetic origin. They found large differences in
fatty acid composition among the genotypes studied.
Genotypic differences in length of oil autoxidation

13

induction period were also large and ranged from 11.6 to
18.5 days. In general, the authors found that Virginia
types, particularly the late maturing, large-seeded
varieties, were higher in oleic and lower in linoleic acid
than the earlier maturing Spanish types.

Worthington and Hammons (1977) presented fatty acid and
oil stability data obtained over several years from
genotypes of Arachis hypogaea, together with fatty acid data
from other species of the genus Arachis . They reported that
some genotypes showed consistent differences in oil
stability patterns that were not related to oil linoleic
acid content. Analysis of entries from 16 wild Arachis
species collections revealed levels of oil linoleic acid
higher than those found in Arachis hypogaea .

Pancholy et al. (1978) examined 27 peanut cultivars and
found an oil content of 46 to 52 percent. Subsequent study
of 77 peanut lines (Pancholy et al. , 1980) showed an oil
content varying from 42.0% to 55.2%.

An extensive study done by Cherry (1977) on a group of
37 peanut collections comprising various wild types,
together with a sampling of 21 known cultivars in relation
to protein and oil composition, revealed that percentages of
oil in seed meals of wild species ranged between 46.5 and
63.1%, while those of cultivars were 43.6 to 55.5%.

Although most earlier and some recent papers reported
differences in oleic and linoleic acid content of Spanish,
Virginia and Runner types, due to the large number of

14

genetic crosses made in recent years, the classification of
types via chemical properties is a hazardous proposition.
Crosses between market types do not necessarily conform in
chemical composition to the parental types (Norden and
Block, 1968) . Cherry (1977) pointed out that it is
difficult to determine specific taxonomic relationships of
species collections and cultivars, within and among samples
from sections of Arachis , based only on percentage of meal
protein and oil. Quantities of protein and oil were
randomly distributed among wild species and cultivars and
could not be used to develop a chemotaxonomic relationship
in Arachis .

The individual seed within an aliquot is another
important factor responsible for variations in the
analytical results. The peanut plant is highly
indeterminate in growth, and under favorable environmental
conditions continues to produce fruits over an extended
period of time. Consequently, seeds found on a plant at
harvest time will span a broad range of developmental
stages. As a result, maturity of the individual seed and
its specific environment in the soil, as well as
post-harvest treatments, could affect markedly the fatty
acid analysis. Carotenoids, sugars, amino acids contents,
and roasted flavor development have been reported to be
especially affected by those factors (Pattee and Purcell,
1967; Newell et al. , 1967; and Mason et al., 1969).

15

Worthington (1968) studied developmental changes in the
fatty acid of various tissues of the Virginia Bunch 67
variety until maturation. He reported that cotyledon and
germ composition roughly paralleled one another during
maturation, as did testa and shells. During maturation of
the cotyledons, palmitic, linoleic, linolenic, eicosenoic,
behenic, and lignoceric acids declined in concentration
while oleic acid increased. The other acids present did not
change appreciably.

Hartzook (1969) observed a reciprocal relationship
between oleic and linoleic acid content in mature and
immature seeds. The linoleic acid level dropped from 43.9%
in the immature to 38.2% in the mature seeds, while the
oleic increased from 45.6% to 48.8%. During maturation,
stearic, oleic, arachidic, eicosenoic, behenic, and
lignoceric acids increased in concentration, while palmitic,
linoleic and linolenic decreased.

Young et al. (1972b) also reported that amounts of
stearic and oleic acids are greater in mature than immature
seeds, and the amounts of linoleic and other fatty acids are
less .

Pattee et al. (1969) reported that the oil content of
the kernel increases in a nearly linear manner up to the
time the kernels are considered mature at 12 weeks after
pegging. Taking this subject a step further, Pattee et al..
(1974) in a study on peanut fruit part compositional changes
at selected physiological stages during maturation.

16

concluded that the lipid content in the seed was low
initially and the rate of accumulation became maximum
between Stages 7 and 11. The highest level was observed in
the seed at full maturity (Stage 13) , then declined at
over-maturity (Stage 15) , suggesting that beyond Stage 13
lipid catabolism predominates over lipid synthesis.

Worthington and Smith (1974) noted significant changes
in fatty acid composition of peanut oil from seeds produced
on plants which had been treated with growth regulator
and/or various fungicides. They reported a decrease in the
level of linoleic acid in samples treated with Kylar.
Sources of differences were unknown, but it was theorized
that they might be associated with an extended period of
plant vigor and a change in the proportions of mature and
immature seeds in the treated samples. Control of
Cercospora leafspot with some foliar fungicides was reported
earlier to affect peanut maturity (Young et al. , 1972a) .
Beuchat and coworkers (1974) also reported significant
differences in the protein percentage and oil content of
peanut kernels, depending upon the fungicide treatment.
Delayed maturity was caused by specific fungicide
treatments .

Sanders (1980a) demonstrated that the oils from three
major commercial varieties of mature peanuts did not differ
substantially in relative weight distributions of lipid
classes, but that distribution of lipid classes was affected
by peanut maturity. His study indicates that the percentage

17

of various oil fractions, some thought to influence
oxidative stability, vary considerably with peanut maturity.
Sanders (1980b) reported that oleic acid increased while
other fatty acids decreased with maturity.

Post-harvest conditions like curing and storage could
also affect the results of total lipid and fatty acid
composition of peanut seeds. Brown et al. (1974) studied
the effects of storage period prior to oil extraction upon
oven stabilities of oil samples using different solvents.
They concluded that cold storage prior to extraction can
influence oven stabilities and correlations with
solvent-extracted and bag-pressed oils. Results indicated
that prolonged storage of the peanuts shortened oven keeping
times. Correlations with oleate/linoleate ratios decreased
with extended storage. Oils extracted from peanuts with
seedcoat with chlorof orm-methanol were less affected.

Young and Holley (1965) held inshell peanuts for more
than five years at 4-6 °C without significant effects on the
oil keeping time or roasting properties of freshly shelled
sound mature kernels.

Worthington and Holley (1967) noted that, although the
proportion of methyl linolenate in synthetic standards has
been observed to decrease with time during storage at -20 °C,
little change occurred in the linolenic acid content of
peanut oil stored under similar conditions. They attributed
the stability of linolenic acid in peanut oil to the
presence of naturally occurring antioxidants.

18

Khan and coworkers (1979) studied the effects of
storage at ambient room temperatures on raw and refined
peanut oils. They reported that the free fatty acid content
of the raw peanut oil increased from 1.2 to 2.7 percent and
the peroxide value increased from 5 to 10 during 660 days of
storage. However, no significant change was noted either in
iodine value or in visible color of the oil. While raw
peanut oils of good initial quality keep well in storage,
the peroxide value and color of refined oils are influenced
by conditions of storage and handling of oils during
storage .

Cecil (1975) studied storage stability of peanut butter
from ten peanut genotypes. He stored peanut butter from ten
genotypes in glass jars for periods up to 14 months at 0 , 70
and 100 F. Color and free fatty acid content of the samples
apparently varied only with genotypes, but aroma and flavor
scores after storage were positively correlated with
stability ratings for 100 F, and negatively with peroxide
values for 0 and 100 F. Negative correlations of peroxide
with stability ratings were significant at all combinations
before and after storage.

Yearly climatic variations and location effects were
considered important causes of variation in fatty acid
composition of peanut samples, since Crawford and Hilditch
(1950) stated that same varieties give oils differing in
composition when grown in different localities.

19

Holley and Hammons (1968) reported some extreme
year-to-year effects in the stability of oil from
26 different strains or varieties during an eight year
period. Eheart and coworkers (1955) also noted seasonal
variations in composition of Virginia type peanuts.

A study conducted by Worthington and coworkers (1972) ,
involving 82 peanut genotypes, indicated great seasonal or
yearly effect on oil stability. But, as reported earlier by
Holley and Hammons (1968) , the oil stability yearly
variations were completely unrelated to levels of linoleic
acid. The source of this variation was unknown, but
appeared to be related to seasonal factors such as yearly
variations in environmental conditions prevailing during
seed formation.

Tai (1972) showed that the cultivar by year
interactions were statistically significant when he examined
the oleic/linoleic ratios of peanut cultivars grown two
years at two locations within a state.

Young et al. (1974) studied the influence of location,
soil moisture, and seasonal variation on the fatty acid
composition of nine Spanish type peanut varieties. Although
no consistent pattern was found, variation in fatty acid
composition due to variety was much less in Oklahoma than in
Georgia for both the irrigated and nonirrigated peanuts.
Location effect and soil moisture conditions gave higher
percentages of palmitic and oleic, with a lower percentage
of linoleic in the Georgia samples and in the nonirrigated

i

20

samples from both locations. Although significant
differences were found in fatty acid composition from the
Southeast and Southwest, the unrelated pattern of variation
found in the stability of peanut oil led the authors to
suggest that there appear to be factors other than fatty
acid composition that influence stability of peanut oils.

Environmental conditions during seed formation affect
fatty acid composition of many seed oils. Researchers
reported that some plants produce a more highly unsaturated
seed fat when grown at lower temperatures (Hilditch and
Williams, 1964; Barker and Hilditch, 1950; Stumpf and
Bradbeer, 1959). Harris and James (1969) pointed out that
this effect is related to oxygen concentration within the
cell system.

Evidence for temperature effects during the growing
season on the fatty acid composition of peanut oil, although
sought by several authors, was always inconclusive. This
may be related to the development of peanut seeds
underground. Most of the attempts in determining degrees of
association among oil components and climatic parameters
were based on the whole growing season (Holley and Hammons,
1968) . Short but critical periods of high or low
temperatures were disregarded by considering only average
season parameters.

Holaday and Pearson (1974) subdivided the days after
pegging until maturity into four-week periods. They
reported that lower temperatures after pegging significantly

21

increased the contents of linoleic acid and decreased the
oleic acid of the oil. This lower temperature effect was
much more pronounced 0 to 4 weeks before harvest. No study
reporting associations among peanut oil composition and soil
temperature was found in the literature.

Another factor that can be misleading in the results of
fatty acid analysis is the portion of the seed tissue
analyzed. Different fruit tissues differ quantitatively and
qualitatively in lipid composition.

v/ The fatty acid composition of morphological distinct
tissues was studied in detail by Worthington (1968) . Using
the Virginia Bunch 67 variety during different stages of
maturation, the author reported that triglycerides
predominated the lipid make up of the cotyledons and embryo,
while complex lipids comprised a large percentage of testa
and shell lipids. At maturity, shells contained 0.6% crude
lipids, testa 2.9%, embryos 51.3% and cotyledons 52.2%. At
maturity the triglyceride fraction of the embryo contained
70% more palmitate, approximately 23% more linoleate, and 15
times the linolenate of the cotyledons. The cotyledons
contained higher levels of oleic and stearic acids.

Fore et al. (1953) demonstrated that the presence of
testa in the seeds during solvent extraction of the oils
increased the oven keeping time of the ensuing oils. The
effects of testa appear to be more significant as the period
of storage increases.

I

22

Fedeli and coworkers (1968) examined the fatty acid
composition of peanut tissues but did not state the genetic
origin of the samples. The oil composition of mature shells
more nearly resembled the cotyledons in their study. The
authors reported that embryos are richer in linoleic acid,
while cotyledons have more oleic acid than embryos.

Ahuja and coworkers (1971) cut seeds of two varieties
in three parts and analyzed them for fatty acid composition.
They concluded that the oil content was maximiim in the
middle portion and decreased both in the upward and downward
directions. Palmitic and higher fatty acids tended to be
distributed evenly in the three parts of the seed. The
amount of stearic acid was low in the lower part of the seed
and that of palmitoleic was low in the middle part. The
embryo (upper part) contains more linoleic and less oleic
acid as compared with the other seed parts, which have
almost the same amounts of the two fatty acids. These
results are in agreement with Fedeli and coworkers (1968) ,
although the last authors separated the seed into its
components instead of cutting it in three sections.

Diseases, insect infestation, growth regulators, damage
from harvest and other abnormalities of the seeds have also
been reported to affect the final analysis of fatty acids.
Development of fungi on the surface of peanut seeds has been
shown to affect sugars, as well as the total quantity and
unsaturation of free fatty acids (Ward and Diener, 1961;
Pattee and Sessoms, 1967). Chopra and Kanwar (1966)

23

reported that sulphur fertilization on deficient soils
lowered protein and raised oil content of peanut seeds.

Worthington and Smith (1973) studied the effects of
foliar fungicides, applied to peanuts for the control of
Cercospora leaf spot, on oil stability and fatty acid
composition of the oil. They found that Benlate and Bravo
gave the most pronounced effects on oil fatty acid
composition. In both years studied those fungicides
decreased levels of stearic (C18:0) and increased levels of
linoleic (C18:2) acid over the control in the Argentine and
Florunner varieties, which increased the iodine number of
those oils.

Taking this investigation a step further, Worthington
and Smith (1974) examined, in a three-year study, the
effects of the growth regulator Kylar with and without
Benlate on fatty acid composition of peanut oil. Kylar
reduced levels of linoleic acid when applied either alone or
with fungicide. Fungicide alone significantly increased
levels of linoleic acid, and the greatest difference in
levels of this fatty acid occurred between samples from
plots treated with fungicide alone and those treated with
Kylar alone. Alterations in the levels of other fatty acids
were less consistent. A visual inspection of the samples
suggested that plants treated with Kylar reached maturity
earlier than the others. The decrease in level of linoleic
acid, together with the greater degree of interior
pigmentation of the pods, suggests that Kylar accelerates

24

maturation in peanuts. Hartzook (1969) reported that with
increased maturity of the seed linoleic acid content in
peanut oils was reduced, while oleic acid was increased.

Laurence and coworkers (1976) also reported that
fungicidal spray increased the length of time to maturity.
High oil content accompanied the extended season of sprayed
plants, and protein levels usually were proportionally
lower. In addition to yield improvement, total protein
content of peanut kernels was raised and the oil/protein
ratio generally lowered by application of sulphur to
sulphur-deficient soils. On soils where sulphur is
sufficient, foliar application of sulphur dust may lead to
improved yields, but kernel protein production is little
affected. In such cases, the authors commented, the oil
content of kernels may be increased in comparison with those
from untreated plots, probably through delays induced in
plant maturity.

Ratner et al. (1979) studied the effects of symbiotic
nitrogen fixation on protein and oil accumulation in irri-
gated peanuts. Oil content of the kernels was found to be
in inverse relation to the crude protein content. The
kernels of the control sample had the highest oil content
and the lowest protein content; on the other hand, kernels
from inoculated plots had the highest protein content and
the lowest oil content, although on a per-unit area basis
yield of oil and protein was higher in inoculated
treatments .

25

Hovis et al_. (1979) studied the effect of two strains
of peanut mottle virus on fatty acid, amino acid and protein
of six peanut lines. They reported that the greatest effect
occurred on fatty acids and the least on the total amino
acids. In general, peanuts infected with a necrosis strain
had lower percentages of stearic and oleic acids, but higher
linoleic, arachidic , behenic, and lignoceric acid contents.
Peanuts infected with a mild strain generally showed a
slight increase in linoleic acid. There were almost twice
as many significant changes in the fatty acids of the
susceptible lines (Florunner and Starr) than in the tolerant
or moderately tolerant lines.

Hovis and coworkers pointed out that since virus
infection changes the chemical composition of peanut seed,
there is need for caution when chemical analysis is used to
evaluate various seed factors such as oil quality and
genetic characteristics. Peanut mottle virus is worldwide
in distribution, and its incidence in some fields is very
high; therefore, the virus effect could be significant in a
variety of standard tests.

Although several factors were shown to be responsible
for variations in the results of the analysis of fatty acid
components of peanuts, the last factor to be mentioned is,
without doubt, of greatest importance. Lack of accuracy and
precision in testing methods was always considered a major
factor causing variations in fatty acid composition of oils.

26

Numerous procedures exist for determining the
physicochemical properties of peanuts. Variations in
results between different laboratories using the same method
are not uncommon. The problem was illustrated in the 1965
report of the Instrumental Methods Committee of the American
Oil Chemist's Society, as pointed out by Cobb and Johnson
(1973) , wherein it was noted that the same peanut oil sample
analyzed in fourteen different laboratories produced such
ranges as 0.9 to 5.7% for stearate, 34.2 to 49.3% for
oleate, and 21.6 to 41.1% for linoleate.

Several studies of peanut oil fatty acid composition
have been reported. In some of the reports there are
considerable differences in the fatty acid composition of
the same varieties or genetic lines. In those studies, the
oils were either pressed or extracted from peanuts with a
variety of organic solvents; but it has to be taken into
consideration that few systems extract oilseed lipids with
equal efficiency.

Although oleate/linoleate ratios and oven keeping time
have been used for predicting shelf-life of peanut butter
(Worthington and Hammons, 1971), peanut oil (Young et al. ,
1974; Fore et al. , 1953) and other roasted peanut products
(Tai, 1972), Brown et al. (1974) reported that those
parameters can give misleading values with different types
of oil extraction, solvents and period of storage. Using
five different varieties, the authors determined the oven
stability of oils extracted with five common solvents and

27

hydraulically pressed oils. Relationships between oven
stabilities, storage period and 0/L ratios were also
determined. Brown et al. concluded that the length of the
oven keeping time can be affected by the method of solvent
extraction. If the peanuts are relatively fresh, good
correlations between 0/L ratios and keeping times can be
obtained using ether of low peroxide content, cyclohexane,
or chrorof orm-methanol , but the values for one set of
solvent extracted oils are not directly comparable to those
from oils extracted with a different solvent system. These
workers postulated that the increased stability of solvent-
extracted oil may have been due either to traces of solvent
or solvent contaminants remaining in the oils or to a more
efficient extraction of seed antioxidants by the more polar
solvents .

Young et al. (1974) studying fatty acid composition of
Spanish peanut oil as influenced by planting location,
moisture conditions, variety and season, also found
differences in oil stability related to differences in the
method of oil extraction. The authors reported that
solvent-extracted oils from the Georgia peanuts had better
than a 50% longer shelf-life than those grown in Oklahoma.
Whereas, oils from these same peanuts prepared by hydraulic
pressing did not show differences in stability.

Hokes (1977) found that removal of phosphatides from
the oil by precipitation reduced oven stability. Thus,
differences in the relative amounts of polar lipids

28

extracted by different solvents might explain the findings
of Brown and coworkers (1974).

Prior to the advent of the gas-chromatograph the
analysis of fatty acids has been based, in most of the
papers, on the preliminary resolution of the mixed peanut
fatty acids into insoluble and soluble lead salts, together
with fractional distillation of the esters of the acids from
the insoluble and, in some papers, from soluble lead salts.
In other cases the mixed fatty acids have been determined as
total saturated and oleic and linoleic acids from their
iodine and thiocyanogen values. Data on the fatty acid
composition of oils were obtained with considerable
difficulty and results were sometimes conflicting. For
example, until gas chromatography was applied to fatty acid
analysis, the presence of linolenic acid in peanut seeds was
subject to conflicting results.

Craig and Murty (1959) found eicosenoic {C20:l) acid
but not linolenic acid in peanut oil. These workers,
however, observed that methyl linolenate has an emergence
time coincidental with methyl eicosenoate on diethylene
glycol succinate columns, and that this liquid phase is
therefore unsuitable for the analysis of oils containing
both these acids.

Iverson and coworkers (1963) fractioned peanut oil
methyl ester with urea and confirmed the presence of
eicosenoic acid by gas-liquid chromatography and chemical
techniques, but did not detect linolenic acid. On the other

hand, French (1962) reported linolenate concentrations of
1.1 to 1.6%, which would appear to be rather high.

Worthington and Holley (1967) examined oils from seven
genetically diverse peanut cultivars and reported levels
varying from 0.02 to 0.04% of linolenic acid in peanut
seeds.

The polarity of the liquid phases must be taken into
consideration, in order to unambiguously demonstrate and
quantify linolenic acid in oils that also contain arachidic
and eicosenoic acid. In this case it is necessary to choose
a gas-liquid chromatograph liquid phase with polarity
characteristics that permit elution of the C18 series of
fatty acid methyl esters prior to elution of the C20 series
(Craig and Murty, 1959) . Diethylene glycol succinate and
other polyester phases of similar polarity are frequently
used in the analysis of fatty acid methyl esters, but these
phases do not adequately separate linolenic from arachidic
and eicosenoic acid esters. Thus, eicosenoic acid, and less
frequently arachidic acid, are sometimes misidentif ied and
reported as linolenic acid in the analysis of peanut oil.
For example, Koman and Kotuc (1976) reported values for
eicosenoic and linolenic acid in peanut oil but not
arachidic acid, although arachidic acid was first isolated
from Arachis oil by Gossman in 1854 (Cobb and Johnson,
1973) . Another example can be cited as in the paper by
Fristom and coworkers (1975) . In this paper the authors
misidentif ied eicosenoic acid as linolenic acid. Correction

30

of the mistake was reported later by Exler and coworkers
(1977) .

Worthington (1977) reported that authentic peanut oils
contain less than approximately 0.15% linolenic acid, and
that this value is not greatly influenced by geographic area
of production.

The genetic material in most of the papers reported
here was comprised of peanut seeds grown in Georgia or North
Carolina locations. In some of them a mixture of seeds of
more than one location was utilized.

Variations in results of oil composition due to
location, years, diseases, fertilizers, age, maturity,
methodology of chemical analyses, etc., have been reported
and were stressed and evidenced in this literature review.

To minimize these variations and properly select peanut
genotypes with improved chemical characteristics of the
seeds, it is imperative to study diverse genotypes growing
in the same location, during several years with a standard
procedure .

MATERIALS AND METHODS

The material for this study involved 100 genotypes
including peanut varieties, breeding lines and introductions
obtained from stocks of the Peanut Breeding Project of the
University of Florida and are designated by the numbers and
names in use in this project. Genotype selection was based
either upon prior knowledge of chemical composition in other
locations (Holley and Hammons, 1968; Worthington and
Hammons, 1971; VJorthington , 1977; and Sanders, 1980a), or
upon possible use in the development of new commercial
varieties, and included subspecies hypogaea as well as
subspecies f astigiata.

Table 1 shows genotypes and their pedigrees, years in
which fatty acid analyses of samples were made, and total
number of observations.

The genotypes involved in this study comprise a large
portion of the currently available peanut gene pool. Most
of them have been in experimental observation for over two
decades and have served as a genetic source for several new
varieties and crosses at the University of Florida.

All peanuts were grown according to the recommended
cultivation practices during the years of 1966 to 1974 and

31

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36

in 1978 at the University of Florida Green Acres Agronomy
Farm.

The peanut seeds were fungicide-treated and hand
planted in the field. They were sown 20 cm apart, in rows
60 m long, with 91 cm between rows to avoid competition.
Overhead irrigation was applied at planting and during dry
periods to obtain uniform emergence and adequate water for
normal growth.

Fertilizers were applied before planting at a rate of
560 to 785 kg/ha of 4-12-12 plus 22 kg/ha of No. 503 Frited
Trace Elements (F.T.E.). The applications were on a
broadcast basis followed by double discing.

A split application of gypsum at a rate of
approximately 780 kg/ha was broadcast over the rows, from
six to eight weeks after planting, to insure uniform and
sufficient Ca for normal seed development.

Herbicides, fungicides and insecticides were applied as
needed, and varied from year to year in accordance to
phytosanitary problems and product availability.

The harvest date was determined by the physiological
aspect of the plants such as loss of older leaves, general
yellowing of foliage, decreased peg strength (Bailey and
Bear, 1973) and by the hardness and pronounced roughness of
the pod surface (Sturkie and Buchanan, 1973) . In general,
Spanish type peanuts and other small seeded types were
harvested 7 to 12 days prior to the large seeded peanuts.

37

Planting and harvest dates for all years are included in
Table 2.

At harvest the plants were stack cured for 6 to 8 weeks
prior to picking with a carding-type machine. After that
the pod samples were promptly forwarded to the laboratory,
where they were kept in cold storage until the samples were
prepared for the analytical work. Samples were hand shelled
and carefully selected for sound, mature kernels as
indicated by seed size, absence of wrinkles and by the
pigmentation of the seedcoat and interior of the pericarp.
This procedure was followed to minimize the influence of
maturity on the results of chemical analysis (Young et al. ,
1972b; Sanders, 1980a) and also to remove moldy and
defective kernels. Analytical work was usually completed
within six months after harvest.

The procedure for analysis of fatty acids in peanuts
involved oil extraction, esterif ication and chromatography.
For oil extraction a 10-gram sample of shelled peanuts was
homogenized in a Waring Blender with 75 ml of hexane for
five minutes. The homogeneate was transferred to a 200 ml
volumetric flask, brought to room temperature, and diluted
with hexane. The suspension was mixed and allowed to
settle. A 25 ml aliquot of the supernatant solution was
evaporated to dryness in a vacuum oven at 70 °C. The oil
percentage was- calculated using the weight of this oil in
relation to the initial weight of the sample.

Table 2. Planting and Harvest Dates During the Ten-Year
Period (1966-1974 and 1978).

Year Date of Planting Date of Harvest

1966

May 3

August 25/Sept. 10

1967

May 16

September 14-21

1968

May 9

September 5-12

1969

April 18

August 18-26

1970

May 20

September 18-23

1971

May 2 7

September 22-30

1972

June 7

October 2-12

1973

April 26

August 20-27

1974

May 10

September 5-12

1978

May 3

August 23 /Sept. 11

39

The glyceride esters of the extracted oils were
converted into methyl esters by interesterif ication , using
sodium methoxide as a catalyst (Craig and Murty, 1959) . The
interesterif ication procedure is simple and requires less
time to prepare the samples for gas-chromatograph analysis
than the common esterif ication procedure.

Methyl ester derivatives of fatty acids were prepared
using a mixture of 100 mg of oil, 21 ml of methanol, and
0.5 mg of sodium refluxed for 30 minutes with constant
stirring. The cooled mixture was acidified with 1 ml of
acetic acid to inactivate the catalyst, diluted with 20 ml
of deionized water, and extracted with 5 ml of hexane three
times. The combined hexane fractions were evaporated to
1/2 ml under dry nitrogen, and a one microliter aliquot was
chromatographed .

Fatty acid methyl esters were analyzed on a Packard,
Model 7831, gas chromatograph , using a 183 mm versus 4 mm
glass column packed with a 20% coating of diethylene glycol
succinate on 80-100 mesh fire-brick (Applied Science
Laboratories, Inc., State College, Pennsylvania). The
column temperature was 185°C and the flame ionization
detector temperature was 195°C. Gas flow rates were as
follows: air flow rate was 350 ml/min, hydrogen flow rate
varied between 25 and 35 ml/min, and helium carrier gas was
used at a flow rate of about 30 ml/min.

Craig and Murty (1959) found that the succinate-
diethylene glycol polyester used for the column

40

completely separated stearic and oleic esters, but a log
plot showed that the methyl linolenate had an emergence time
coincident with methyl eicosenoate, which would complicate
the analysis of oils containing both of these fatty acids,
as do peanut oils. Besides that, the analytical procedure
using polyester columns in the fatty acid determination is
rapid and ideally suited when a large number of samples are
to be analyzed, and also when small quantities of fats and
oils are utilized in the analysis. The inaccuracy due to
inadequate separation of linolenic acid from eicosenoic acid
provided only a small bias in the results, because linolenic
acid in peanuts has been reported to be present in small
amounts, ranging from 0.03 to 0.13 weight percentage of
total fatty acids (Worthington , 1977) . Thus, results on
eicosenoic acid included also small percentages of linolenic
acid.

Peak areas were integrated manually by triangulation at
1/2 height and percentages of fatty acids were computed in
relation to total peak areas.

Periodically, percentage of total area under peaks was
calculated on chromatograms obtained by the injection of
actual standard quantitative mixtures of fatty acid methyl
esters into the column and detector of the chromatograph in
order to determine the quantitative efficiency of the
instrument. Analysis of the standards showed errors of less
than 5% of the total mixture in relation to the stated
standard composition. Using the same column, fatty acid

methyl esters in the samples were identified by comparing
their relative retention volumes and logarithm of relative
retention volumes with those of known standards obtained
from Applied Science Laboratories, Inc., and by plots of the
logarithm of relative retention volumes versus carbon
numbers (Packard Operation Manual, 1967). Relative
retention times were calculated by converting distance from
initiation of solvent peak to intersection of tangents to
sides of respective peaks into units of time.

It was possible to separate and quantify eight fatty
acids which account for approximately 98% of the total fatty
acids in peanut oil. The remaining percentages are composed
of the glycerol portion of triglycerides and other
constituents. Iodine values were calculated directly from
the amounts of unsaturated acids determined by the gas
chroma tograph, assuming purity and complete esterif ication
of the oil and are, therefore, approximately 6% higher than
would have been obtained by direct measurement (Worthington
et al. , 1972) .

Cumulative rainfall, mean maximum and minimum air
temperature, mean maximum and minimum soil temperature, and
the average of the four last parameters for each year were
recorded in relation to the period of fruit formation and
seed development (from 8 weeks after planting until
harvest) . The climatological data were obtained from the
Agronomy Department records (1966-1978), and the values are
reported in Table 3. Correlation coefficients were

42

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43

calculated involving climatic parameters with all other
variables in order to study possible effects of temperature
and v/ater regime in the yearly variation of fatty acids,
iodine number and oil percentage.

All statistical analyses were performed at the
Northeast Regional Data Center of the State University
System of Florida, Gainesville, Florida. The analyses were
obtained using the procedures of the Statistical Analysis
System (SAS) of the SAS Institute, Inc. The procedures are
listed in Barr et al. (1979) and Helwig (1977).

Of the 100 genotypes included in this study, only 40
appeared in more than one year, although genotypes that
appeared only once might have had more than one replication.
For the analysis of variance and subsequent test of means,
only the genotypes that appeared at least in two years were
considered. Due to missing values and unequal subclass
numbers the data were analyzed by the method of least
squares using the General Linear Model (GLM) procedure from
SAS 79.5. Correlations were obtained using SAS ' s
correlation procedure. A discussion of these analysis
procedures can be found in references listed by Barr et al.
(1979) .

The whole experiment was considered a completely random
design with a two-way classification model (years and
genotypes) and no interaction. Genotypes whose fatty acid
analyses were not made in a given year were handled as

44

missing data. Unequal numbers of replications were also
present .

The model used in the analysis of variance was

Y. = y + a. + 3 . + e .

where Y. is the k^^ observation (replicate) of the j^^
genotype in the i^'^ year,

y is the overall mean for all the treatments,

t h

is the effect of the i year,

t h

6j is the effect of the j genotype, and
e. is the component of random error associated with
observation ijk.
An approximate test to select a group of one or more
genotypes, so that the probability of including the genotype
with the lowest (or the highest) mean is at least (1-a) ,
would be a modification of the test proposed by Gupta in
1956.

In the original test if Y is the largest sample

max ^ ^

mean, then all treatments in the interval

Y - V ( a; t) a-
max * ' ' "^y

are retained and the probability that this interval includes
the treatment with the largest mean is at least (1-a) .

One of the principal requirements to apply the original
test developed by Gupta is that all populations have a

45

2

common known variance a . As the population variance is

2

generally not known, the sample estimate for a / i.e. error
mean square, may be used provided the number of degrees of
freedom is large, as it is in this study.

Another important requirement in the test is that each
sample mean is based on the same number of observations.
Due to unequal subclass numbers, the original test was
modified by dividing the error mean square by the harmonic
mean. For the same reason, least square means were utilized
instead of the sample means. Thus, the critical highest
mean would be

EMS

LSM_^ - V (.05;t) . [^]

max

where LSM is the maximum least square mean,
max

V (.05;t) is the critical value for a=0.05 and t
genotypes found in special tables (Gupta, 1956) ,

EMS is the error mean square provided by the analysis
of variance, and

is the harmonic mean, obtained by the following

formula ;

H n ^n, n_ • • • n . •'
o o 1 2 3

t h

where n^ is the number of observations for the j genotype,
and n^ is the number of genotypes.

46

As some values are desirable in either large or low
amounts, depending on the standpoint considered (industrial
or dietary) , group separation was made taking into
consideration that maximum or minimum values are desirable.
Thus, the critical lowest mean would be

LSM . + V (.05;t) . [|^]
mm '

where LSM . is the minimum least square mean,
mm ^

In order to use the Gupta test the least square means
must be put first in increasing or decreasing order.

The data were analyzed combined (40 genotypes) and then
later subdivided into three maturity groups (early, medium
and late) and four commercial types (Virginia, Runner,
Spanish and Valencia) . Early maturing genotypes comprised
those whose total cycle varied from 110 to 125 days. Medium
maturity genotypes represented those maturing from 126 to
140 days, while later maturing genotypes had a total cycle
ranging from 141 to 150 days.

RESULTS AND DISCUSSION

The fatty acids, iodine value and oil content means of
100 genotypes over the ten years under study are presented
in Table 4, as well as the number of observations on which
the means are based.

The range in oil composition among the genotypes under
investigation was rather large. Mean ranges in fatty acid
composition were as follows: palmitic (hexadecanoic , C16:0)
6.90 to 17.50%; stearic (octadecanoic, C18:0) 1.55 to 5.00%;
oleic (cis 9-octadecenoic , C18:l) 40.60 to 73.50%; linoleic
(cis 9, cis 12-octadecadienoic, C18:2) 8.60 to 39.15%;
arachidic (eicosanoic, C20:0) 0.10 to 2.00%; eicosenoic (cis
11-eicosenoic, C20:l) 0.20 to 2.50%; behenic (docosanoic,
C22:0) 0.40 to 5.10%; and lignoceric (tetracosanoic , C24:0)
traces to 3.80%. Iodine number varied from 75.00 to 105.00,
while oil percentage ranged from 46.20 to 53.40%.

The data from this study indicate that there is
quantitative diversity of fatty acids, iodine value and oil
content in the genus Arachis, and that the magnitude of this
diversity should be sufficient to permit the development of
new varieties with improved chemical qualities.

Similar ranges in fatty acids were recorded by
Worthington et al. (1972), when they studied 82 peanut

47

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52

genotypes during a three-year period. Large differences in
fatty acid composition of peanut samples were also reported
by Holley and Hammons (1968) . Differences of 20% in the
high-low range for oil and 217% for linoleic acid were noted
in their study.

As shown in Table 4, oleic (C18:l) and linoleic (C18:2)
acids are the major fatty acids, and together generally
comprised about 80% of the total fatty acids present in the
oil.

For the analysis of variance, and subsequent test of
means, only the genotypes that appeared in at least two
years were considered. Mean squares and significance levels
of the combined data (40 genotypes) are shown in Table 5, as
well as the variable means and coefficients of variation.

In the combined analysis of variance, genotypes and
years were highly significant (P < 0.01) for iodine value,
oil percentage and all fatty acids, except arachidic and
behenic. For these two fatty acids, year effects were
highly significant while the genotypic differences were not.

Yearly variation in fatty acid composition of peanut
genotypes was also reported by other authors (Holley and
Hammons, 1968; Worthington and Hammons, 1971; Worthington et
al. , 1972; and Tai, 1972). The source of variation is not
well clarified, but appears to be related to climatic
effects, such as temperature and moisture. The possible
effects of temperature and rainfall on the chemical

53

Table 5. Mean Squares from the Analysis of Variance,

Coefficients of Variation (C.V.) and Means of Fatty
Acids, Iodine Value and Oil Percentage of 40 Peaunt
Genotypes .

Palmitic Stearic Oleic Linoleic Iodine
Source df C16 C18 C18;l C18:l Value

Model

48

23.

.6119**

2.

. 2548**

295.

. 1866**

216.

.9000**

176.

. 1881**

Year

9

9,

. 9162**

5.

.8223**

38,

. 1580**

91.

.6908**

241.

,3358**

Genotype

39

16.

, 8954**

1.

,3327**

318.

,3928**

221.

,9624**

116.

,6200**

Error

166

1.

,2677

0,

,3780

8.

,2237

9.

,5769

11.

, 8726

Mean

11.

,6730

2.

,4484

51.

, 8372

27.

,6809

94.

, 6651

C.V.

9.

, 6454

25.

,1113

5.

,5321

11.

,1798

3.

, 6399

Arachidic Eicosenoic Behenic Lignoceric
Source df C20 C20; 1 C22 C24

Model

48

0.

.5437**

0,

.4578**

1,

.4260**

0,

. 8507**

Year

9

2.

.0979**

0.

. 9795**

3.

, 6380**

2,

. 7997**

Genotype

39

0.

,1375

0.

,1372**

0.

, 5731

0.

,2105**

Error

158

0.

,1158

0.

,0745

0.

,4884

0.

,1185

Mean

1.

,2227

1.

, 3304

2.

, 6353

1.

, 1005

C.V.

27.

,8369

20.

,5111

26.

,5186

31.

,2763

Source

df

Oil

Model

45

6.

2587**

Year

7

8.

5014**

Genotype

38

5.

1883**

Error

97

1.

7206

Mean

50.

5832

C.V.

2.

5932

**Significant at 0.01 level.

54

composition of peanut genotypes in this study are discussed
later.

The coefficients of variation for the combined data
were low for oil, iodine value and oleic acid. Medium
coefficients were found for palmitic and linoleic acids,
while the coefficients of variation for stearic, eicosenoic,
arachidic, behenic and lignoceric acids were very high.
Iodine value, oil percentage and the major fatty acids
seemed to be quantified in the chemical analyses with more
relative precision, while the fatty acids that represent
only small percentages of the total (C18, C20:l, C20, C22
and C24) were of difficult quantification. Higher
coefficients of variation for the minor fatty acids in
comparison with the major ones were also reported by
Worthington and Holley (1967) .

As is clearly seen in Table 5, most of the variation in
oleic (C18:l) and linoleic (C18:2) acids was due to genotype
effects, while years appeared to have a greater influence on
the iodine value and minor fatty acids (CIS, C20, C20:l, C22
and C24) . Very little seasonal variation in oleic and
linoleic acid content of peanut oil was observed by Pickett
and Holley (1956) .

A modification of the test proposed by Gupta (1956) was
utilized to obtain a set of least square genotype means
which included either the highest or lowest yielding
genotype. Use of least square means was necessary due to

55

unequal subclass numbers. Procedures for the application of
the test were described in the previous section.

Table 6 presents the least square means and standard
errors of the forty genotypes, as well as least square mean
group separation in relation to maximum and minimum values
for all dependent variables. Genotype grouping was made
taking into consideration that maximum or minimum values are
desirable. There are some parameters, for example, linoleic
acid, that are desirable in large amounts when considering
human health, while for industrial quality of peanut
products low amounts are sought.

Based on dietary qualities of the oil (low oleic, high
linoleic, high iodine value) the best genotypes would
include C10302A-4-3-B-1 , genotypes derived from F 439 and
F 529B, genotypes F 455-2-2, F 416-2, F 504A-2-1-1-1 and
F 487A-7-10-2-B2. On the other hand, based on industrial
qualities (high oleic, low linoleic, low iodine value), the
best genotypes would include Storers Jumbo, genotypes
derived from F 393 in general (including NC-FLA 14) ,
F 520B-VAR-10-2-B, OT Early Bunch, F 420-100-2-4-1-1-4,
genotypes derived from F 427B, Florigiant, F 435-2-3-1-B-B
and F 490-2-1-1-2-1-1-2-B . Those are also, with the
exception of Storers Jumbo, high oil genotypes.

Included in the best group of genotype means for all
variables were genotypes from early, medium and late
maturity groups, as well as Virginia, Runner, Spanish and
Valencia commercial types. The data show that iodine

56

Table 6. Least Square Means, Standard Errors and Genotype

Grouping of Oil Components of 40 Peanut Genotypes.

Palmitic Acid

(C16)

Laboratory Number and

Least Square

Standard

Genotype

Mean

Error

31

F 459B-3-2-4-6-3-1-1-B

15.02*

0.45'

41

F 501A-12-l-l-l-3-l-8-bl0

14.43*

0.67

42

F 504A-2-1-1-1

14. 22*

0.67

30

F459B-3-2-4-6-2-2

14.05*

0 . 28

92

Pearl White Spanish

13.82*

0. 82

19

F 439-2-3-2-1

13.79*

0 . 52

49

F 520B-VAR-10-2-B

13 . 40*

0.82

95

Val Ga 803-1-1

13. 32*

0.57

22

F 439-16-6-3-2

13. 14*

0.26

18

F 435-2-3-1-B-B

13. 09*

0. 43

54

F 531A-7-4-B

13. 00*

0.82

53

F 529B-4-1-2

12. 90*

0 . 82

81

C10302A-4-3-B-1

12.30

0. 82

6

F 416-2

12.07

0.36

29

F 455-2-2

12.00

0.52

45

F 519-3-1-2-1-B

11.93

0.67

28

F 454-8-23-9-3-3-1-B3

11.86

0.66

24

F 439-17-2-1-1-3

11. 66

0.33

23

F 439-16-10-1-1

11.59

0.81

21

F 439-16-4-9-1-B2

11.39

0 . 57

20

F 439-16-1-1-3-2-1

11.29

0.81

86

Florunner

11.26

0.29

85

Florigiant

10.58

0.40

40

F 490-2-1-1-2-1-1-2-B

10.39

0.67

88

Pearl Early Runner

10 . 25**

0.67

47

F 519-4-1-1-1-3-2-B

10.21**

0.62

7

F 420-100-2-4-1-1-4

10. 18**

0.43

1 7

F 427B-R-3-1-1-B-64

10 . 15**

0.81

15

F 427B-V-5-B4

9.83**

0.67

83

OT Early Bunch

9 . 75**

0.83

33

F 476-1-1-5-1

9.61**

0.58

37

F 487A-7-10-2-B2

9.56**

0.67

16

F 427B-V-11-B

9.20**

0.58

14

F 427B-V-4-73

9.11**

0.83

5

F 393-9-5-4-2-1

8.89**

0.47

10

F 427B-3-1-7-4

8.84**

0.58

87

NC-FLA 14

8. 66**

0.70

4

F 393-7-1

8.18**

0.47

94

Storers Jumbo

8.07**

0. 82

3

F 393-6-3-2-2

8.01**

0.47

*Best group of genotypes for desirable maximum values (P<.05)
**Best group of genotypes for desirable minimum values (P<.05)

57

Table 6. Continued.

Stearic Acid

(C18)

Laboratory Number and

Least Square

Standard

Genotype

Mean

Error

92

Pearl White Spanish

4.48*

0.45

87

NC-FLA 14

4.48*

0.37

42

F 504A-2-1-1-1

3. 66*

0.37

3

F 393-6-3-2-2

3.40*

0.26

20

F 439-16-1-1-3-2-1

3.25*

0.44

4

F 393-7-1

3. 22*

0.26

16

F 427B-V-11-B

3.21*

0.32

95

Val Ga 803-1-1

3.17**

0.31

85

Florigiant

3. 16**

0.22

7

F 420-100-2-4-1-1-4

2 .98**

0. 24

49

F 520B-VAR-10-2-B

2.89**

0.45

18

F 435-2-3-1-B-B

2.78**

0.24

94

Storers Jumbo

2. 73**

0.45

5

F 393-9-5-4-2-1

2.65**

0.26

15

F 427B-V-5-B4

2.58**

0.37

83

OT Early Bunch

2.58**

0.45

54

F 531A-7-4-B

2.54**

0.45

6

F 416-2

2.54**

0.20

88

Pearl Early Runner

2.47**

0.36

28

F 454-8-23-9-3-3-1-B3

2.47**

0.36

30

F 459B-3-2-4-6-2-2

2.47**

0.15

14

F 427B-V-4-73

2.46**

0.45

10

F 427B-3-1-7-4

2.42**

0.32

29

F 455-2-2

2.39**

0.28

17

F 427B-R-3-1-1-B-64

2.39**

0.44

41

F 501A-12-l-l-l-3-l-8-blO

2.38**

0.37

45

F 519-3-1-2-1-B

2.34**

0.37

40

F 490-2-1-1-2-1-1-2-B

2.35**

0.37

31

F 459B-3-2-4-6-3-1-1-B

2.31**

0.24

P 4 Q— 1 7— "5— 1 _ 1 _ "3
r 'i Jiy~ 1 / ~ Z~ 1~ 1~ J

2.24**

0.18

86

Florunner

2.22**

0.16

33

F 476-1-1-5-1

0.31

23

F 439-16-10-1-1

2.15**

0.44

22

F 439-16-6-3-2

2.15**

0.14

19

F 439-2-3-2-1

2.07**

0.28

47

F 519-4-1-1-1-3-2-B

2.00**

0.34

21

F 439-16-4-9-1-B2

1.99**

0.31

81

C10302A-4-3-B-1

1.94**

0.45

37

F 487A-7-10-2-B2

1.91**

0.37

53

F 529B-4-1-2

1.89**

0.45

*Best group of genotypes for desirable maximum values (P<. 05)
**Best group of genotypes for desirable minimum values (P<.05)

58

Table 6. Continued.

Oleic Acid

(C18 : 1 )

Laboratory Number and

Least Square

Standard

Genotype

Mean

Error

94

Storers Jumbo

73.14*

2. 08

3

F 393-6-3-2-2

69.21*

1 . 20

5

F 393-9-5-4-2-1

64.45

1.20

4

F 393-7-1

64.20

1 . 20

14

F 427B-V-4-73

63.92

2.11

10

F 427B-3-1-7-4

62.61

1 . 49

16

F 427B-V-11-B

62.31

1 . 48

87

NC-FLA 14

62.26

1.71

83

OT Early Bunch

62.00

2.11

17

F 427B-R-3-1-1-B-64

60 . 38

2.07

33

F 476-1-1-5-1

60 . 25

1. 47

15

F 427B-V-5-B4

60.00

1 . 72

7

F 420-100-2-4-1-1-4

59.68

1.10

40

F 490-2-1-1-2-1-1-2-B

58.43

1 .71

45

F 519-3-1-2-1-B

56.33

1.71

21

F 439-16-4-9-1-B2

56. 29

1.46

49

F 520B-VAR-10-2-B

56.15

2.09

88

Pearl Early Runner

55. 90

1 . 70

20

F 439-16-1-1-3-2-1

55.41

2.07

28

F 454-8-23-9-3-3-1-B3

55 . 40

1.70

85

Florigiant

55.20

1.02

37

F 487A-7-10-2-B2

53. 49

1.71

86

Florunner

53.41

0. 73

47

F 519-4-1-1-1-3-2-B

52 . 44

1 .57

23

F 439-16-10-1-1

51.91

2.07

18

F 435-2-3-1-B-B

50.81

1 . 10

24

F 439-17-2-1-1-3

48.91

0.85

54

F 531A-7-4-B

48 . 00

2.09

31

F 459B-3-2-4-6-3-1-1-B

47. 89

1.14

30

F 459B-3-2-4-6-2-2

46.59**

0.72

6

F 416-2

45 . 54**

0 . 93

29

F 455-2-2

44.24**

1.32

41

F 501A-12-l-l-l-3-l-8-bl0

44.06**

1.71

42

F 504A-2-1-1-1

43.76**

1.72

95

Val Ga 803-1-1

42.71**

1.46

19

F 439-2-3-2-1

41.98**

1.32

92

Pearl White Spanish

41.49**

2.08

22

F 439-16-6-3-2

41.48**

0.66

53

F 529B-4-1-2

41.25**

2.09

81

C10302A-4-3-B-1

41.10**

2.09

*Best group of genotypes for desirable maximum values (P<. 05)
**Best group of genotypes for desirable minimum values (P<.05)

59

Table 6. Continued.

Linoleic Acid

(C18: 2)

Laboratory Number and

Least Square

Standard

Genotype

Mean

Error

81

C10302A-4-3-B-1

38.01*

2. 26

22

F 439-16-6-3-2

36.96*

0.72

19

F 439-2-3-2-1

36.01*

1.42

29

F 455-2-2

35.58*

1.42

53

F 529B-4-1-2

35.21*

2.26

54

F 531A-7-4-B

34. 97*

2.25

6

F 416-2

33. 65*

0.99

42

F 504A-2-1-1-1

33.58*

1.85

95

Val Ga 803-1-1

33.12*

1.58

41

F 501A-12-l-l-l-3-l-8-blO

31.73*

1.84

30

F 459B-3-2-4-6-2-2

30.89

0. 78

24

F 439-17-2-1-1-3

30.84

0.91

92

Pearl White Spanish

30.21

2.26

31

F 459B-3-2-4-6-3-1-1-B

28.77

1.23

37

F 487A-7-10-2-B2

28.63

1.84

23

F 439-16-10-1-1

27. 78

2.24

47

F 519-4-1-1-1-3-2-B

27.70

1.70

86

Florunner

26.51

0.79

18

F 435-2-3-1-B-B

26.21

1.19

88

Pearl Early Runner

25. 75

1.83

20

F 439-16-1-1-3-2-1

25. 08

2.24

21

F 439-16-4-9-1-B2

24.86

1.58

28

F 454-8-23-9-3-3-1-B3

24.26

1.83

85

Florigiant

23.89

1.11

45

F 519-3-1-2-1-B

22.49

1.84

40

F 490-2-1-1-2-1-1-2-B

22.26

1.84

33

F 476-1-1-5-1

22.01

1.58

15

F 427B-V-5-B4

21 . 64

1.85

49

F 520B-VAR-10-2-B

21.11

2.26

7

F 420-100-2-4-1-1-4

20.92

1.19

17

F 427B-R-3-1-1-B-64

20.89

2.23

83

OT Early Bunch

20.35

2.27

10

F 427B-3-1-7-4

19.77

1.60

14

F 427B-V-4-73

19.22

2.28

16

F 427B-V-11-B

18.60

1.60

87

NC-FLA 14

17.76**

1.84

4

F 393-7-1

17.07**

1.29

5

F 393-9-5-4-2-1

16.89**

1.29

3

F 393-6-3-2-2

13.33**

1.29

94

Storers Jumbo

11.47**

2.25

*Best group of genotypes for desirable maximum values (P<.05)
**Best group of genotypes for desirable minimum values (P<.05)

60

Table 6. Continued.

Aracniuic /iciu

i uz u ^

Laboratory Number and

jjeasu iDquare

o uanaaru

Genotype

Mean

Error

b J

r bzbB— 4— i— 2

1 Q Q *

U . 2b

4

TOT n 1

r jyj-/— 1

1 c; /I *

i . b4''

U . lo

O 1
O i

C i (J J U z A— 4 — J - B — i

1 "3 *

1 . b J"

U . 2b

4 b

r biy— J— B

1 . bU

U . 2U

4 /

r biy— 4— i— i— i— J— z-B

1 ^ 53 *

i . 4 o

n 1 Q

u . 1 y

b

r jy J-y— b— 4-z-i

1 /I "7 * * *

J- . 4 1^

n 1 c
U . lb

iU

r 42 /B— J— i— / — 4

n 1 Q
U . 1 o

y b

vai (ja oUo— 1— 1

i . 4 b

n 1 "7
U . 1 /

0 b

Flor ig iant

1.4b

n 1 o
U . 1 2

4U

F 4y U-2-1-1-2-1-1-/-B

1 /I o It A
1 . 4 O

n on
U . 2U

4 y

T7 cr T n la \ ZATD 1 n o d

r D z UB— VAK— 1 U— z— B

n o c
U . 2b

1 a
1 D

r 4z/B— V— li— B

1 . Jo'""'

n 1 o
U . 1 o

■7

/

c inn o yi 1 1 >i
F 42U— iUU— 2— 4— 1— 1— 4

i /

F 42 /B-R- J— i — 1— B— 64

1 o o * * *
1 • O 2

n o c
U . 2b

Q C
0 D

Florunner

1 on***

n no
0 . U 9

J

r jyj-D-J— 2— 2

1 "3 Q * * *

n 1 >!
U . 14

O /

r 48/ A— /-iU — 2— B2

1 on***

n on
U . 20

1 A

1 4

F 42/B-V-4-73

1 o ^ * * *
1.2b***

U . 25

I. ^

r 4jy— ib-b— 3— 2

1 o o * * *

1 . 2 J * * *

n no
0 . Oo

O "7

O /

NC-FLA 14

1 o o * * *

1.23***

0 . 20

C A

b4

F b3iA-7-4-B

1 o o * * *

1 . 2 J * * *

0.25

Pearl wnite Spanisn

1 o o * * *

1.22***

0 . 25

2. 1

F 4 J 9- 16-4- 9-1 -B2

1 1 * * *
1 . 2 1 * * *

0.17

•3 1

r 4byB— J— z— 4-6— 3- 1— 1— B

1 1 n * * *

A 1 >1

0.14

1 O

F 4 Jb-2-3-l-B-B

1 1 n * * +

1.19***

A IT

0.13

JU

r 4b yB— J— 2— 4— b— 2— 2

1 . 1 o * * *

A A A

0.09

0 J

F 47b-l-l-5-l

1 . 18 ***

A 1 "7

0.17

y b

Storers Jumbo

1,1 / * * *

0 . 25

4 1

T? ciniA — lo 1 1 1 "3 1 o Kin
r bU iA— i 2— X— i— i— J— i— 0— D i U

1.17***

0 . 20

24

F 439-17-2-1-1-3

1.16***

0.10

23

F 439-16-10-1-1

1 1 >i * *
1 . 1 4 * *

n o c
0.25

29

F 455-2-2

1.10**

0. 16

19

F 439-2-3-2-1

1.08**

0.16

15

F 427B-V-5-B4

1.08**

0.20

6

F 416-2

1.08**

0.12

28

F 454-8-23-3-3-1-B3

1.06**

0.20

88

Pearl Early Runner

0.99**

0.20

20

F 439-16-1-1-3-2-1

0.79**

0.25

42

F 504A-2-1-1-1

0.76**

0.20

83

OT Early Bunch

0. 75**

0.25

*Best group of genotypes for desirable maximum values (P<. 05)
**Best group of genotypes for desirable minimum values (P<. 05)

61

Table 6. Continued.

Eicosenoic Acid

(C20:l)

Laboratory Number and

Least Square

Standard

Genotype

Mean

Error

87

NC-FLA 14

1. 76*

0. 16

4

F

393-7-1

1 . 65*

0 . 14

16

F

427B-V-11-B

1 .59*

0. 14

41

F

501A-12-l-l-l-3-l-8-blO

1 .56*

0. 16

10

F

427B-3-1-7-4

1 .54*

0.14

5

F

393-9-5-4-2-1

1.51*

0. 13

47

F

519-4-1-1-1-3-2-B

1 . 49*

0.15

85

Florigiant

1 .47*

0. 10

23

F

439-16-10-1-1

1.44*

0.20

95

Val Ga 803-1-1

1.41*

0. 14

18

F

435-2-3-1-B-B

1 . 40*

0.10

54

F

531A-7-4-B

1 . 38*

0.20

30

F

459B-3-2-4-6-2-2

1.36*

0.07

45

F

519-3-1-2-1-B

1 . 33*

0 . 16

86

Florunner

1.33*

0.07

3

F

393-6-3-2-2

1.30*

0.11

17

F

427B-R-3-1-1-B-64

1.30*

0. 20

40

F

490-2-1-1-2-1-1-2-B

1 . 30*

0. 16

24

F

439-17-2-1-1-3

1.27*

0.08

31

F

459B-3-2-4-6-3-1-1-B

1 . 27*

0.11

15

F

427B-V-5-B4

1 . 27*

0.16

14

F

427B-V-4-73

1 . 26*

0.20

22

F

439-16-6-3-2

1. 26*

0.07

28

F

454-8-23-9-3-3-1-B3

1.25*

0. 16

21

F

439-16-4-9-1-B2

1. 25*

0. 14

42

F

504A-2-1-1-1

1 . 22***

0. 16

7

F

420-100-2-4-1-1-4

1 .21***

0.11

20

F

439-16-1-1-3-2-1

1.19***

0.20

49

F

520B-VAR-10-2-B

1.18**

0.20

33

F

476-1-1-5-1

1.17**

0.14

6

F

416-2

1.14**

0. 10

53

F

529B-4-1-2

1.13**

0.20

88

Pearl Early Runner

1.11**

0.16

29

F

455-2-2

1.11**

0. 13

83

OT

' Early Bunch

1.11**

0.20

19

F

439-2-3-2-1

1.10**

0.13

37

F

487A-7-10-2-B2

0.99**

0.16

81

C10302A-4-3-B-1

0.88**

0.20

94

Storers Jumbo

0.86**

0.20

92

Pearl White Spanish

0.66**

0.20

*Best group of genotypes for desirable maximum values (P<. 05)
**Best group of genotypes for desirable minimum values {P<.05)

62

Table 6. Continued.

Behenic Acid (C22)
Laboratory Number and Least Square Standard

Genotype Mean Error

D O

F

529B-4-1-2

"3 O Q ^

0 • 51

Q

Val Ga 803-1-1

u • 36

1 0

F

435-2-3-1-B-B

"0 O "7 * * *

A "7

0.27

A
'i

F

393-7-1

o o o * * *

0.36

A 1

F

50 lA-1 2-1-1-1-3- 1-8-blO

0.42

c
D

F

393-9-5-4-2-1

J . 1 (J

0.32

P 1
0 1

C10302A-4-3-B-1

, J . u y ^ *

0 . D 1

J /

F

487A-7-10-2-B2

J , U 4 ^ ^

0.42

0 D

Florigiant

0 . 25

1 Q

F

439-2-3-2-1

z . 82***

0.32

F

439-16-10-1-1

2 . bl***

0.51

/I

D 'i

F

531A-7-4-B

z . 79***

0.51

A Q

F

520B-VAR-10-2-B

z . / y * *

0.51

F

439-16-6-3-2

z . 76***

0.17

9 4
Z 4

F

439-17-2-1-1-3

2 . 75***

0.21

P

O 0

Florunner

O •? "D * * *
Z . / Jl***

0.18

4 D

F

519-3-1-2-1-B

2.64***

0.42

P 7

NC-FLA 14

2.64***

0.42

An

4 U

F

490-2-1-1-2-1-1-2-B

2 . 61***

0.42

•3
J

F

393-6-3-2-2

2.59***

0 . 29

7

F

420-100-2-4-1-1-4

z . 58***

0.27

4 7
4 /

F

519-4-1-1-1-3-2-B

2.57***

0 . 38

z u

F

439-16-1-1-3-2-1

2.57***

0.51

T n

J u

F

459B-3-2-4-6-2-2

z . 5 5 * * *

0.18

u

F

416-2

z . 53***

0 . 25

1 D

F

427B-V-5-B4

2.52***

0 . 42

1 u

F

427B-3-1-7-4

2.51***

0 .36

29

F

455-2-2

2.49***

0.32

16

F

427B-V-11-B

0 44***

17

F

427B-R-3-1-1-B-64

2.35**

0.51

31

F

459B-3-2-4-6-3-1-1-B

2.31**

0.28

14

F

427B-V-4-73

2.30**

0.51

88

Pearl Early Runner

2.30**

0.41

33

F

476-1-1-5-1

2.21**

0.36

28

F

45 4-8-23-9-3-3-1-B3

2.16**

0.41

92

Pearl White Spanish

2.12**

0.51

83

OT

' Early Bunch

2.12**

0.52

42

F

564A-2-1-1-1

2.09**

0.42

21

F

439-16-4-9-1-B2

2.03**

0.36

94

Storers Jumbo

1.82**

0.51

*Best group of genotypes for desirable maximum values (P<.05)
**Best group of genotypes for desirable minimum values (P<.05)

63

Table 6. Continued.

Lignoceric

Acid (C24)

Laboratory Number and

Least Square

Standard

Genotype

Mean

Error

47

F

519-4-1-1-1-3-2-B

1.78*

0.19

28

F

454-8-23-9-3-3-1-B3

1.66*

0.20

49

F

520B-VAR-10-2-B

1.59*

0.25

53

F

529B-4-1-2

1 .49*

0.25

41

F

50 lA-1 2-1-1-1-3- 1-8-blO

1.46*

0.20

45

F

519-3-1-2-1-B

1 . 44*

0.20

85

Florigiant

1.32*

0.12

23

F

439-16-10-1-1

1 .25***

0.25

24

F

439-17-2-1-1-3

1.23***

0.10

95

Val Ga 803-1-1

1 .22***

0.18

18

F

435-2-3-1-B-B

1.21***

0.13

33

F

476-1-1-5-1

1 .21***

0.18

86

Florunner

1.19***

0.09

17

F

427B-R-3-1-1-B-64

1.18***

0.25

19

F

439-2-3-2-1

1.17***

0.16

31

F

459B-3-2-4-6-3-1-1-B

1.16***

0. 14

92

Pearl White Spanish

1.16***

0.25

7

F

420-100-2-4-1-1-4

1.16***

0.13

15

F

427B-V-5-B4

1. 14***

0.21

87

NC-FLA 14

1.12***

0.20

83

OT Early Bunch

1.12***

0.26

88

Pearl Early Runner

1.11***

0.20

22

F

439-16-6-3-2

1.11***

0.08

6

F

416-2

1.07***

0.13

4

F

393-7-1

1.06***

0.18

20

F

439-16-1-1-3-2-1

1.05***

0.25

10

F

427B-3-1-7-4

1.04**

0.18

21

F

439-16-4-9-1-B2

1.04**

0.18

16

F

427B-V-11-B

1.03**

0.18

29

F

455-2-2

1 .02**

0. 16

30

F

459B-3-2-4-6-2-2

0.94**

0.09

37

F

487A-7-10-2-B2

0.96**

0.20

40

F

490-2-1-1-2-1-1-2-B

0.92**

0.20

54

F

531A-7-4-B

0.89**

0.25

5

F

393-9-5-4-2-1

0. 86**

0.16

94

Storers Jumbo

0.81**

0.25

42

F

504A-2-1-1-1

0. 66**

0.21

81

C10302A-4-3-B-1

0.79**

0.25

14

F

427B-V-4-73

0. 57**

0.25

*Best group of genotypes for desirable maximum values (P<. 05)
**Best group of genotypes for desirable minimum values (P<. 05)

64

Table 6. Continued.

Iodine Value

Laboratory Number and
Genotype

iieasu oquare
Mean

0 uanaara
Error

Q 1
O 1

I- 1 U J U 4~ J ~c~ i

1 n 4 n T *
1 u 4 . U J

7 CO

z . b z

0 0

IT /I "3 Q_ 1 ^_ _ T _ 0

1 f> 1 Q n *
1 u 1 . y u

n on

r 4DDZZ

1 n 1 "3 n *
lUl . oU

1 C Q

1 . b 0

1 Q

/I "3 Q_ 0_ ■3_ T_ 1

r 4jy—

inn Q c *
lUU . Ob''

1 CO

1 . by

D J

17 c: 0 Qn_ 4 _ 1 _ 0
r Dzyts— 4~l~Z

Q 0 "3 *

0 CO

z . b z

D

r 4 1 D Z

Q Q 1 "3 *

1 11
i . 1 i

1 7

Q 7 0 7 *

y / . 0 /

0 n c
2.0b

>1 "3 Q_ 1 '7_ 0_ 1 1 "3

r 4oy— 1 /— Z— i— i— J

Q 7 7 7 *

y / . / z'^

1 no
1.02

A 0
4 ^

r DU4A— ^— i— i— i

Q 7 A C "k

y / . 4b''

0 f\ c

2.0b

Q 0

Pearl White Spanish

y b . b 1

0 c n
2 . bO

Q c;

y D

vax ija oUo — 1 — i

C 11

y 0 . 2 1

1.76

J U

r 4D ytJ— J — Z — 4 — D — z — z

Q C 0 Q

y D . 0 y

n 0 c
0 . Ob

A "7

r Diy— 4— i— 1— i— J— z— B

Q C CO

yb . DO

1 on

i . by

O 4

^"312^ — 7 — 4_T3

yb . D J

0 CO

2.52

r 4oy— lb— iU— i— i

n c 0 fi

y5 . 3 y

2.49

4 1

V RniB_io_i_i 1 "3 1 Q Kin
r D U lA— 1 z— 1— 1— 1— J— 1— o— D 1 U

Q c on
y o . Z (J

O D

Florunner

n >i 0 T
y 4 . 37

0.88

Q Q
0 O

Jreari i^ariy Kunner

y 4 . 3b

2.04

£. J.

1? 4 "3 Q_ 1 <^ _ /I _ Q 1 no

r 4 J y ~ 1 D — 4 — y — 1 — rJ z

y 3 . bb

1.76

"3 1

T-1 / r QD '3'3>1ir'31 Irj

r 4Dyii— J — z — 4 — b — J — 1 — 1— B

no 10

y3 . Iz

1.37

z u

1? 4 "3 Q— 1 ^ — 1 — 1 — '3_ 0_ 1

r 4 J y — 1 D 1 1 j~ z~ 1

no on

yz . by

2,49

T71 Ana 1 1 c 1

r 4/b 1— 1— D— 1

y 1 . y 0

1.76

0 R
O

T? 4I^^_Q — 0*3 Q "3 "3 1 DO

r 4D4— 0—/ J— y—j— J— 1—B J

y i . b y

2 • 0 J

1 fl
1 O

4 "3 _ 0 _ "3 _ 1 n n
r 4 0 D— z— J— 1 — B— B

n 1 00++
y 1 . 2a**

1 . 33

4 U

■p 4 Q n — 0 — 1 _ 1 _ 0 _ 1 _ 1 0 n
r 4 y U— Z— 1 — 1— Z— 1— 1— Z— B

n 1 on**

yi . 20**

2.05

0 3

r longiant:

n 1 no**

y i . 03**

1.23

1 n
± U

17 >107T3 0 1 7 A

r 4z/B— J— 1— /— 4

n n n "7 * *

yo . y /**

1.78

1 C
J. 3

r 4Z /X3 v~D— rS4

yo . 71**

2 . 06

17

F 427B-R-3-1-1-B-64

90.41**

2.49

14

F 427B-V-4-73

n n 0 ^ * *
y 0 • 3b**

2.54

45

F 519-3-1-2-1-B

89.87**

2.05

7

F 420-100-2-4-1-1-4

89.85**

1.33

83

OT Early Bunch

89.71**

2.53

16

F 427B-V-11-B

88.26**

1. 78

49

F 520B-VAR-10-2-B

88.03**

2.52

5

F 393-9-5-4-2-1

87.17**

1.44

4

F 393-7-1

87.09**

1.44

87

NC-FLA 14

86.87**

2.05

3

F 393-6-3-2-2

84.87**

1.44

94

Storers Jumbo

84.11**

2.50

*Best group of genotypes for desirable maximum values (P<. 05)
**Best group of genotypes for desirable minimum values (P<.05)

65

Table 6. Continued.

Oil Percentage

Laboratory Number and Least Square Standard
Genotype Mean Error

1 o

18

F

435-2-3-1-B-B

52. 87*

0. 67

88

Pearl Early Runner

52 . 65*

0.83

3

F

393-6-3-2-2

52. 47*

0.67

87

NC-FLA 14

51 . 85*

1 . 00

6

F

416-2

51.84*

0.54

19

F

439-2-3-2-1

51. 76*

0 .83

O O

83

OT Early Bunch

51 .36*

1.01

20

F

439-16-1-1-3-2-1

51.34*

0. 99

40

F

490-2-1-1-2-1-1-2-B

51.20*

1.00

-7

7

F

420-100-2-4-1-1-4

51.07*

0.67

23

F

439-16-10-1-1

50 .99*

0 . 99

c

b

F

393-9-5-4-2-1

50.91*

0 . 67

41

F

501A-12-l-l-l-3-l-8-bl0

50 . 80*

1.00

33

F

476-1-1-5-1

50 . 72*

0 . 73

21

F

439-16-4-9-1-B2

50.68*

0.83

42

F

504A-2-1-1-1

50.62*

1 . 20

4

F

393-7-1

50. 57*

0.63

2 o

F

454-8-23-9-3-3-1-B3

50 .54*

0 . 99

4 /

F

519-4-1-1-1-3-2-B

50 . 55*

1.39

30

F

459B-3-2-4-6-2-2

50.53*

0.57

1 0

F

427B-3-1-7-4

50 . 49*

0.74

15

F

427B-V-5-B4

50. 40*

1.00

86

Florunner

50. 25*

0.49

24

F

439-17-2-1-1-3

50 . 24*

0 . 60

85

Florigiant

50.23*

0.62

F

439-16-6-3-2

50.03*

0 . 54

45

F

519-3-1-2-1-B

49. 85*

1,00

95

Val Ga 803-1-1

49.79*

0.99

17

F

427B-R-3-1-1-B-64

49.75*

1.38

31

F

459B-3-2-4-6-3-1-1-B

49. 20**

0.76

37

F

487A-7-10-2-B2

49.15**

1.00

92

Pearl White Spanish

48.82**

1.00

81

C10302A-4-3-B-1

48, 75**

1.39

29

F

455-2-2

48.47**

0.74

49

F

520B-VAR-10-2-B

48, 15**

1.39

94

Storers Jumbo

47,97**

1.00

16

F

427B-V-11-B

47.30**

1.00

54

F

531A-7-4-B

46. 75**

1.22

53

F

529B-4-1-2

45.85**

1.39

*Best group of genotypes for desirable maximum values {P<.05)
**Best group of genotypes for desirable minimum values (P<.05)

66

value, oil percentage and fatty acid composition were not
clearly separated among the three maturity groups of peanuts
or among the four commercial types. It is difficult to
determine specific group relationships among the genotypes
involved in this study based only on the chemical
characteristics observed. This is expected in view of the
fact that most of the genotypes are crosses between
different commercial types and also different maturity
groups .

Norden and Block (1968) pointed out that peanut
varieties derived from crosses between market types do not
necessarily conform in chemical composition to the parental
varieties. The authors commented that it is possible to
obtain from a cross between Spanish and Virginia types, for
example, a Virginia type variety that has oil with a
chemical composition similar to that commonly found in
Spanish peanuts, as evidenced with the F 416-1 genotype.

Even though the combined results of 40 genotypes showed
random distribution of the studied variables, the genotypes
were subdivided in maturity groups and commercial types, and
analyzed separately to investigate possible trends of
maturity group and market type means. Mean square values,
levels of significance, and coefficients of variation are
presented in Table 7 for the different maturity groups and
in Table 8 for the different commercial types. The
statistical analysis of the late maturity group was
compromised due to the small number of degrees of freedom

67

Table 7. Mean Squares from the Analysis of Variance, and
Coefficients of Variation (C.V.) of Fatty Acids,
Iodine Value and Oil Percentage for the Different
Maturity Groups .

Early

Palmitic Stearic Oleic Linoleic Eicosenoic
Source df C16 C18 C18:l C18:l C20:l

Model 13 10.1416** 1.1813**

Year 8 5.6573* 1.3553**

Genotype 5 4.4297 1.3117*

Error 29 2.3058 0.4150

C.V. 10.6172 25.5538

65.0831** 71.6441** 0.6385**

30.4708** 80.8814** 0.5303**

89.7300** 67.7961** 0.0827

7.3554 14.0079 0.05762

5.6332 13.0292 16.8926

Arachidic Behenic Lignoceric Iodine
Source df C20 C22 C24 Value

Model

13

0.

6227**

2.

2636*

0.

3445*

110.

8570**

Year

8

0.

8299**

2.

1740*

0.

4517*

161.

7193**

Genotype

5

0.

0653

1.

9183

0.

1604

45.

2029

Error

29

0.

0388

0.

9146

0.

1489

20.

3151

C.V.

16.

9403

35.

1486

38.

9489

4.

8672

Source

df

Oil

Model

10

5.

3404

Year

5

2.

3741

Genotype

5

8.

4310**

Error

14

1.

5924

C.V.

2.

4774

Continued

68

Table 7. Continued

Medium

Palmitic Stearic Oleic Linoleic Iodine

Source df C16 C18 C18;l C18; 2 Value

Model 32 15.8124** 2.5213** 303.1563** 249.8823** 196.4835**

Year 9 5.1718** 4.6093** 18.6635* 39.9102** 116.5958**

Genotype 23 14.9440** 1.3598** 365.6451** 280.9813** 159.5777**

Error 112 1.0035 0.3099 8.5184 7.6133 8.1633

C.V. 8.9244 23.1014 5.6531 9.7627 2.9863

Arachidic Eicosenoic Behenic Lignoceric
Source df C20 C20:l C22 C24

Model

32

0.

.4338**

0,

. 3406**

0.

.9497**

0.

.9617**

Year

9

1.

,1950**

0.

.5239**

2.

,2196**

2.

,0662**

Genotype

23

0.

,1024

0,

.1460*

0.

,3194

0.

,2410**

Error

104

0.

, 1402

0.

,0801

0.

, 3037

0.

, 1078

C.V.

29.

,8747

21.

, 5627

20.

,6292

28.

,4992

Source

df

Oil

Model

29 6.0181**

Year 6
Genotype 23
Error 68

8.4342**
4. 1388**
1.9144

C.V.

2.7319

Continued

69

Table 7 . Continued

Late

Source

Palmitic
df C16

Stearic
C18

Oleic
C18: 1

Linoleic
C18:l

Eicosenoic
C20:l

Model
Year

Genotype
Error

13 2.3236** 0.6268 26.9579 17.4222** 0.2768

7 2.2147* 0.5101 4.7625 4.2476 0.1367

6 0.6967 0.1736 38.7355* 20.0541** 0.1606

7 0.2855 0.8633 9.0029 2.2772 0.0803

C.V.

5.8814 38.8140 4.8022 7.4688 21.7959

Arachidic Behenic Lignoceric Iodine
Source df C20 C22 C24 Value

Model

13

0.

2118

0.

4686

0.

4090

26.

7718**

Year

7

0.

3396

0.

3764

0.

6528*

15.

6357*

Genotype

6

0.

0522

0.

1900

0.

1246

15.

0194*

Error

7

0.

1406

1.

1267

0.

1328

3.

7095

C.V.

31.

4993

48.

0401

37.

7031

2.

1165

Source

df

Oil

Model

9

3.

8760

Year

4

1.

6875

Genotype

5

5.

1432

Error

5

1.

0545

C.V.

2.

0562

*Significant at 0.05 level.
**Signif icant at 0.01 level.

70

Table 8. Mean Squares from the Analysis of Variance and

Coefficients of Variation (C.V.) of Fatty Acids,
Iodine Value and Oil Percentage for the Different
Commercial Types.

Virginia

Palmitic Stearic Oleic Linoleic Iodine

Source df C16 C18 C18; 1 CIS; 2 Value

Model 26 32.7609** 1.8425** 296.2385** 194.4269** 142.0117**

Year 9 6.2540** 2.5892** 32.9050** 67.8218** 152.2305**

Genotype 17 24.8177** 1.2318** 404.4248** 272.8478** 127.5048**

Error 73 1.3705 0.3850 8.5615 11.4390 14.9991

C.V. 10.2735 23.1912 5.3545 13.5292 4.1978

Arachidic Eicosenoic Behenic Lignoceric
Source df C20 C20:l C22 C24

Model

26

0,

.5809**

0,

,4653**

0.

,9374

0,

.6586**

Year

9

1.

, 4011**

0.

,5112**

1.

,4984*

1.

,3112**

Genotype

17

0.

. 1604

0.

, 1612*

0.

,4789

0.

.2318

Error

66

0.

. 1582

0.

,0839

0.

,6872

0.

, 1598

C.V.

32.

,5298

20.

,8132

32,

,3124

40.

. 1003

Source

df

Oil

Model 21
Year 5
Genotype 16

Error 49

7.0393**
7.8737**
6279**
9059

6,
1,

C.V.

2. 7261

Continued

71

Table 8. Continued.

Runner

Source

df

Palmitic
C16

Stearic
C18

Oleic
CIS: 1

Linoleic
CIS: 2

Iodine
Value

Model 24 9.6687** 1.2812**187.5219**155.0354**106.8266**

Year 9 5.3361** 2.6830* 13.4144 25.2334** 73.5654**

Genotype 15 9.0719** 0.4165 235.4717**172.5665** 97.2179**

Error 71 0.9907 0.3337 8.4285 7.1857 7.5197

C.V.

8.5352 26.8933

5.8190

8. 9619

2. 8237

• Arachidic Eicosenoic Behenic Lignoceric
Source df C20 C2 0 : 1 C22 C24

Model

24

0.

. 2704**

0.

.2488**

0,

. 8994**

0,

. 8530**

Year

9

0.

, 4840**

0.

,3452**

1.

.3064**

1.

.4419**

Genotype

15

0.

.0354

0,

,0616

0.

.2973

0.

. 1873**

Error

70

0.

,0530

0.

, 0638

0,

,2671

0.

, 0736

C.V.

18.

,7185

19.

, 6548

19.

, 5930

22.

, 7132

Source

df

Oil

Model
Year

Genotype
Error

21
6
15
36

5

9,
2,
0,

0389**
0703**
8734**
9709

C.V.

1.9506

Continued

72

Table 8. Continued.

Spanish

Source

df

Palmitic
C16

Stearic
C18

Oleic
CIS: 1

Linoleic
C18: 2

Iodine
Value

Model
Year

Genotype
Error

7
6
1
1

0.9596
1. 1177
0. 2025
0.4225

1875
0031

0. 4900

21.6171*
3. 6495

32.6922
8.7745

40. 8889**
27.0357**

6100 115.5625** 79.2100* 25.0000**

0.0225

0 . 4900

0.0001

C.V.

4.9118 24.5136

0.3065

2. 4287

0.0000

Arachidic Eicosenoic Behenic Lignoceric
Source df C20 C20:l C22 C24

Model

7

0.

4539

0.

5917

2.

2413

0.

3679**

Year

6

0.

5196

0.

3767

2.

0090

0.

4081**

Genotype

1

0.

0225

0.

1600

0.

0900

0.

0001

Error

1

0.

0625

0.

0400

0.

1600

0.

0001

C.V.

22.

7273

17.

3077

14.

3426

0.

0000

Source df Oil

Mode 1
Year

Genotype
Error

7 7.5144*
6 0.9315*

1 14.0625**
1 0.0025

0.0968

*Signif leant at 0.05 level.
**Signif icant at 0.01 level.

73

for the error term. The same is true for the Spanish
commercial type. No statistical analysis could be done in
the Valencia type since only one genotype was tested.

Significant differences among genotypes were observed
in the early maturity groups for stearic (P < 0.05), oleic
and linoleic acids and for oil content (P < 0.01). Yearly
differences were statistically significant for all variables
except oil percentage. Coefficients of variation were low
for oil, iodine value and oleic acid, and high for stearic,
behenic and lignoceric acids. Coefficients of variation
were medium for palmitic, linoleic, eicosenoic and arachidic
acids .

Medium maturity group genotype effects were significant
for all variables, except arachidic and behenic acids. Year
effects were significant for all variables analyzed. The
same trends among coefficients of variation found in the
earlier types were found in this group, although lower
values were observed for all responses.

Significant differences were found among the genotypes
of the late maturity group for the variables oleic and
linoleic acids and iodine value. Significant year effects
were detected only for palmitic and lignoceric acids and
iodine value. Coefficients of variation were smaller than
those for the early and medium groups for palmitic, oleic
and linoleic acids, as well as iodine value and oil
percentage. Very high coefficients of variation were found
for stearic, arachidic, behenic and lignoceric fatty acids.

74

Table 9 presents the means of all the variables for
maturity groups and commercial types. Although not
statistically analyzed, early maturity genotypes seem to
have larger percentages of palmitic, stearic, eicosenoic and
behenic acids and oil contents in comparison with the medium
and late maturity groups. The amount of palmitic acid, for
example, was 27.42% larger than for the medium maturity
group, and 57.42% higher than the late maturity group. The
increase in oil content was only 0.57% in relation to the
medium group, and 1.99% larger than the late genotypes.

Late maturing genotypes had a larger amount of oleic
acid and less linoleic acid than the early and medium
maturity groups. Oleic acid was 29.78% larger than the
early maturing genotypes, and 21.02% larger than the medium
maturity genotypes. On the other hand, linoleic acid, in
the same group, was 29.66% less than the early maturity
group, and 28.51% less than the medium maturing genotypes.
Due to this inverse relationship, the iodine value of the
late maturing genotypes was considerably lower than that
found for the two other maturity groups: 1.73% less than
the earlier genotypes, and 4.89% less than the medium
maturing genotypes. These findings are in agreement with
the results reported by Worthington and coworkers (1972) .
They pointed out that the late maturing large seeded
varieties, most of them from the Virginia type, were higher
in oleic and lower in linoleic than the earlier maturing
types .

75

Table 9. Mean Oil Composition of Peanut Genotypes for the
Different Maturity Groups and Commercial Types.

Maturity Group

Variables Early Medium Late

Palmitic

14.

30

11,

.22

9.

,09

Stearic

2.

52

2.

.41

2.

,46

Oleic

48.

14

51.

.63

62.

.48

Linoleic

28.

73

28.

,26

20.

,20

Arachidic

1.

16

1.

.25

1.

,19

Eicosenoic

1.

42

1.

,31

1.

.30

Behenic

2.

72

2.

,67

2.

,21

Lignoceric

0.

99

1.

, 15

0.

,97

Iodine Value

92.

60

95.

,68

91.

,00

Oil Content

50.

94

50.

,65

49.

,94

Commercial Type

Variables

Virq

inia

Runner

Spanish

Valencia

Palmitic

11.

40

11.

66

13.

23

13.

83

Stearic

2.

66

2.

15

2.

86

2.

76

Oleic

54.

65

49.

89

48.

94

43.

45

Linoleic

25.

00

29.

91

28.

82

31.

70

Arachidic

1.

22

1.

23

1.

10

1.

58

Eicosenoic

1.

39

1.

29

1.

16

1.

58

Behenic

2.

57

2.

64

2.

79

3.

78

Lignoceric

1.

00

1.

19

1.

02

1.

33

Iodine Value

92.

26

97.

11

93.

56

93.

75

Oil Content

50.

64

50.

51

51.

63

49.

50

76

Analysis of variance of commercial types showed large
genotype effects, especially for oleic and linoleic acids,
while year effects were more pronounced in the minor fatty
acids (C18, C20, C20:l, C22 and C24) . Year effects on oil
percentage were highly evident on Runner and Virginia type
peanuts, but very small year effects were found in the
Spanish genotypes.

As evidenced in Table 9, although not statistically
analyzed, the Spanish and Valencia commercial types appear
to have higher amounts of palmitic, stearic and behenic
acids in relation to the others. Linoleic acid contents
were larger in Valencia type peanuts in comparison to the
other types (5.98 to 26.81% higher). On the other hand,
oleic acid was comparatively lower (11.23 to 20.49% lower).
Worthington and Holley (1967) reported similar variation
among the commercial types.

Oil percentage showed small variation among the
different market types as well as among the different
maturity groups.

Iodine values were especially high for the Runner
genotypes in comparison with all others. These results
contradict findings by Pickett and Holley (1951) and Fore et
al. (1953) . Those authors pointed out that oils from Runner
genotypes contained less linoleic acid and had higher
stabilities than oils from Spanish or Virginia market types.
The major reason for the difference in results seems to be
the different genetic background of the genotypes used by

77

those authors in comparison with the ones investigated in
this study. Another possible explanation for the results
found could be related to maturity of the peanut seeds.
Young et al. (1972b) and Sanders (1980b) reported that oleic
acid content increased with maturity, while linoleic acid
decreased in mature peanut seeds. Although early genotypes
were harvested 7 to 12 days in advance to the other
genotypes, all harvesting was complete after 125 to 130 days
(Table 2). Thus, Runner genotypes, generally of medium late
(131 to 140 days) to late maturing (141 to 150 days) cycles,
appear to be harvested in this study before complete
maturation, which could be responsible for the high iodine
value found.

Virginia genotypes had larger amounts of oleic acid
(9.54 to 25.78% more) and lower amounts of linoleic acid
(13.25 to 21.14% less) in comparison to the other market

types. Similar results were found in an earlier paper
(Jamieson et al. , 1921) and were confirmed by others
(Pickett and Holley, 1951; Fore et al. , 1953; Freeman et

al. , 1954).

Although the subdivision of the data in maturity groups
or commercial types does not fit for all genotypes, general
trends, like the ones pointed out, are still visible within
groups. As the time passes, distinction of maturity groups
and market types based on chemical characteristics of the
seeds will be less evident due to the complete intercross

78

compatibility of the four market types and the three
maturity groups. Evidences that this is already occurring
can be found in a recent bulletin (Mozingo et al. , 1982) ,
where no trends in oil composition among market types or
maturity groups could be detected, especially among the
newer genotypes.

The previously described modified Gupta's test was used
for variables that were statistically significant by the F
test. Table 10 shows the least square means, standard
errors and genotype grouping for the different maturity
groups. The same information is presented in Table 11 for
the three commercial types. No test was applied for
Valencia type, since there was only one genotype.

Based on the approximate statistical test, the best
genotype from the industrial standpoint in the early
maturity group is OT Early Bunch. A late maturing genotype
with good industrial quality is Storers Jumbo. Medium
maturity genotypes with a higher level of saturation include
lines derived from F 393 (including NC-FLA 14) and
F 420-100-2-4-1-1-4.

The best genotypes from the nutritional standpoint are
Pearl White Spanish, Val Ga 803-1-1 and genotypes derived
from F 459B, for the early maturity group. Best late
maturing genotypes include genotypes derived from F 427B and
F 476-1-1-5-1. Genotypes F 439-2-3-2-1, F439-1 6-6-3-2 ,
C10302A-1-2-4-5-B, F 416-2 and F 455-2-2 in the medium

79

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92

maturity group can be considered superior in nutritional oil
qualities .

Within the commercial types, the best genotypes in
relation to industrial quality are Florigiant,
F 490-2-1-1-2-1-1-2-B, genotypes derived from F 427B, OT
Early Bunch, genotypes derived from F 393 (including
NC-FLA 14) and Storers Jumbo (Virginia types) . In the
Runner types the best group of genotypes include
F 520B-VAR-10-2-B, F 519-3-1-2-1-B, F 420-100-2-4-1-1-4 and
F 427B-R-3-1-1-B-64.

The best genotypes from the dietary standpoint are
F 544-2-2, F 459B-3-2-4-6-2-2 and F 416-2 in the Virginia
group. Runner genotypes considered nutritionally best
include F 439-2-3-2-1, F 439-16-6-3-2 and F 519-3-1-2-1-B.

F 435-2-3-1-B-B, a Spanish genotype, is better for
industrial quality than Pearl White Spanish. This last one
is consequently better than the former from a dietary
standpoint.

The results presented here indicated that in each of
the three principal commercial types (Virginia, Runner and
Spanish) there is high variability in relation to fatty acid
composition, iodine value and oil percentage. It should be
possible to select from each group, genotypes that best suit
industrial or dietary qualities. Breeding programs need not
be restricted to just one type, since every commercial type
presented enough variability to select for desirable
chemical characteristics. The same is true when comparing

93

the best genotypes in the different maturity groups. Khan .!
and coworkers (1974) found a similar pattern of variation
among commercial types when studying fatty acid composition
of segregating populations derived from inf raspecif ic peanut
crosses .

Subdivided and combined data, in general, showed highly
significant year effects. Seasonal variation has been
extensively reported (Eheart et a_l. , 1955; Holley and
Hammons, 1968; Worthington et al, , 1972; Tai, 1972) and has
been related, at least in part, to temperature and moisture
conditions. Attempts to find significant relationships
between these parameters have generally failed, mainly due
to the indeterminate growth habit of the species and the
underground fruit formation and development.

In order to investigate possible associations of
temperature, rainfall and the yearly variation of fatty acid
composition, iodine value and oil content, correlation
coefficients were calculated involving these variables and
climatic parameters during the period of pegging formation
until harvest.

Correlation coefficients were calculated for the
combined data, and later among different maturity groups and
commercial types. Results and levels of significance are
presented in Tables 12, 13 and 14. The true numbers of
observations are less than the ones reported, in view of the
fact that the year-temperature-rainfall axis has the same
value for all genotypes. Thus, correlation coefficients are

i

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Iodine value showed negative correlation coefficients
with maximum air and soil temperatures, and also with
average air temperature for the combined data. Maximum air
and soil temperatures also presented good associations with
iodine value for the different maturity groups and
commercial types. Late genotypes showed no significant
correlation coefficients involving climatic parameters and
iodine value. Early maturing genotypes presented a
statistically significant association of iodine value only
with maximum air temperature.

The negative correlation coefficients found for iodine
value and temperature parameters seem to indicate that as
the air and soil temperatures increased the iodine values of
the genotypes decreased. Thus, peanut varieties grown in
cooler regions might be expected to have higher iodine
values than when grown in warmer climates. Indications that
this in fact occurs are provided in a recent bulletin by
Mozingo et al. (1982) . The authors reported higher iodine
values for Florigiant and UF 75102 (F 519) genotypes, grown
in Virginia and North Carolina in comparison with the
results reported here. Moreover, in data involving two
locations, a higher iodine value is reported for all
genotypes in the cooler location (Virginia) than in the
warmer region (North Carolina) . Two-year data also show
significant differences for all genotypes in oil
composition. The 1981 crop had always higher iodine values
than the 1980 crop. The only climatic parameter given was

103

rainfall, thus no comparisons of the results based on
temperature differences were possible.

Oil percentage showed negative correlations with
minimum air temperature, maximum and minimum soil
temperatures and average air temperature for the combined
data. Subdivision of the genotypes indicates negative
correlations between oil and some of the mentioned
parameters. No correlation involving oil content was
significant for the late maturing genotypes.

The negative correlation coefficients found for oil
percentage appear to indicate that higher temperatures from
pegging until harvest (especially maximum and minimum soil
temperatures) should result in genotypes with less oil
content than the ones under cooler temperatures during the
same period. These findings are in agreement with Mozingo
et al. (1982), who reported that Florigiant, Keel 29 and
NC 17941 genotypes grown in North Carolina had less oil than
when grown in Virginia.

Oleic and linoleic acids, in general, did not show any
significant correlation with climatic parameters, except in
the early maturity genotypes, where oleic was positively
correlated with average soil temperature, while linoleic
showed a negative correlation with maximum air temperature.

Cumulative rainfall showed significant negative
associations with the minor fatty acids, C18, C20, C20:l,
C22 and C24. No significant correlations of rainfall with
iodine value and oil percentage were found.

104

The subdivision of the data by commercial type showed a
similar pattern of association among climatic parameters and
oil composition components.

Stearic acid (C18) had a consistent, statistically
significant, positive correlation with average soil
temperature, although for all other temperature parameters
significant negative values were found. No explanation
could be found for this phenomenon in the literature
(Kirschenbauer , 1960; Hilditch and Williams, 1964;
Applequist, 1975; and Robinson, 1980) .

All other statistically significant correlation
coefficients presented in Tables 12, 13 and 14 are negative,
appearing to indicate that increases in temperature are
associated with decreases in fatty acids, oil content and
iodine value. Eicosenoic acid (C20:l) seemed to be
particularly associated with temperature and rainfall
parameters. From the results presented here it might be
inferred that altering planting dates within a region could
alter the chemical composition of peanut genotypes.

Correlations among fatty acids were also calculated to
measure the degree of association among oil components.
Values and levels of significance are presented in Table 15.
A highly significant (P < .01) negative association between
oleic and linoleic acid was found. Several authors have
reported the same association (Holley and Hammons, 1968;
Worthington and Hammons, 1971; Khan et al. , 19 74; Sekhon et
al., 1980).

105

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1

Considering the other fatty acids, results showed that
there was a significant positive correlation involving
palmitic and linoleic acids, while linoleic had significant
negative correlations with arachidic and eicosenoic acids.
Behenic was positively associated with arachidic and
eicosenoic, while lignoceric acid did not show any
meaningful association with the other oil components.

Iodine value presented a strong positive correlation
with linoleic acid, and a negative (P < .05) association
with arachidic acid.

Oil percentage was positively associated with stearic
and negatively associated with eicosenoic acid.

Selection for lower levels of linoleic acid, to
increase the stability and shelf -life of peanut products,
might be expected to result in a lower level of palmitic
acid and a higher level of oleic acid. An increase in the
amounts of arachidic and eicosenoic acid might also occur
due to the negative association involving these parameters.
Selection of low linoleic genotypes could result in
genotypes with lower iodine values due to the strong
positive association between these variables.

Selection of genotypes with higher levels of
unsaturation could result in an increase in the amounts of
palmitic acid and in a decrease in the arachidic and
eicosenoic acids contents.

SUMMARY AND CONCLUSIONS

A hundred genotypes from the Peanut Breeding Project of
the University of Florida were chemically analyzed for oil
content, fatty acid composition and iodine value during a
ten-year period. Genotypes involved in this study included
early, medium and late maturing lines, as well as Virginia,
Runner, Spanish and Valencia market types.

The results show that peanut oil is comprised primarily
of oleic, linoleic and palmitic acids, with the first two
accounting for about 80% of the total.

Means of the hundred genotypes over the years under
study show an impressive variation in fatty acid
composition, iodine value and oil percentage. Oil
composition among the genotypes varied as follows: palmitic
6.90 to 17.50%; stearic 1.55 to 5.00%; oleic 40.60 to
73.50%; linoleic 8.60 to 39.15%; arachidic 0.10 to 2.00%;
eicosenoic 0.20 to 2.50%; behenic 0.40 to 5.10%; and
lignoceric traces to 3.80%. Iodine value varied from 75 to
105, while oil percentage ranged from 46.2 to 53.4%. The
magnitude of this diversity should permit, through selection
and hybridization, the development of new varieties with
improved chemical qualities.

107

108

i

Based on dietary and industrial qualities, the best
group of genotype means, relative to oil composition,
included members of all the three maturity groups (early,
medium and late) , as well as of the four market types
(Virginia, Runner, Spanish and Valencia) .

The subdivision of the data by maturity and market type
showed that, as a group, early maturity genotypes had larger
percentages of palmitic, stearic, eicosenoic an behenic
acids and oil content compared with genotypes in the medium
and late maturity groups; whereas late maturing genotypes
had larger percentages of oleic acid and less linoleic acid
than the two other groups. However, relatively high levels
of genetic variability for oil composition could be found
within each group. The same is true when comparing the
different market types. Although Spanish and Valencia types
presented higher amounts of palmitic, stearic and behenic
acids compared with Virginia and Runner types, a rather
large range of these components was found in each group. It
is difficult to assign specific group relationships among
the genotypes involved in this study based only on the
chemical characteristics observed. The large variation in
oil composition found within each group indicates that it
should be possible to select varieties that best suit
industrial or dietary qualities in each maturity group
and/or market type.

109

Subdivided and combined data generally showed a
significant year effect. Eicosenoic, a minor fatty acid,
seems to be particularly affected by climatic variations.

The negative correlation coefficients found for iodine
value and temperature appear to indicate that as air and
soil temperatures increased the iodine number of the
genotypes showed lower values. Oil percentage also showed
negative correlations with air and soil temperatures. The
negative associations found between oil percentage and
temperature suggest that higher temperatures during pod and
seed formation would lower the oil content.

As a rule, no significant correlations among oleic
acid, linoleic acid and climatic parameters were found.

Minor fatty acids seem to be affected by moisture
conditions. Significant negative associations were found
involving minor fatty acids and cumulative rainfall. No
significant correlations were found between iodine value or
oil percentage and cumulative rainfall.

The significant iodine value association with maximum
air and soil temperatures is of considerable importance, and
might help explain the poorer industrial quality of oils
from cooler locations. Based on this association it might
be inferred that earlier or delayed plantings could be used
to alter the chemical composition of peanut genotypes within
a given location.

Correlation coefficients among oil components suggest
that selection for lower levels of linoleic acid, to improve I

I

110

peanut shelf-life, could result in a decrease in the amount
of palmitic acid and an increase in the oleic acid
percentage. A corresponding increase in arachidic and
eicosenoic acid might also occur due to the negative
association between linoleic acid and these variables.

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BIOGRAPHICAL SKETCH

Marilene L.A. Bovi was born to Miguel and Olivia Leao
on May 22, 1948. In her precollege years, she lived in Sao
Paulo (SP) , Brasil.

In 1968, she enrolled in the Escola Superior de Agri-
cultura "Luiz de Queiroz" (Piracicaba, SP, Brasil) , from
which she received her B.S. degree as Engenheiro Agronomo
in 1972.

After graduation, Mrs. Bovi joined the Instituto
Agronomico de Campinas (SP, Brasil) to work as a plant
breeder on perennial tropical plants research. In the fall
of 1978, she enrolled in the Graduate School of the
University of Florida, in the Agronomy Department, and
received her Master of Science degree in August of 1980.
Since then she has been working toward her Doctor of
Philosophy degree.

119

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.

A.J7 'Norden, Chairman
Pris/fessor of Agronomy

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.

E.S. Horner
Professor of Agronomy

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.

D.W. Corbet

Associate Professor of
Agronomy

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.

F.G. Martin

Associate Professor of
Statistics

I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality,
as a dissertation for the degree of Doctor of Philosophy.

P.M. Lyrehe
Associate Professor of
Horticultural Science

This dissertation was submitted to the Graduate Faculty of
the College of Agriculture and to the Graduate Council, and
was accepted as partial fulfillment of the requirements for
the degree of Doctor of Philosophy.

December 1982

Dean for Graduate Studies and
Research