Peanut quality

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Peanut quality its assurance and maintenance from the farm to end-product
Series Title:
Bulletin Agricultural Experiment Stations, University of Florida
Ahmed, E. M ( Esam M )
Pattee, Harold E
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Gainesville Fla
Agricultural Experiment Stations, Institute of Food and Agricultural Sciences, University of Florida
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94 p. : ill. ; 23 cm.


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Peanuts -- Quality ( lcsh )
City of Gainesville ( local )
Peanuts ( jstor )
Flavors ( jstor )
Aflatoxins ( jstor )
bibliography ( marcgt )
non-fiction ( marcgt )


Bibliography: p. 91-94.
General Note:
"July 1987."
Bulletin (University of Florida. Agricultural Experiment Station) ;
Statement of Responsibility:
Esam M. Ahmed and Harold E. Pattee, editors.

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7July 1987
- '

Its Assurance and Maintenance
from the Farm to End-Product

Esam M. Ahmed and Harold E. Pattee, editors

Agricultural Experiment Station
Institute of Food and Agricultural Sciences
University of Florida, Gainesville
J. M. Davidson, Dean for Research

Bulletin 874 (technical)
| | i i

Its Assurance and Maintenance
from the Farm to End-Product

Esam M. Ahmed and Harold E. Pattee, editors

Agricultural Experiment Stations
Institute of Food and Agricultural Sciences
University of Florida, Gainesville


Ahmed, Esam M., Professor, Department of Food Science and
Human Nutrition, IFAS, University of Florida, Gainesville,
Florida 32611

Blankenship, Paul D., Agricultural Engineer, National Peanut
Research Laboratory, Agricultural Research Service, U.S.
Department of Agriculture, Dawson, Georgia 31742

Dickens, James W., Research Leader, Market Quality and Handling,
Agricultural Research Service, U.S. Department of Agriculture,
North Carolina State University, Raleigh, North Carolina

Fletcher, Michelle M., Research Associate, Nabisco Brands Inc.,
P.O. Box 1942, East Hanover, New Jersey 07936-1942

Grice, G. Max, Vice-President, Birdsong Peanut Company, P.O.
Box 698, Gorman, Texas 76454
Heinis, James J., Research Analyst, Department of Food Science,
North Carolina State University, Raleigh, North Carolina

Johnson, Ligon W., Assistant Chief, Fresh Products Branch,
Agricultural Marketing Service, U.S. Department of Agricul-
ture, Washington, DC 20250

McClure, William F., Professor, Department of Biological and
Agricultural Engineering, North Carolina State University,
Raleigh, North Carolina 27695-7625

Parker, Wilbur A., Vice-President, Seabrook Blanching Corporation,
P. O. Box 609, Edenton, North Carolina 27932

Pattee, Harold E., Research Chemist, Market Quality and Handling,
Agricultural Research Service, U.S. Department of Agriculture,
North Carolina State University, Raleigh, North Carolina

Ross, Douglas T., Manager, Private Label Marketing, Canada
Packers Inc., 30 St. Clair Avenue West, Toronto, Canada M4V

Sanders, Timothy H., Plant Physiologist, National Peanut Research
Laboratory, Agricultural Research Service, U.S. Department of
Agriculture, Dawson, Georgia 31742

Smith, John S., Jr., Agricultural Engineer, National Peanut Research
Laboratory, Agricultural Research Service, U.S. Department of
Agriculture, Dawson, Georgia 31742

Whitaker, Thomas B., Agricultural Engineer, Market Quality and
Handling, Agricultural Research Service, U.S. Department of
Agriculture, North Carolina State University, Raleigh, North
Carolina 27695-7625

Young, Clyde T., Professor, Department of Food Science, North
Carolina State University, Raleigh, North Carolina 27695-7624


Chapter 1.

Chapter 2.

Chapter 3.

Introduction to Peanut Quality . . .
H. E. Pattee and E. M. Ahmed

Peanut Quality: Effects of Amino Acids and
Carbohydrate Composition on Roasted Flavor
H. E. Pattee and C. T. Young

Measuring Peanut Maturity Using Near
Infrared Reflectance . . . .
T. B. Whitaker, H. E. Pattee, W. F. McClure,
and J. W. Dickens

Chapter 4. Peanut Quality in Curing and Storage. .
T. H. Sanders, P. D. Blankenship, and
J. S. Smith, Jr.

Chapter 5. Peanut Grading and Quality Evaluation.
J. W. Dickens and L. W. Johnson

Chapter 6. Shelling Edible Peanuts for Quality and
Marketability. ..............
G. M. Grice

Chapter 7. Peanut Blanching--Processing, Utilization
and Effects on Quality and Product
Shelf Life . . . .
W. A. Parker

Chapter 8. Peanut Quality: The Needs of
International Users . . .
D. T. Ross

Chapter 9. Evaluation of Peanut Flavor Quality .
M. M. Fletcher

Chapter 10. Peanut Processing in the United States:
Conventional Techniques . . .
J. J. Heinis and C. T. Young

Chapter 11. Peanut Quality and Non-Conventional
Processing of Peanut Seed . .
E. M. Ahmed

. 29


. .. 55

. .. 60

. 73

. 86

Introduction to Peanut Quality

Harold E. Pattee and Esam M. Ahmed

Peanut quality is a multifarious term, as evidenced by the
diversity of topics addressed in the chapters that follow this
Introduction. In general, when the term peanut quality is used, it
is referring to one of two broad subdivisions of quality. One sub-
division is economic quality, and this subdivision encompasses the
factors that have been defined to determine the monetary value of
peanuts. These economic quality factors are commonly known as
"grade factors". In general, when one sees the term "quality" in
the pre-1980's literature, it is most often referring to grade factor
terms. These grade factor terms have been well-defined, and ex-
cellent descriptions of their application are found in the succeeding

The second subdivision is sensory quality and is defined as the
summation of all physical and chemical characteristics of edible
peanut seed or their products that influence human senses and
bring about acceptability judgements by the consumer. Sensory
quality in any commodity is a fragile property. In peanuts the
importance of sensory quality tends to be subordinated to grade
factors, particularly after the moisture level is lowered below 10%.
This subordination of sensory quality maintenance arises, more than
anything else, from the previous lack of solid research results and
use of hearsay findings. However, solid research findings are now
available on proper curing, handling and storage. The research
results prior to 1980 related to peanut curing, handling and storage
have been summarized in the book Peanut Science and Technology
(Pattee and Young, 1982). Research on sensory quality of peanuts
through 1982 has been summarized by Pattee et al. (1985).

The lack of sensory quality information at the time grade
factors were initially being established most likely accounts for
only the composite terms--"rancidity, mold and decay" and "dirty
face splits" being used as sensory quality terms as a part of
establishing economic quality. Subsequent changes in the grade
factors of peanuts that have occurred since their establishment
have been due primarily to economic pressures resulting from

uncontrollable production factors; i.e., freeze damage, increased
awareness of mycotoxins, and buyer demand. Information on
sensory quality has been of only minor importance in prompting
these changes since, as already indicated, the information was
widely dispersed prior to 1980 and it is only since 1980 that our
information on sensory quality has been adequate enough to have
an impact on economic factors.

Of almost equal importance to quality maintenance by proper
curing, handling, and storage is the effect of maturity on quality.
The peanut provides a particular challenge with regard to maturity
because of its indeterminant reproduction. This indeterminant
reproduction trait generally causes a total range of maturity stages
to be present at harvest, and little is known about the relationship
of physiological maturity to acceptable sensory quality. Two
chapters in this publication provide insight into new research areas
which may permit us to better understand the relationship between
physiological maturity and acceptable flavor quality and may lead to
the development of quality evaluation tests which would enable us
to predict the potential quality of the product prior to product

Once the peanut crop is harvested and cured, its maximum
quality level, both economic and sensory, is established. The
challenge to the various segments of the peanut industry which
handle the peanut crop until it reaches its final disposition is one
of quality maintenance and prevention of quality deterioration.
Chapters on storage of farmers stock peanuts, shelling, and blanch-
ing of peanuts provide us with excellent overviews of efforts made
by these segments of the peanut industry to maintain quality.

Exportation of the U.S. peanut crop is a rapidly expanding
area, and the quality requirements and expectations of this segment
of the peanut industry have not heretofore been documented.
Whether peanuts are utilized within the United States or exported,
all peanut processors have a type of quality control program. The
American Peanut Research and Education Society in 1970 approved
the Critical Laboratory Evaluation of Roasted Peanuts (CLER)
Method for evaluating the quality of roasted peanuts (Holaday,
1970); however, an official version of the method has never been
published. The chapter on the revised CLER method represents the
first refereed publication of this method. The chapters on conven-
tional and non-conventional processing and utilization of peanuts
also present information which has heretofore been widely scattered
in the published literature or has not been published. The con-

solidation and publication of this information benefits all concerned
with peanut quality and increased edible consumption.

The goal of the entire U.S. peanut industry is to provide to its
end-users, the consumers, the very highest quality product possible.
The means by which peanut quality is maintained and evaluated
changes as the peanut passes from one segment of the peanut
industry to another on its route to the end-user. The changing
challenges for maintaining and evaluating peanut quality are not
always understood between the various segments of the peanut
industry. The succeeding chapters bring together a wide diversity
of information and represent the efforts of the American Peanut
Research and Education Society and its supporting organizations to
assist the peanut industry in its efforts to provide the consumer
with the very highest quality product possible.


Holaday, C. E. 1970. Report of the Peanut Quality Committee. J.
Amer. Peanut Res. and Educ. Assoc. 2:158.

Pattee, H. E. and C. T. Young. 1982. Peanut Science and Technol-
ogy. pp. 825. Amer. Peanut Res. and Educ. Soc., Yoakum, TX

Pattee, H. E., C. T. Young and C. Oupadissakoon. 1985. Peanut
quality: Effect of cultivar, growth, environment, and storage.
pp. 277-314. In H. E. Pattee (ed.), Evaluation of Quality of
Fruits and Vegetables. AVI Publishing Co., Inc., Westport, CT.

Peanut Quality: Effects of Amino Acid and
Carbohydrate Composition on Roasted Flavor

Harold E. Pattee and Clyde T. Young

In 1981 about 60% of the edible peanuts produced in the United
States were roasted (Agricultural Statistics, 1983). It is this
roasting process which converts the peanut kernel from its slightly
sweet, green "beany" flavor in the raw state to a flavor that is
delicate, uniquely nutty, and widely enjoyed. Research into the
origin of this delicate and uniquely nutty flavor for peanuts has
shown that amino acids, a peptide, and carbohydrates in an oil
medium are the precusors to roasted peanut flavor (Mason and Wal-
ler, 1964; Mason et al., 1969; Newell et al., 1967). Newell et al.
(1967) postulated that amino acids could be separated into those
associated with the production of typical roasted peanut flavor and
those associated with atypical or off-flavor roasted peanut flavor.
The amino acids associated with typical roasted peanut flavor were
aspartic acid, glutamic acid, glutamine, asparagine, histidine, and
phenylalanine, while those with atypical roasted flavor were thre-
onine, tyrosine, lysine, and an unidentified nitrogen-containing
compound. Cobb and Johnson (1973) in reviewing roasted peanut
flavor precursors listed threonine, tyrosine, lysine, and arginine
as precursors of atypical roasted flavor, thus suggesting the
replacement of the unidentified nitrogen-containing compound
with arginine. Their list for precursors of typical roasted flavor
was the same as that reported by Newell et al. (1967).

Oupadissakoon and co-workers (1980A,B) studied the effects of
geographical location, harvest time, and varieties on the contents
of individual amino acids of peanuts. They found significant
variations among amounts of amino acids due to differences in
varieties and location (Oupadissakoon et al., 1980B). In the second
study (Oupadissakoon et al., 1980A), location effects were sig-
nificant for many of the typical but not the atypical roasted flavor
precursors. At optimum harvesting time, they observed typical
roasted flavor precursors to be predominant comprising 64% of the
total free amino acids. Using seed size as an indicator of maturity,
Pattee et al. (1981A) showed high concentrations of the atypical
roasted flavor precursors in the immature seed size, 5.95 mm in
diameter, and suggested these high concentrations could contribute

to a potential poor quality in this seed size. Increase in seed size
from 5.95 to 7.14 mm resulted in a significant decrease in individual
amino acid fractions; however, the atypical roasted flavor precur-
sors, taken as a group, decreased more rapidly, 59.8% to 32.3%,
than the typical roasted flavor precursor group (Pattee et al.,
1982). Roasted flavor scoring of these seed sizes showed a sig-
nificant difference in acceptability between these two seed sizes
(Table 2.1). These observations suggest the possibility of using the
ratio of the concentrations of the amino acids responsible for
typical and atypical roasted peanut flavors as a quality index for
predicting the roasting flavor potential of peanuts.

Carbohydrates have also been shown to be precursors to
roasted peanut flavor (Newell et al., 1967). Their role is primarily
the contribution of carbon atoms to the flavor compounds (Koehler
et al., 1969). The monosaccharides, fructose and glucose, are the
primary source, with fructose being more reactive than glucose
(Newell et al., 1967). Sucrose per se is not involved in the pro-
duction of roasted flavor but serves as a source for fructose and
glucose (Mason et al., 1969; Reyes et al., 1982). Sucrose has also
been shown to be much less reactive in model browning system
than fructose or glucose (El'ode et al., 1966).

Table 2.1. Flavor scores of peanut butter from 1978 crop peanuts
of varying seed size (Adapted from Pattee et al., 1982).

Seed Size Flavor Score# Flavor Score#
(mm) (in) (UT)+ (VT)

5.95 15/64 4.0 4.0
7.14 18/64 2.5 3.0
7.94 20/64 2.7 2.8
8.74 22/64 2.5 2.4

L.S.D.,9 0.6 0.7

# Values are an average across the 0, 3, 6, and 9 month storage times for each seed
size. A 5-point scale was used: Excellent = 1, very poor = 5.
+ Same roasting time used for all seed sizes.
Roasting time varied to obtain uniform roasted color for each seed size.

The cotyledons of peanuts naturally contain about 18% car-
bohydrate (Woodroof, 1983). In addition to being carbon suppliers
to the roasted flavor reactions, carbohydrates also provide the
basic sweet taste of peanuts. Sucrose is the most abundant car-
bohydrate in the peanut seed and accounts for about 2.9-6.4% of
the total peanut weight (Holley and Hammons, 1968; Newell et al.,
1967). Pattee et al. (1974) followed the accumulation of starch and
sugars during maturation of peanuts. These authors found starch
to reach a maximum just beyond the middle maturity stage of the
seed and then remain constant. Sugar content increased throughout
maturation, reaching a maximum at full maturity. Tharanathan
et al. (1975) showed that total carbohydrate in the defatted edible
peanut flour was 38%. Glucose and fructose, the dominant reducing
sugars, represent 0.8 and 0.4%, respectively. Pattee et al. (1981B)
studied seed size and storage effects on carbohydrates and found
significant changes occurring. It has been generally accepted that
the carbohydrate content of peanuts does not change with storage
time, and these data support this concept for total carbohydrates.
However, the fact that the individual components did change
indicates that information on the quality effects of such changes
should be obtained.

The prediction of roasted peanut quality by the analysis of raw
peanut constituents has long been a goal of researchers into
peanut quality. Recently, Oupadissakoon and Young (1984) pub-
lished a 10-variable statistical model for predicting roasted peanut
flavor which gave an R2 of 0.928. This model contained a number
of factors related to the typical roasted flavor precursor group.
Pattee and co-workers (1982) have used a percent composition
change in the relationship between typical and atypical roasted
flavor precursors to explain an improvement in roasted flavor
scores between 5.95 and 7.14 mm diameter seeds. This type of a
change suggests that a ratio of the sums of the concentration of
the typical roasted peanut flavor precursors to the atypical roasted
peanut flavor precursors might serve as an index of the potential
for good roasted flavor quality. The typical-atypical (T-AT) ratios
for 1978 crop peanuts at selected seed sizes are given in Table 2.2.
The ratios show a linear increase with increasing size and are
significantly different from each other. The flavor scores from
these seed sizes (Table 2.1) indicate that the 7.14 mm diameter seed
have significantly better flavor than the 5.95 mm seed, regardless
of whether uniform or variable roasting temperatures are used.
When variable roasting temperatures are used to optimize the
roasting conditions for each seed size, a more consistent improve-
ment in flavor with seed size is observed. The agreement between

Table 2.2. Ratio of typical to atypical (T-AT) roasted peanut
flavor precursors across selected seed sizes (1978 crop,
calculated from amino acid data in Pattee et al.,

Seed Size
(mm) 5.95 7.14 7.94 8.74
(in.) 15/64 18/64 20/64 22/64

T-AT Ratio 1.11 1.88 2.88 4.64

Table 2.3. Ratio of typical to atypical (T-AT) roasted peanut
flavor precursors across selected seed sizes, 1981 crop.

Seed Size
(mm) 5.95 6.35 6.74 7.14
(in.) 15/64 16/64 17/64 18/64

T-AT Ratio 0.92 1.01 1.12 1.51

increasing T-AT ratio and roasted flavor scores are supportive of
the practicality of the T-AT ratio. Data from 1981 crop peanuts
(Tables 2.3 and 2.4) show the ratio changes for four seed sizes
from 5.95 mm to 7.14 mm and the roasted flavor acceptability of
these samples as judged by a 40-member consumer panel and a
6-member professional taste panel. Because the flavor scoring was
done by different panels using different scoring systems (1981 and
1978 crop), a direct comparison of the flavor scores cannot be
made. However, the general level of flavor acceptability for these
samples is apparent. All three panels judged the 5.95 mm size seed
to be unacceptable for roasted flavor. The 6.35 mm size seed were
also unacceptable for roasted flavor with only a slight improvement
in roasted flavor acceptability for the 6.74 mm size seed. The 1981

Table 2.4. Effect of seed size on flavor scores of peanut butter
(1981 crop).

Seed Size
(mm) 5.95 6.35 6.74 7.14
(in.) 15/64 16/64 17/64 18/64

Flavor Score**,# 4.8 5.1 5.3 5.3
Flavor Score+ 1 1 2 3

Scores are an average of three location replications. A 10-point scale was used:
Excellent = 10; very poor = 1.
**Indicates significantly different at P < 0.01
cConsumer taste panel (40 members)
+Professional taste panel (6 members)

crop 7.14 mm size seed were judged marginally acceptable for
roasted flavor, while the 1978 crop seed were judged as having
"fair" roasted flavor acceptability. Comparison of the T-AT ratios
for the two crop years to each other and to the flavor accepta-
bility ratings enables us to begin to put some definitive criteria to
the T-AT ratio values. The flavor scores and T-AT ratio values
(Tables 2.3 and 2.4) for the 5.95 mm and 6.35 mm seed sizes
indicate that T-AT ratio values below 1.20 are strongly indicative
of seeds with unacceptable roasted flavor potential. The applica-
tion of the 1.20 value to the 1981 crop 6.74 mm size seed is
justified by the flavor evaluation scores; however, the 6.74 mm seed
size in other years may have a higher T-AT ratio and a more
acceptable flavor score; thus this seed size should not be classified
as always having a questionable flavor level. These data (Tables
2.2, 2.3, and 2.4) also suggest that T-AT ratios above 1.8 to 1.9
would be indicative of good roasting flavor potential. The selection
of this limit for good roasting flavor potential is based on the
fluctuating flavor scores for the 1978 crop 7.14 mm size seed,
which vary between "fair" and "good". In the 1981 crop, when
T-AT ratio for the 7.14 mm seed dropped to 1.5, the roasted
product was judged as having a marginal roasted flavor level, thus
giving support to placing the cut-off point at 1.8 to 1.9.

Application of the T-AT ratio to selected peanut varieties for
which typical and atypical amino acid precursors have been quan-
tified (Mohamed-Som, 1984) shows the T-AT ratio for some culti-
vars currently used in the commercial production of peanuts (Table
2.5). In this study the T-AT ratio values ranged from 1.68 to 3.12.
Two early maturing varieties and seven medium-late maturing
varieties which fell below the 1.90 value. These observations
combined with the location effect (2.56 to 1.92) and the previously
discussed seed size effects on the T-AT ratio demonstrate the
sensitivity of roasting flavor potential to factors such as maturity.

Low roasted peanut flavor may not always be associated with a
low T-AT ratio. The cultivar NC 8C, which has a low roasted
peanut flavor but has a T-AT ratio of 3.12, is an example of this
situation. Mohamed-Som (1984), in evaluating the amino acid levels
in the selected varieties, pointed out the very low levels of amino
acids in NC 8C and suggested this could be related to the low
roasted peanut flavor associated with NC 8C. However, no sug-
gestion was given as to what constituted an adequate level of
amino acids for roasted peanut flavor. Comparing the NC 8C total
amino acid concentration and the concentration of amino acids in
the T-AT ratio to these values for the 7.14 mm size seed in 1978
and 1981 crops suggests some guidelines for future studies (Table
2.6). Using 7.14 mm size seed as the evaluation source and stan-
dard deviation value for amino acid concentration calculated by
Mohamed-Som (1984) of 4.26 mmoles/g, a concentration of less than
22.7 mmoles per g in 7.14 mm size seed might be suspect for low
roasted flavor potential. If we apply this same criterion to the
survey data of Mohamed-Som (1984), which gave an average con-
centration of 21.1 mmoles per g, the limiting value would be 16.85
mmoles per g. One other cultivar had a value of less than 16.85
mmoles per g; this was NC 9, with a value of 16.56 mmoles per g.
This cultivar is rated as having a moderate level of roasted peanut
flavor potential. This point is extremely important, since regardless
of any relationship that may exist, in this case T-AT ratios of 3.12
and 2.93, respectively, which suggest good flavor potential, an
adequate amount of the flavor precursors must be present if a good
roasted flavor is to be generated. Further research of this point is
needed; but, in most of our commercially grown peanut varieties an
adequate quantity of roasted flavor precursors seem to be present
when harvested at full maturity and recommended curing and
storage practices are followed.

Table 2.5. Typical to atypical ratio for roasted peanut flavor
precursors from selected varieties grown at two
locations during 1982. Raw data from Mohamed-Som

Early Maturing
Variety T-AT Ratio#

Early Bunch
UF 78114
NC 9
NC 17
Keel 29
NC 7
VA 81B
NC 18222




Medium-Late Maturing
Variety T-AT Ratio#

NC 5
NC 2
NC 6
NC 4
Avoca 11
Va Bunch 46-2
GK 3
Va 56R
Tifton 8
Va 72R
Gal 19-20




Ave. T-AT

Ave. T-AT

ratio for all

ratio for all

varieties grown at Lewiston, NC

varieties grown at Suffolk, VA

#Mean of three replications each from two locations.
+All means not followed by the same letter are significantly different at the P <0.05
level according to Waller-Duncan K-Ratio T-Test.
**Indicates significantly different at P <0.01.

Table 2.6. Comparison of total amino acid concentrations and
total T-AT amino acid concentrations from NC 8C and
general crop, 1978 and 1981, 7.14 mm (18/64 in) size

Cultivar General Crop
NC 8C 1978 1981

- mmoles/g-----

Total Amino Acids 13.96 27.01 28.54

Total T-AT Amino Acids 8.98 17.58 17.72


The use of trade names in this publication does not imply
endorsement by the North Carolina Agricultural Research Service or
the United States Department of Agriculture of the products
named nor criticism of similar ones not mentioned.


Agriculture Statistics. 1983. U.S. Dept. of Agriculture, USGPO,
Washington, DC.

Cobb, W. Y. and B. R. Johnson. 1973. Physicochemical properties
of peanuts. pp. 209-263. In Peanuts Culture and Uses.
Amer. Peanut Res. Educ. Assoc., Stillwater, OK.

El'ode, T. E., T. D. Doinseiter, E. S. Keith, and J. J. Powers. 1966.
Effects of pH and temperature on the carbonyls and aromas
produced in heated amino acid-sugar mixtures. J. Food Sci. 31:

Holley, K. T. and R. O. Hammons. 1968. Strain and seasonal effect
on peanut characteristics. Res. Bull., Ga. Agric. Exp. Stn. 32.

Koehler, P. E., M. E. Mason, and J. A. Newell. 1969. Formation of
pyrazine compounds in sugar-amino acid model systems. J.
Agric. Food Chem. 17:393-396.

Mason, M. E., J. A. Newell, B. R. Johnson, P. E. Koehler, and
G. R. Waller. 1969. Nonvolatile flavor components of peanuts.
J. Agric. Food Chem. 29:800-802.

Mason, M. E. and G. R. Waller. 1964. Isolation and localization
of the precursors of roasted peanut flavor. J. Agric. Food
Chem. 12:274-278.

Mohamed-Som, H. Z. 1984. Chemical composition and flavor of
virginia-type peanuts. Unpubl. M.S. thesis, Dept. of Food
Science, N. C. State University, Raleigh, NC.

Newell, J. A., M. E. Mason, and R. S. Matlock. 1967. Precursors
of typical and atypical roasted peanut flavor. J. Agric. Food
Chem. 15:767-772.

Oupadissakoon, C. and C. T. Young. 1984. Modeling of roasted
peanut flavor for some virginia-type peanuts from amino acid
and sugar contents. J. Food Sci. 49:52-58.

Oupadissakoon, C., C. T. Young, F. G. Giesbrecht, and A. Perry.
1980A. Effect of location and time of harvest on free amino
acid and free sugar contents of Florigiant peanuts. Peanut Sci.

Oupadissakoon, C., C. T. Young, and R. W. Mozingo. 1980B.
Evaluation of free amino acid and free sugar contents in five
lines of virginia-type peanuts at four locations. Peanut Sci.

Pattee, H. E., E. B. Johns, J. A. Singleton, and T. H. Sanders.
1974. Composition of peanut fruit parts during maturation.
Peanut Sci. 1:57-62.

Pattee, H. E., J. L. Pearson, C. T. Young, and F. G. Giesbrecht.
1982. Changes in roasted peanut flavor and other quality
factors with seed size and storage time. J. Food Sci. 47:455,
456, 460.

Pattee, H. E., C. T. Young, and F. G. Giesbrecht. 1981A. Free
amino acids in peanuts as affected by seed size and storage
time. Peanut Sci. 8:113-116.

Pattee, H. E., C. T. Young, and F. G. Giesbrecht. 1981B. Seed size
and storage effects on carbohydrates of peanuts. J. Agric.
Food Chem. 29:800-802.

Reyes, F. G., R. B. Pocharoen, and R. E. Wrolstad. 1982. Maillard
browning reaction of sugar-glycine model systems: Changes in
sugar concentration, color and appearance. J. Food Sci.
47:1376, 1377.

Tharanathan, R. N., D. B. Wankhede, M. R. and Raghavendra-Rao.
1975. Carbohydrate composition of groundnuts (Arachis hvyo-
gaea). J. Sci. Food Agric. 26:749-754.

Woodroof, J. G. 1983. Peanuts: Production, Processing, Products.
411 pp. 3rd ed. AVI Publishing Co., Westport, CT.

Measuring Peanut Maturity Using
Near Infrared Reflectance

Thomas B. Whitaker, Harold E. Pattee, William F. McClure,
and James W. Dickens

The indeterminate flowering characteristic of the peanut plant
results in pods at various stages of maturity at the time of digging.
Several methods have been developed to determine the maturity
profile of peanuts so farmers can dig at a time that maximizes
yield and/or crop value (Sanders et al., 1982). After farmers stock
peanuts are marketed, the presence of immature kernels in produc-
tion channels can have an adverse effect upon the quality of the
finished product (Pattee et al., 1985; Sanders et al., 1982). The
present grading system for farmers stock peanuts does not measure
maturity as a grade factor partly because of the lack of a suitable

Spectrophotometric techniques have been used to measure the
quality and chemical composition of various agricultural commodi-
ties (Polesello and Giangiacomo, 1983). In particular these tech-
niques have been developed to measure the ripeness of peaches,
blueberries, and tomatoes (Chen, 1979). Kramer et al. (1963) used
light absorption in the visible range (400 to 750 nm) to measure
the maturity of intact peanut kernels. Norris (1964) demonstrated
that reflected energy in the near infrared (NIR) region (800 to 3000
nm) can be used to measure the quality and composition of agricul-
tural products. Regression techniques have been developed to
determine multiple wavelengths in the NIR region where reflected
energy correlates with chemical composition (Hamid et al., 1981).
Near infrared (NIR) techniques provide a method to measure
chemical constituents of a commodity more rapidly and at less cost
than conventional wet chemistry methods (Osborne, 1981). The
objectives of this study were to determine if NIR reflectance
techniques could be used to measure peanut maturity, determine the
specific wavelengths where reflected energy correlates with matur-
ity, and develop calibration equations to measure the maturity of
virginia type peanuts.



The NIR reflectance from the comminuted peanut kernel
samples was measured using a computerized spectrophotometric
system developed by McClure et al. (1980) that is similar to that
developed by Norris (1964). The system consists of a mono-
chrometer with a wavelength range from 400 to 3000 nm, a sample
compartment containing four lead sulfide detectors that sense the
energy reflected from the sample, and a minicomputer which
controls the system and performs the necessary data transfor-
mations and statistical analyses. Each sample was placed into the
sample compartment, and the log (1/R), where R is reflected
energy, was obtained over a wavelength range of 900 to 2600 nm.
The log (1/R) spectrum, consisting of 1700 discrete values one nm
apart, was stored on a floppy diskette along with its associated
maturity class for further data analysis. A log (1/R) spectrum from
a reference standard of halon powder was stored in the computer
for system response corrections.

The log (1/R) spectrum (1700 data values) was smoothed using
a 21-point moving point average. Ten log (l/R) values were lost at
the beginning (900 to 909 nm) and 10 at the end (2591 to 2600 nm)
of the spectrum due to the smoothing technique. Every other log
(1/R) value was then removed from the remaining 1680 points in
the smoothed spectrum. The remaining 840 log (1/R) values in the
spectrum were each transformed into the optical parameter D2(li)
by taking the second derivative with respect to wavelength of the
log (1/R) or d2 (log(1/R))/dl2. The D2(li) transformation was
chosen because past studies in other commodity areas have demon-
strated that stronger correlations were achieved with this param-
eter than with other optical parameters (McClure et al., 1977;
Hamid et al., 1978; McClure and Williamson, 1982).

Maturity Classification by Kernel Size

NC 6 peanuts harvested from a single field at the Peanut Belt
Research Station, Lewiston, NC, were dried to approximately 7%
moisture (w.b.) and shelled in equipment similar to that used by the
Agricultural Marketing Service (AMS) (Dickens, 1968). The kernels
were divided into 10 classes by kernel diameter. Kernel diameter
was determined by use of slotted peanut grading screens. While
kernel diameter is not a precise method of determining kernel

maturity (Pattee et al., 1981), screens do provide a rapid method of
classifying a large quantity of kernels into approximate maturity
levels. The 10 size classes (to be called maturity classes) consisted
of whole kernels that were retained on 4.76 mm (12/64 in round),
5.95 x 25.4 mm (15/64 x 1 in), 6.35 x 19.05 mm (16/64 x 3/4 in),
6.75 x 19.05 mm (17/64 x 3/4 in), 7.14 x 25.4 mm (18/64 x 1 in),
7.54 x 25.4 mm (19/64 x 1 in), 7.94 x 19.05 mm (20/64 x 3/4 in),
8.53 x 25.4 mm (21.5/64 x 1 in), 8.73 x 31.75 mm (22/64 x 5/4 in),
and 9.53 x 31.73 mm (24/64 x 5/4 in) screens. Kernels that were
retained on a given size screen, fell through all screens of a larger
size. For example, kernels that were retained on the 5.95 x 25.4
mm screen, fell through the 6.35 x 19.05 mm and larger screens.
Kernels that were retained on the smallest screen, 4.76 mm, were
considered to be on the average the most immature and were
assigned a maturity class of 12. Kernels that were retained on the
largest screen, 9.53 x 31.75 mm, were considered to be on the
average the most mature and were assigned a maturity class of 24.
The kernels in each maturity class were comminuted in a Waring
blender for 10 sec. The comminuted kernels were screened over a
1 mm diameter sieve to remove the larger particles. Approximately
5 g of screened comminuted peanuts were placed into a Technicon
sample holder with a quartz window. The sample holder was placed
into the sample compartment, and the log (1/R) spectrum was

A total of 1,000 spectra (10 maturity classes times 100 samples
per class) were recorded. The total data set was divided into two
groups. Fifty spectra per maturity class were randomly placed into
a calibration group while the remaining 50 spectra per maturity
class were placed into a prediction group. Each group contained
500 spectra, each with an associated maturity class value.

The 500 spectra in the calibration group were used to develop
a calibration equation to predict maturity class. The relationship
between maturity class, M, and the optical parameter, D2(li), is
given by equation 1:

M = ao +...+ aiD2(li) +...+ anD2(ln) (1)

where ao is the intercept, ai are regression coefficients, D2(li) is
the magnitude of the optical parameter at wavelength li in nm, and
n is the number of terms in the calibration equation. A stepwise
multiple linear regression was used to determine the regression
coefficients ai. The regression procedure considered all the wave-
lengths in each of the 500 spectra in order to select the wave-

lengths at which D2(li) best correlates with M. The stepwise
process is terminated when (i) there is no variable left which
causes a statistically significant improvement in the regression
equation, (ii) the variable entering the equation is the one just
eliminated, or (iii) the desired number of steps has been executed.
For this study, the regression analysis was terminated after 10
steps were executed.

After the calibration equation was developed from the spectra
in the calibration group, the validity of the calibration equation
was tested. For each spectrum in the prediction group, D2(li) was
calculated at each wavelength chosen in the regression analysis,
and was substituted into the calibration equation, and the maturity
class was computed. The predicted maturity class for each of the
500 spectra in the prediction group was then compared with the
observed maturity class value for closeness of fit.

Maturity Classification by Hull Scrape Method

A second study similar to the one described above was made on
peanut kernels which were divided into five maturity classes using
the hull scrape method (Drexler and Williams, 1981). NC 7 peanut
pods were dug from a single field at the Peanut Belt Research
Station. Peanut kernels from freshly dug pods that had a white,
yellow to orange, orange, orange to brown, and black color were
placed into maturity classes 1, 2, 3, 4, and 5, respectively. Kernels
in maturity class 1 were considered to be the most immature, while
peanut kernels in maturity class 5 were considered to be the most
mature. The kernels were dried to about 7% moisture and prepared
for NIR measurement in a similar manner to the size study. The
log (1/R) spectra for 32 samples per maturity class (160 total
samples) were obtained over the wavelength range of 900 to 2600
nm. The total data set was divided into two groups. Sixteen
spectra per maturity class were randomly placed into a calibration
group, while the remaining 16 spectra per maturity class were
placed into a prediction group.

Using stepwise multiple linear regression techniques, equation 1
was fit to 80 spectra (16 spectra per maturity class) in the cali-
bration group. The regression coefficients ai were calculated, as
were the wavelengths at which D2(li) were found to correlate with
maturity. These values were substituted into equation 1, which
then became the calibration equation. The calibration equation was
then used to measure the maturity class of the 80 samples in the

prediction group. The predicted maturity class for each of the 80
spectra in the prediction group was then compared with the ob-
served maturity class value for closeness of fit.

Predicting Maturity of Farmers Stock Lots

Equation 1, with coefficients and wavelengths developed from
screen size data, was used to measure the maturity class of 497
farmer stock lots marketed in the Virginia-Carolina area. Samples
of approximately 1800 g each were collected from 497 farmers stock
peanut lots during the 1985 marketing season by the North Carolina
Federal State Inspection Service. In accordance with the proce-
dures described by the USDA Inspection Instructions (1980), about
500 g of pods were removed from the 1800 g sample and shelled.
Kernels that were retained on a 5.95 x 25.4 mm screen were split.
All mold-damaged and discolored cotyledons were removed. Ap-
proximately 100 g of the remaining cotyledons were used to deter-
mine the maturity class for the sample.

After NIR measurements, the remaining portions of some of the
samples were combined for taste test evaluations and further NIR
maturity measurements. Samples with a computed maturity class of
15 or less were combined into one group called the immature group.
Samples with a computed maturity class of 22 or greater were
combined into another group called the mature group. Peanuts in
each group were shelled, and the kernels were subdivded into 11
kernel sizes using the following slotted peanut grading screens:
5.95 x 25.4 mm, 6.35 x 19.05 mm, 6.75 x 19.05 mm, 7.14 x 25.4 mm,
7.54 x 25.4 mm, 7.94 x 19.05 mm, 8.53 x 25.4 mm, 8.73 x 31.75 mm,
9.53 x 31.75 mm, 9.92 x 31.75 mm (25/64 x 5/4 in), and 10.32 x 38.1
mm (26/64 x 3/2 in). The maturity class of the kernels in each
size category and maturity group was measured using equation 1,
and coefficients were developed from kernel size data.

Flavor Evaluation

The peanut kernels in each maturity group were separatedinto
two size categories with slotted screens: 6.75 mm (retained on a
6.75 x 19.05 mm screen and fell through a 7.14 x 25.4 mm screen)
and 8.53 mm (retained on a 8.53 x 25.4 mm screen and fell through
a 8.73 x 31.75 mm screen). The kernels in each size category and
maturity group were subdivided into eight 50-gm subsamples prior
to roasting to provide a single kernel layer in the eight roasting

trays and uniform distribution within roasting oven thus overcom-
ing any temperature gradients within the oven. The roasting tem-
perature was 1600C; however, roasting time was varied to insure
uniform roast color between each size category and maturity group.
Three trial runs were made for each group to establish the roasting
time. Each batch was forced-air cooled at room temperature to
minimize the variation in cool-down time. Each batch was blanched
as described by Hoover (1979) and then ground into peanut butter
by single pass through an Olde Tyme Peanut Butter Mill (Olde
Tyme Food Products, East Long Meadow, MA 01028). The peanut
butter samples were rated for consumer acceptance by a profes-
sionally trained panel of six individuals in the Department of Food
Science, North Carolina State University. Training of the panel for
peanut flavor attributes and peanut butter ranking is described by
Oupadissakoon (1980).


Maturity Classification by Kernel Size

Log (1/R) spectra for maturity classes 12 and 24 are shown in
Fig. 3.1. Each spectrum looks like an absorption spectrum [log
(1/T)] where the peaks represent the presence of absorbers. The
log (1/R) and D2(li) spectra for maturity class 12 are shown in Fig.
3.2. Negative peaks in the D2(li) spectrum occur at wavelengths
where maximum peaks occur in the log (1/R) spectrum. One ad-
vantage of the D2(lj) spectrum is that it indicates the location
of hidden peaks in the log (1/R) spectrum (Hamid et al., 1978;
McClure and Williamson, 1982).

The wavelengths and regression coefficients for equation 1
selected by the stepwise multiple linear regression analysis are
shown in Table 3.1. The coefficient of determination (r2) for the
calibration equation is 0.95. The large coefficient of determination
indicates that there is a strong correlation between the optical
parameter D2(li) and maturity class when using the 10 wavelengths
listed in Table 3.1.

The calibration equation was then used to predict the maturity
class of each of the 500 samples in the prediction group. The
results are shown in Fig. 3.3. The standard error of prediction
(SEP) was 0.88. Ninety-five percent of all the predicted maturity
class values were within + 1.76 of the observed maturity class. The
coefficient of determination and the SEP suggests that reflectance


V 8.7

o e.s
J 8.4




Figure 3.1.





v B.79-

J 0.42-



Figure 3.2.

Figure 3.2.


Log (1/R) spectra versus wavelength for two samples
of comminuted peanuts with different maturity classes
(R = reflectance).

D2CL06 <1/R))

I rt t i i 'i;i '"1'

-- lI I 1 I I I-
S1.07 1.24 1.41 1.50 1.76 1.02 2.88 2.20 2.43 2.80

Log (l/R) spectrum and second derivative (D2) of lot
(1/R) spectrum versus wavelength for a peanut
sample with maturity class 15 (R = reflectance).

Table 3.1. Regression coefficients and wavelengths chosen by the
stepwise multiple linear regression analysis where the
reflected energy correlates with maturity (M) as
determined by kernel size.

Regression Term Coefficient Wavelength
i ai li

0 19.21
1 234.76 1180
2 -144.16 1398
3 -268.35 1412
4 239.61 1186
5 -165.73 1380
6 213.96 1516
7 -225.64 1708
8 -386.29 1670
9 -16.03 2316
10 193.53 1468

r2 = 0.953
M = ao + alD2(ll) +...+ aiD2(li) +...+ anD2(ln)

techniques do have the potential to predict the maturity of peanuts
as defined by kernel size.

Maturity Classificiation by Hull Scrape Method

Equation 1 was fit to the 80 spectra in the calibration group
using stepwise multiple linear regression techniques. The regression
coefficients and wavelengths chosen by the regression analysis
where D2(li) correlated with maturity class as defined by the hull
scrape method are shown in Table 3.2. As in the previous case,
where maturity was defined by kernel size, there is also a high
correlation between D2(li) and maturity as defined by the hull
scrape method. The coefficient of determination for the calibration
equation was 0.96. The calibration equation was then used to pre-
dict the maturity class of the remaining 80 samples in the predic-

tion group. The results are shown in Fig. 3.4. The standard error
of prediction was 0.60. These results also support the conclusion
that NIR reflectance techniques can be used to measure peanut

Predicting Maturity of Farmers Stock Lots

The distribution of predicted maturity classes of the 497
farmers stock lots computed with the calibration equation shown in
Table 3.1 is given in Table 3.3. All computed maturity classes fell
between 13 and 26. A total of 44 samples had a maturity class of
15 or less and were combined into the immature group. A total of
35 samples had a maturity class of 22 or greater and were com-
bined into the mature group. The maturity class of the kernels in
each size category of the two maturity groups are shown in Table
3.4. The predicted maturity class of kernels in the mature group

Table 3.2. Regression coefficients and wavelengths chosen by the
stepwise multiple linear regression analysis where the
reflected energy correlates with maturity (M) as
determined by the hull scrape method.

Regression Term Coefficient Wavelength
i ai li

0 0.09
1 64.49 1734
2 190.29 1386
3 -6.66 2542
4 -76.25 1696
5 -370.76 1704
6 225.26 1208
7 -278.00 1160
8 -102.99 1362

r2 = 0.96
M = ao + aD2(l) ++ aD2(11) D() +...+ anD2(ln)


T.B 1.2 1.4 1.6 1.8 2.8 2.2 2.4 2.6 2.8 i

Figure 3.3.




m 3
Fu 2


Figure 3.4.

Relationship between the maturity class of 500 peanut
samples as determined by screen size and the maturity
class of the same 500 peanut samples as predicted by
near infrared (NIR) reflectance. The standard error
of prediction (SEP) was 0.88.


Relationship between the maturity class of 80 peanut
samples as determined by the hull scrape method and
the maturity class of the same 80 peanut samples as
predicted by near infrared (NIR) reflectance. The
standard error of prediction (SEP) was 0.60.

Z 2.6



I I 1 1 I I I L

- 2.4

V 2.2



\ 1.6
4 1.2

Table 3.3. Distribution of measured maturity classes of 497 check
samples taken from farmers stock lots marketed in the
Virginia-Carolina area in 1985.

Computed Number Cumulative Relative
Maturity Class Samples % Samples Maturity

13 1 0.2 Immature
14 12 2.6
15 31 8.9
16 73 23.5
17 80 39.6
18 93 58.4
19 77 73.8
20 58 85.5
21 37 93.0
22 20 97.0
23 8 98.6
24 4 99.4
25 2 99.8
26 1 100.0 Mature

was higher than for the same size kernels in the immature group
across all size categories. These measurements indicate that kernel
size and kernel maturity are not closely related for peanuts grown
under different conditions and that NIR maturity measurements are
related to factors other than kernel size.

The taste panel results for each maturity group are shown in
Table 3.5 for two kernel size categories. The flavor scores are a
consensus among the six panel members. Each individual panel
member scored the samples on a scale of 1 (bad) to 10 (good).
Then, after discussing their results, the group came to a consensus
score. For a given kernel size, the kernels in the mature group
tasted slightly better than the kernels in the immature group.
Large kernels with a maturity class of 15.3 had a better flavor
than small kernels with a maturity class of 18.0. These data
indicate that NIR maturity measurements are not closely related to

Table 3.4. Measured maturity of kernels from each maturity
group that were divided into 11 size categories.

Screen Immaturea Matureb Differencec
Size (mm) Group Group

5.95 x 25.4 12.1 14.7 2.6
(15/64 x 1 in)

6.35 x 19.05 12.7 16.2 3.5
16/64 x 3/4 in)

6.75 x 19.05 13.2 18.0 4.8
(17/64 x 3/4 in)

7.14 x 25.4 13.6 19.4 5.8
(18/64 x 1 in)

7.54 x 25.4 14.6 21.5 6.9
(19/64 x I in)

7.94 x 19.05 16.6 23.2 6.6
(20/64 x 3/4 in)

8.53 x 25.4 15.3 23.9 8.6
(21.5/64 x 1 in)

8.73 x 31.75 15.8 23.4 7.6
(22/64 x 5/4 in)

9.53 x 31.75 17.1 23.8 6.7
(24/64 x 5/4 in)

9.92 x 31.75 16.3 23.9 7.6
(25/64 x 5/4 in)

10.32 x 38.1 17.5 22.8 5.3
(26/64 x 3/2 in)

a 44 check samples that measured 15 or less (see Table 3.5).
b 35 check samples that measured 22 or greater (see Table 3.5).
c Difference = Mature Immature

Table 3.5. Consensus flavor scores for roasted peanut butter.

Maturity Kernel Size

6.75 mmb 8.53mmc

Maturity Flavor Maturity Flavor
Class Score Class Score

Immatured 13.2 2 15.3 7
Mature 18.0 3 23.9 8

a Consensus of a 6-member panel where 1 = least desirable flavor and 10 = most
desirable flavor.
b Kernels were retained on a slotted screen 6.75 mm wide and fell through a slotted
screen 7.14 mm wide.
c Kernels were retained on a slotted screen 8.53 mm wide and fell through a slotted
screen 8.73 mm wide.
d 44 AMS grade samples that measured 15 or less (see Table 3.3).

e 35 AMS grade samples that measured 22 or greater (see Table 3.3).


There is a strong correlation between reflected energy in the
NIR region at 10 specific wavelengths and maturity as defined by
kernel size. Equally strong correlations were found when the hull
scrape method was used to define maturity. The predicted maturity
class of samples from 497 farmer stock lots varied from 13 to 26.
Samples measuring 15 or less were placed into an immature group,
while samples measuring 22 and greater were placed into a mature
group. Kernels from the immature group measured more immature
than kernels of the same size from the mature group. These
results suggest that NIR reflectance measurements are highly
correlated with maturity. While NIR is probably measuring some
chemical compounds) that varies with maturity, flavor panel results
suggest that the compounds) may not be related to flavor.


This is Paper No. 10842 of the Journal Series of the North
Carolina Agricultural Research Service, Raleigh, NC 27695-7601.

The use of trade names in this publication does not imply
endorsement by the United States Department of Agriculture or the
North Carolina Agricultural Research Service of the products
named, nor criticism of similar ones not mentioned.


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Peanut Quality in Curing and Storage

Timothy H. Sanders, Paul D. Blankenship, and
John S. Smith, Jr.

Quality maintenance is a continuous process. Any breakdown
in the system from planting to consumption may reduce quality.
Quality cannot be restored once lost. As a beginning point and as
a constant consideration throughout curing and storage, maturity
must be considered. The work of Williams and Drexler (1981) is
well documented relative to pod maturity based on pod mesocarp
color. The basic work which developed into a harvest prediction
method may be used after harvesting to determine the maturity
profile of the harvested crop. Maturity profiles of peanuts already
in drying wagons have shown that a wide range of profiles can be
obtained within a given harvesting period. Some profiles are
uniformly mature, some are split crops (about as many mature as
immature), and others are very immature. Planting date, soil
temperature, soil moisture, variety, various cultural practices and
other factors affect peanut maturation rates and some of these,
drought in particular, have the propensity to affect kernel moisture
at harvest. The moisture content of peanuts of different maturity
levels is usually quite different. Moisture content of individual
pods within a harvested lot (after window drying) may vary from
less than 10% to more than 30%. Because of this variability, a
given set of drying conditions will not dry all peanuts in a load to
the same moisture level. Because of moisture and composition
considerations, maturity must be considered in all aspects of curing
and storage.

The first apparent step in curing is window drying of peanuts.
In the window peanuts are exposed to ambient air and sunlight for
1-3 days to reduce moisture content to 18-25%. Peanut pod tem-
peratures in the window vary with ambient conditions. Peanuts
properly exposed to the air reach temperatures higher than am-
bient, and temperatures of 43.30C (1100F) are not uncommon for
short periods of time during the hottest part of a day. After
digger-inverter operations some peanuts are left in contact with the
soil during the period of window drying. These peanuts are
exposed to higher temperatures than peanuts not in contact with

soil (Pearman and Butler, 1968; Butler et al., 1969). Bailey and
coworkers (1954) recorded a temperature of 550C inside a partially
cured peanut exposed to direct sunlight when the maximum air
temperature was 36.60C. The effects of very high drying tempera-
tures on high moisture peanuts will be discussed later. The effects
of various environmental conditions during window drying have
received little research attention; however, extended periods of wet
conditions and the normally accompanying cool temperatures may
result in significant pod loss and/or mold growth on peanuts.
After window drying, peanuts are combined and usually placed in
wagons for further drying with heated air. Since quality main-
tenance is a continuous process, we must note here that significant
damage can be imparted during the combining operation. Studies
on pod damage imparted by combining indicate that approximately
half the pods harvested may be visibly damaged, depending on
moisture content and combine cylinder speed (Wright, 1968). This
damage may not only expose the kernel to further damage from
dust or insects but also may have damaged or ruptured kernel cells
to expose cell components, thus leading to rapid deterioration.

Too often, due to the rush of harvest, little concern is given
to curing peanuts versus drying peanuts. Thus, rapid movement of
peanuts through the curing process often takes precedence over
quality concerns. The term "drying wagon" inherently overlooks
the concept of curing. Drying may be considered water removal
without concern for the finer biochemical processes that occur
during water removal to produce optimum food quality. Curing
then is the process of water removal with attention to those
factors that result in optimum biochemical/physiological processes
related to food quality. Because of common usage we will continue
to use the terms interchangeably in this chapter. Rate of peanut
deterioration at the point of curing may be related to (1) original
quality, (2) moisture content control and (3) damage. Original
quality is related to production environment, maturity and window
conditions as already discussed. Moisture content control relates to
the way in which moisture is removed from the peanuts.

Recommended peanut drying practices in the Southeast are
generally considered to be as follows: drying air temperature in
the trailer plenum no higher that 350C with no more than a 8.40C
rise above ambient temperature and air flow rate of approximately
15 m3/min/m3 of peanuts. These recommendations are basic guide-
lines and may vary somewhat with geographical area. Delays
between the time of trailer loading and beginning curing should be
kept to a minimum. Long delays, especially when high initial

moisture peanuts are loaded into drying wagons, may result in
extensive microbial growth in the peanuts with generation of high
temperatures and off-flavors.

Two of the most common deviations from recommended drying
practices are overdrying and drying air temperature too high.
These practices have some results in common; one of these is
increased percentage of split kernels. Percentage of split kernels
is related to drying air temperature, maturity (digging time), drying
potential of air (relative humidity) and after drying moisture
content (Beasley and Dickens, 1963; Hutchison, 1966; Davidson
et al., 1970; Blankenship and Pearson, 1975). Percentages generally
increase with increased drying air temperatures, decreased drying
air relative humidity (below 50-60%), and decreased final moisture
content below 9-10%. Increases of up to 5% split kernels are not
uncommon, depending on combinations of the above factors. If
peanuts are overdried, not only does the percentage of split kernels
increase, but the marketable weight of the load is reduced and
value is lost.

The results of elevated drying air temperature are increased
split kernels, loose shelled kernels (LSK), and potential for flavor
variations (Beasley and Dickens, 1963). Often, overdrying or drying
too fast with high temperatures weakens peanut hulls. Weakened
hulls may result in more peanuts being shelled during sampling and
grading procedures, with the result that the grade indicates an
incorrect LSK percentage. Increasing percentages of LSK decrease
the value of the load, and LSK are much more likely to become
contaminated with Aspergillus flavus and aflatoxin during storage.
LSK's are also more likely to undergo significant quality deteriora-
tion in storage than unshelled peanuts.

In the late 1940's and early 1950's it was recognized that
curing affected peanut flavor (Bailey et al., 1947; Bailey and
Pickett, 1952) and that high curing temperatures resulted in off-
flavors (Bailey et al., 1954). Matlock (1968) reported a decrease in
sensory panel scores when peanuts were dried at elevated tempera-
tures (40.60C and 48.90C). Whitaker and Dickens (1964) found the
level of off-flavor to be related to anaerobic respiration in the
peanut that occurred during curing. They also found that immature
peanuts were more susceptible to the problem, as observed earlier
by Dickens (1957). Pattee et al. (1964, 1965) were the first to
isolate, identify and compare the volatiles from normal flavored and
off-flavored peanuts. Singleton et al. (1971) compared the volatiles
from peanuts cured at various temperatures and found an increase

in compounds previously associated with high-temperature-curing

Flavor problems are more subtle than LSK, split kernels and
other physical factors, as they are initially less obvious and usually
not detected until manufacturing. At this point in the system it is
generally impossible to identify when or why flavor variation oc-
curred unless specific flavor notes can be related to specific envi-
ronmental or handling situations.

The curing process is limited by many factors, not the least of
which is moisture content of individual peanuts. Peanuts are dried
to an average moisture of about 10%, which means that some pea-
nuts will be higher and some will be lower, depending on initial
moisture. Overdried peanuts are subject to the problems previously
described; however, peanuts that are too moist present a totally
different problem as they move through the marketing system.
Blankenship and Hutchison (1971) found that the moisture content
of immature peanuts was approximately twice the moisture content
of mature peanuts at harvest. The.difference in moisture content
decreased substantially during drying. The immature kernels were
at a higher moisture content than the mature kernels from harvest
through 5 months of artificial storage. We have recently measured
the moisture content of various peanut and foreign material com-
ponents found in several lots. After normal drying and 5 months
storage, immature peanuts still contained up to 17% moisture. This
moisture content is unacceptable for any storage period. The
importance of maturity as it relates to moisture content in curing
and subsequent storage is clear in these examples.

Storage of farmers stock peanuts in the relatively uncontrolled
environment of 3,000-5,000 tonne warehouses is critical to quality
maintenance. Peanuts are usually stored in-shell in these ware-
houses from early fall until late spring (6-8 months). During this
time significant changes occur in ambient temperature which affect
moisture and temperature control in the warehouse. Warehouse
operation must include consideration of ventilation, relative
humidity, temperature and foreign material in the warehouse.
Perhaps the most significant is ventilation, which in practice is
controlling the removal of moisture from the warehouse. The
example of moisture content of immature peanuts is sufficient to
show this need. Peanuts usually dry from about 10% moisture to
6-7% moisture during farmers stock storage. In a typical warehouse
this amounts to approximately 151,200 L (40,000 gallons) of water
that must be eliminated from the overspace inside the warehouse.

Peanuts being loaded into warehouses are warm because of ambient
environmental conditions and the curing operation. Smith et al.
(1983) examined peanut mass temperature profiles for selected times
in mechanically and naturally ventilated warehouses during a
9-month storage period. They found that very warm temperatures
early in storage in the Southeast moderated to cooler temperatures
as winter temperatures prevailed outside the warehouse. As
exterior ambient temperatures and relative humidities decrease,
peanuts begin to lose moisture. If ventilation is not sufficient to
remove the moist air from inside the warehouse, water condenses
on roof structures and drips onto the pile of peanuts. Wet peanuts
are very susceptible to microbial growth and quality deterioration.
Sanders et al. (1981) conducted studies on peanuts from five peanut
warehouses with obvious deficiencies. They found that excess
moisture, high temperatures and mechanical damage resulted in
peanut quality deterioration as evidenced by low grade factors,
increased fatty acids and increased carbonyl content. Levels of
deterioration were related to kernel condition and length of
storage. Loose shelled kernels were highly susceptible to deteriora-
tion. The research emphasized the need for reduced mechanical
damage, improved ventilation, elimination of moisture concentra-
tions (condensation) and minimizing length of storage of peanuts of
marginal initial quality.

Current research to monitor conditions in warehouses and
relate quality changes to specific situations or locations within the
warehouse indicate that some quality differences may in fact be
imparted during storage. However, with the current practices of
mixing loads into large warehouses, mixing locations within the
warehouse as the warehouse is unloaded, and further mixing in
shelling operation, quantitative variation in quality imparted by
storage alone may be negligible, when recommended practices are
carefully carried out. This is not to indicate that all these
practices cannot be improved to provide higher quality. It is an
indictment against many practices that complicate net end product
quality evaluation to the point that change in any area alone may
not have observable impact on a consistent basis.


Bailey, W. K., J. G. Futral, and T. A. Pickett. 1947. Peanut curing
studies. I. Effect of harvesting and curing procedures on
quality of peanuts. Ga. Agric. Exp. Sta. Bull. 255.

Bailey, W. K. and T. A. Pickett. 1952. Sunlight can damage
peanuts during curing. Georgia Agric. Experiment Station Press
Bulletin No. 640.

Bailey, W. K., T. A. Pickett, and J. G. Futral. 1954. Rapid curing
adversely affects quality of peanuts. The Peanut J. and Nut
World 33(8):17, 37-39.

Beasley, E. 0. and J. W. Dickens. 1963. Engineering research in
peanut curing. N. C. Agric. Exp. Sta. Techn. Bull. 155.

Blankenship, P. D. and J. L. Pearson. 1975. Effects of restoring
peanut moisture with aeration before shelling. Peanut Sci.

Blankenship, P. D. and R. S. Hutchison. 1971. Differences in the
moisture content of mature and immature peanuts. ARS 52-61.

Butler, J. L., G. E. Pearman, and E. J. Williams. 1969. Effect of
window configuration on drying rate and uniformity of
moisture content of peanuts. Amer. Peanut Res. and Educ.
Assoc. Journal 1:54-61.

Davidson, J. I., Jr., P. D. Blankenship, and R. S. Hutchison. 1970.
Shelling and storage of partially dried (cured) peanuts. Amer.
Peanut Res. and Educ. Assoc. J. 2:57-64.

Dickens, J. W. 1957. Observations related to the flavor of bulk
cured peanuts. Proc. Assoc. Southern Agric. Workers 54th
Annual Convention, Birmingham, AL, pp. 37-38.

Hutchison, R. S. 1966. Research studies on drying farmers stock
peanuts. Proc. Fourth National Peanut Research Conference,
July 14-15, Tifton, GA, pp. 33-42.

Matlock, R. S. 1968. Research on peanut quality. Proc. Fifth
National Peanut Research Conference, July 15-17, Norfolk, VA
pp. 41-54.

Pattee, H. E., E. O. Beasley, and J. A. Singleton. 1964. Isolation
and identification of off-flavor components from high tempera-
ture cured peanuts. Proc. Third National Peanut Research
Conference, July 9-10, Auburn, AL, pp. 66-68.

Pattee, H. E., E. 0. Beasley, and J. A. Singleton. 1965. Isolation
and identification of volatile components from high-tempera-
ture-cured off-flavor peanuts. J. Food Sci. 30:388-392.

Pearman, G. E. and J. L. Butler. 1968. Effect of inverting peanuts
on kernel temperature, moisture content and losses. Proc.
Fifth National Peanut Research Conference, July 15-17, Nor-
folk, VA. pp. 67-79.

Sanders, T. H., J. S., Smith, Jr., J. A. Lansden, and J. I. Davidson,
Jr. 1981. Peanut quality changes associated with deficient
warehouse storage. Peanut Sci. 8:121-124.

Singleton, J. A., H. E. Pattee, and E. B. Johns. 1971. Influence
of curing temperature on the volatile components of peanuts.
J. Agric. Food Chem. 19:130-133.

Smith, J. S., Jr., J. I. Davidson, Jr., T. H. Sanders, J. A. Lansden,
and R. J. Cole. 1983. Changes in the temperature profile of
farmers stock peanuts during storage. Peanut Sci. 10:88-93.

Whitaker, T. B. and J. W. Dickens. 1964. The effect of curing on
respiration and off-flavor in peanuts. Proc. Third National
Peanut Research Conference, July 9-10, Auburn, AL, pp. 71-80.

Williams, E. J. and J. S. Drexler. 1981. A non-destructive method
for determining peanut pod maturity. Peanut Sci. 8:134-141.

Wright, F. S. 1968. Effect of combine cylinder speed and feed
rate on peanut damage and combine efficiency. Proc. Fifth
National Peanut Research Conference, July 15-17, Norfolk, VA,
pp. 99-112.


Peanut Grading and Quality Evaluation

James W. Dickens and Ligon W. Johnson

Accurate determination of peanut quality will not only expedite
the marketing of peanuts but will serve to benefit the whole peanut
industry, because high quality peanuts will be presented at the
market place more consistently when the seller can be assured that
the buyer will recognize and pay for high quality. The U.S. peanut
industry is currently trying to improve the quality of peanuts for
domestic and export trade. The Research Committee of the Na-
tional Peanut Council has identified improved peanut grading and
quality evaluation as a means of improving U.S. peanut quality.
The committee has indicated that the grade should reflect flavor
and other factors related to the edible use of peanuts. Other
concerns are related to accurate detection and measurement of
various types of foreign material with special emphasis on poten-
tially harmful foreign material such as glass, metal, and stones. A
critical concern of the manufacturers of peanut products is the risk
of aflatoxin in the finished product.

The purpose of this paper is to describe the current U.S.
peanut grading and quality control system and how the program is


The Fresh Products Branch of the U.S. Department of Agri-
culture's Agricultural Marketing Service administers the peanut
grading program for U.S. peanuts. Through cooperative agreements
between the U.S. Department of Agriculture (USDA) and the peanut
producing states, the states employ peanut inspection personnel and
conduct the peanut grading program within each state. The State
Inspection Services serve as independent, impartial organizations to
make grade and quality determinations on peanuts. In order to
provide uniform peanut grading among all of the states, the Agri-
cultural Marketing Service (AMS) provides standardization of the
grading procedures used by State Inspection Services (hereinafter
referred to as the Inspection Service). The AMS also provides
training, licensing and federal supervision for the inspectors.

Domestic peanuts are graded at least twice by the Inspection
Service. The initial inspection takes place at the time the producer
markets the peanuts to the sheller (handler). At this stage the
peanuts are referred to as "farmers stock" peanuts which means
they have not been shelled or otherwise altered from their con-
dition at time of picking except for removal of foreign material,
shelled kernels and excess moisture. They are again inspected as
"milled" peanuts after going through the milling process of sizing,
cleaning and removal of shells for lots shipped as shelled peanuts.
Reinspection of milled peanuts is sometimes made by Federal or
Federal-State Inspectors at terminal markets outside the peanut
production area.

In the inspection of farmers stock peanuts the Inspection Ser-
vice does not specify peanut grade factors, but it is responsible for
developing procedures to make unbiased, dependable estimates of
grade factors. For example, it does not specify the amount of
damaged kernels allowed in edible peanuts, but it specifies the
sampling, subsampling, and sample processing procedures to be used
for estimating the amount of damaged kernels in a lot of peanuts.
In other words, the Inspection Service does not specify what grade
and quality factors will be determined but it specifies how they will
be determined.

The Inspection Service provides peanut grading services on a
fee basis and is self supporting. It will make grade or quality
determinations requested by any financially interested party, if the
party is willing to pay the cost of the determination and if
approved procedures are available to make the determination.

In order to carry out its responsibilities for making accurate
grade determinations for peanuts, the Inspection Service conducts
an ongoing research development and testing program in coopera-
tion with the Agricultural Research Service, USDA. This research
program has developed equipment and procedures to improve sam-
pling and grading operations. A continuing research program is
needed to improve the accuracy of the present grading system and
to adapt the system to the changing requirements of the peanut
industry. For example, in-line samplers for milled peanuts were
recently developed to meet the need for improved sampling in
modern peanut shelling plants; and an automated electronic moisture
meter was recently tested and approved for peanuts.


Agricultural Stabilization and Conservation Service (ASCS): The
ASCS-USDA is responsible for administering the USDA price sup-
port program for farmers stock peanuts. The quality factors for
farmers stock peanuts are designated by the ASCS in order to
determine their support price. Producers and commercial buyers of
peanuts use the grades as guidelines for trading. The level of
price support announced each year by the USDA is based on an
average ton of peanuts for each market type. The "average ton" is
determined by averaging the grade factors for all quota peanuts
marketed during the previous five crop years.

In addition to grade specifications for farmers stock peanuts,
the ASCS has established grade and quality requirements for pea-
nuts purchased from the Commodity Credit Corporation for export.
These requirements are designed to insure that export peanuts are
of acceptable quality and to protect the price support program for
quota peanuts produced for edible purposes in the United States.

Peanut Administrative Committee (PAC): An aflatoxin control
program for U.S. peanuts is administered by the PAC under provi-
sion of a USDA Peanut Marketing Agreement (Marketing Agree-
ment for Peanuts, 1986). The 18-member PAC consists of three
grower representatives and three sheller representatives from each
of the three peanut production areas (Virginia-Carolina, Southeast-
ern and Southwestern). Work of the committee is financially
supported by assessment of signers of the marketing agreement
shelterss) based upon the volume of peanuts they purchase.

Through PAC, shelters have accepted a major role in the afla-
toxin control program of the peanut industry (Dickens, 1977). They
attempt to channel aflatoxin-contaminated peanuts from the farm to
nonfood uses; to prevent aflatoxin contamination during storage,
handling, processing and shipment; to remove aflatoxin-contami-
nated kernels during processing; and to deliver aflatoxin-free
peanuts to the manufacturer. In order to achieve these goals the
PAC has specified grade and quality requirements for farmers stock
peanuts to prevent the edible use of those peanuts with high
concentrations of damaged kernels or aflatoxin and to prevent
storage of peanuts with high foreign material or moisture contents
that might be conducive to mold growth and aflatoxin production
during storage. For milled peanuts the PAC has specified grade
requirements for edible quality and has specified an aflatoxin
testing program that is described in a subsequent section of this

U.S. Standards for Peanuts: The U.S. Standards for milled peanuts
were developed by the AMS at the request of the peanut industry.
The following standards have been established: U.S. Standards for
Grades of Shelled Spanish Type Peanuts, U.S. Standards for Grades
of Shelled Virginia Type Peanuts, U.S. Standards for Grades of
Shelled Runner Type Peanuts and U.S. Standards for Grades of
Cleaned Virginia Type Peanuts in the Shell. Proposed changes in
the U.S. Standards must be published in the Federal Register with
an invitation for comment from interested parties.

Southeastern Peanut Association Grades: The Southeastern Peanut
Association has established a set of grades for trading purposes.
These grades apply only to shelled runner type peanuts (Milled
Peanuts Inspection Instructions, 1986).

Others: In addition to the requirements specified above, interested
parties may request information about the quality of a peanut lot.
The Inspection Service will provide the additional information if
approval is given by the applicant who has requested the grading
service and if the Inspection Service has the capability to make a
reasonably accurate estimate of the requested information. Addi-
tional costs for providing the information is charged to the app-
licant. For example, a count of pieces of foreign material and a
listing of the types of foreign material in a shelled peanut lot will
be shown on the grade certificate if requested by the applicant.


A detailed set of instructions for grading farmers stock peanuts
has been published by the AMS (Farmers Stock Peanuts Inspection
Instructions, 1986). Following is a brief step-by-step procedure
which gives a general description of the grading operations for
runner-type peanuts. The grading procedure is slightly different
for virginia-type peanuts, for spanish-type peanuts, and for valen-
cia-type peanuts. Details regarding these types of peanuts are
available in the AMS grading instructions cited above.

1. Take a sample from the lot. If the peanuts are in bags,
use the prescribed hand sampling procedure. If the peanuts are in
bulk, use the pneumatic sampler (Dickens, 1964) or the spout sam-
pler (Kramer, 1959).

2. Subdivide the sample to about 1800 g (not less than 1500 g)
with a riffle-type sampler divider for farmers stock peanuts.

3. Separate foreign material (FM) and shelled kernels (LSK)
from the sample with a sample cleaner and/or by hand. Determine
the % FM and % LSK based on the total weight of the sample.

4. Inspect all of the LSK for visible Aspergillus flavus mold
growth, and use a microscope to confirm the identification of mold
that appears to be A. flavus (Dickens and Satterwhite, 1971).

5. Pass a 500-g subsample of the pods (1000-g subsample if
the lot weighs over 10 tons) through the presizer (Dickens, 1962).

6. Shell the subsample in the sampler sheller (Dickens, 1962)
and determine the % hulls based on the weight of the subsample.
(Except for % moisture, all subsequent percentages are based on
subsample weight, which is either 500-g or 1000-g.)

7. Measure the percent moisture in the shelled kernels with an
approved electronic moisture meter.

8. Use the mechanical screen shaker to screen the sample of
kernels over a grading screen with 16/64 x 3/4-inch openings.

9. Divide the material that passed through the grading screen
into splits (kernel cotyledons and broken pieces of kernels that are
between 3/4 and 1/4 of a kernel) and other kernels (small whole
kernels and small pieces of kernels). Then divide the splits into
sound splits and damaged splits. Keep splits with freeze damage
separate from other damaged splits. Note: Inspectors are trained
and visual aids are available to assist in recognizing the various
types of damage found in farmers stock peanuts.

10. Pick out the splits that rode the screen and combine them
with the appropriate group of splits that passed through the screen.
Weigh the whole kernels that rode the screen and then separate
those kernels with visible damage. Keep kernels with freeze dam-
age separate from other damaged kernels.

11. Split the whole, sound appearing kernels from step 10 with
a kernel splitter-inspection belt (Dickens, 1961) and segregate
pieces of kernels with internal or concealed damage. Divide the
damaged pieces of kernels into the following three categories:
damage due to rancidity, mold and decay (RMD); freeze damage;
and damage due to other types of discoloration.

12. Use the weights of the various portions segregated in
steps 9-11 to calculate the % sound splits, % other kernels (% OK);
% damage splits, % concealed RMD, % freeze damage, % total
damage, % sound mature kernels (% SMK), and total % kernels.
Enter these data on the inspection certificate.

13. Examine all kernels from steps 9-11 for visible A. flavus
mold growth and use a microscope to confirm the identification of
mold that appears to be A. flavus. If one or more kernels with A.
flavus growth are found in this step or step 4, indicate the pres-
ence of A. flavus mold on the inspection certificate.


A detailed set of instructions for grading milled peanuts has
been published by AMS (Milled Peanuts Inspection Instructions,
1986). This set of instructions also includes PAC and ASCS re-
quirements for milled peanuts, peanut sheller association trading
rules, official rules of the Southeastern Peanut Association, U.S.
Standards for peanuts, and instructions for sampling peanuts for
aflatoxin. Following is a brief step-by-step procedure which gives
a general description of the usual sampling and grading operation
for a lot of U.S. No. 1 Virginia peanuts. The grading procedure is
slightly different for other grades of virginia-type peanuts and for
other types of peanuts. Details regarding the grading procedure
for those peanuts is available in the AMS grading instructions cited

1. Take sample from the lot. The sample should be taken
with an Inspection Service approved in-line automatic sampler.
When peanuts are packaged in sacks, a sample may be taken from
the sacks with the prescribed hand probe procedure. In special
cases samples may be taken from large cartons with the pneumatic
grade sampler. A primary sample of approximately 160 pounds is
taken from the lot. Note: All lots of milled peanuts must be
"positive lot" identified by means of lot-numbered tags sewn in the
closure of bags or by means of Inspection Service seals on bulk

2. Pass the 160-pound sample of peanuts through an Inspec-
tion Service approved rotating divider that subdivides the sample
into three 48-pound samples and a 16-pound sample for grade
analysis. (Use of the three 48-pound samples for aflatoxin tests is
discussed elsewhere in this report.)

3. Pass the 16-pound grade sample through an Inspection Ser-
vice approved riffle-type divider for shelled peanuts to obtain an
analytical sample. The required size of the analytical sample for
foreign material determinations varies from 2000 g for a 23,000-
pound lot to 8000 g for lots weighing up to a maximum of 200,000
pounds. The size of analytical sample required for other grade
determinations is one-half that required for foreign material deter-
minations. (At the request of the applicant, one of the 48-pound
aflatoxin samples can be sorted to determine the % foreign material
in the lot.)

4. Remove all foreign material from the large analytical sample
and compute the % by weight of foreign material to the second
decimal place. If unusual foreign material such as glass or metal is
found, make a note of this on the grade certificate. If requested
by the applicant, report the piece count and kinds of foreign
material found.

5. After foreign material is removed from the large analytical
sample, use the riffle-type divider to subdivide the sample to the
sample weight required for subsequent grade determinations.

6. Measure the moisture content of the sample with an
Inspection Service approved electronic moisture meter.

7. Count the kernels in a 2-pound portion of the sample to
determine the kernel count per pound. An electronic counter
approved by the Inspection Service may be used for this purpose.

8. Use the mechanical screen shaker to screen the sample over
a grading screen with 15/64 x 1-inch openings.

9. Examine the kernels that rode the screen to determine the
weight of kernels that are "unmistakably of another variety and
which stand out in conspicuous contrast to the majority of the
kernels in the sample." Then separate all of the whole kernels into
the following categories: sound kernels, kernels with visible dam-
age, kernels with minor defects, and unshelled kernels. Add split
and broken kernels that rode the screen to the portion that passed
through the screen. Note: Detailed descriptions of damage and
minor defects are provided by the AMS instructions for grading
milled peanuts and by visual aids developed by AMS. Special
efforts are made by the Inspection Service to assure uniform scor-
ing of defects by holding formal classroom and on-the-job training
for all inspectors.

10. Sort the portion that passed through the screen into the
following categories: sound split and broken kernels; split and
broken kernels with damage; split and broken kernels with minor
defects; sound whole kernels; whole kernels with damage; whole
kernels with minor defects; and unshelled kernels.

11. Calculate the required grade factor percentages and com-
plete the inspection certificate.


The PAC indemnifies sellers for most of the losses related to
aflatoxin contamination in lots of edible peanuts which meet grade
requirements. PAC regulations prohibit the sheller from negotiating
the sale of peanuts on the basis of aflatoxin content. The buyer
(manufacturer) is guaranteed that the peanuts will test "negative"
(not more than 25 parts-per-billion) by the official PAC aflatoxin-
testing program, but the sheller is not allowed to make any other
specification in regard to aflatoxin. Manufacturers who complete
tests within 36 hr after the lot is sampled by the Inspection Ser-
vice may accept lots of peanuts on the basis of their own aflatoxin
analyses, but only those lots which test positive in PAC approved
laboratories may be returned to the sheller because of aflatoxin

All shelled peanuts sold for human consumption must be
positive-lot-identified and sampled by the Inspection Service for
aflatoxin tests. As previously mentioned, three 48-pound samples
are taken from the lot of peanuts at the same time the grade
sample is taken. One 48-pound sample is comminuted in a sub-
sampling mill (Dickens and Satterwhite, 1969; Dickens, et al., 1979)
and a 1100-g subsample is sent to a PAC approved laboratory.
(Except for two independent laboratories, PAC approved labora-
tories are operated by federal or state government). The entire
1100-g subsample is blended with water to finely comminute the
peanut particles and make a water slurry. Aflatoxin is extracted
from a weighed portion of the water slurry with a methanol-water
solution and duplicate 50-ml portions of the methanol-water extract
are analyzed for aflatoxin (Whitaker, et al., 1980; Inspectors
Instructions for Aflatoxin, 1983). The two independent determina-
tions of aflatoxin concentration by thin layer chromatography
(TLC) are averaged. If the average is 16 parts-per-billion (ppb)
or less, an "aflatoxin-negative" certificate is issued and the lot is
accepted. If the average is more than 75 ppb, the average concen-

tration is shown on the certificate, and the lot is rejected.
Otherwise, a second 48-pound sample is analyzed by the same
procedure, and the aflatoxin determinations from the first and
second 48-pound samples are averaged. If the average of the four
determinations is 22 ppb or less, an aflatoxin-negative certificate is
issued. If the average is 38 ppb or more, the average concentra-
tion is shown on the certificate, and the lot is rejected. Other-
wise, a third 48-pound sample is analyzed, and when the six
determinations average 25 ppb or less, a negative certificate is
issued. Otherwise, the average concentration is shown on the
certificate and the lot is rejected. When requested, the results of
all aflatoxin analyses are made available to the buyer of the

Whitaker and Dickens (1979) have estimated the probability of
accepting lots with various concentrations of aflatoxin when the
official PAC testing program is used. As indicated previously, the
manufacturer may elect to conduct his own 36-hr aflatoxin analyses
in lieu of the official PAC aflatoxin tests. In this case, the
Inspection Service will provide the manufacturer's laboratory with a
1100-g subsample from the first 48-pound sample and hold a
subsample in reserve. After analysis of his subsample, the manu-
facturer may accept the lot or request the official PAC test
outlined above. If requested, the Inspection Service will send the
manufacturer a 1100-g subsample in addition to each 1100-g
subsample sent to the PAC approved laboratory. These subsamples
may be analysed by the manufacturer for quality control purposes.

Manufacturers may appeal official PAC aflatoxin tests if
positive-lot identification has been maintained for the lot. The
Inspection Service or AMS is required to take a 144-pound sample
from the lot. The 144-pound sample is comminuted, and duplicate
analyses are made on three 1100-g subsamples. If the average of
the six determinations is 25 ppb or less, the lot must be accepted.
If the average is more than 25 ppb, the manufacturer may reject
the lot. The manufacturer pays all costs of appeal testing, and
there is no limit on the number of appeals made on a lot.

Lots of shelled peanuts which test positive for aflatoxin may be
remilled or blanched in an attempt to remove the aflatoxin.
Remilling may include the following procedures: (a) screening to
remove small kernels, (b) treatments to remove low-density kernels
and foreign material, (c) electronic color sorting to remove dis-
colored kernels, and (d) hand picking to remove discolored kernels.
The blanching process consists of removing the skin or testa from

the kernels followed by color sorting and hand-picking to remove
the discolored kernels and those kernels that retain their skins.
After blanching or remilling, the lots are considered to be new lots
and are subjected to the PAC aflatoxin testing program outlined
above. There is no limit on the number of times a lot may be
remilled, and the lot may be blanched following remilling. Even-
tually, all lots which fail to pass the PAC aflatoxin testing program
must be restricted from food or feed except for the oil which is
aflatoxin-free after proper refining.


The organized grading system administered by the Inspection
Service provides the peanut industry with an excellent opportunity
to incorporate an improved quality control program into the mar-
keting system for peanuts. Few other commodities have such an
organized grading system in place. In order to take advantage of
this opportunity, important peanut quality factors must be iden-
tified, and practical ways to make objective measurement of those
quality factors during the grading operation must be developed.
Finally, those segments of the peanut industry with a financial
interest in the quality measurements must take the initiative to
arrange for the Inspection Service to make those measurements.

The aflatoxin sampling program for shelled peanuts and the
examination of farmers stock samples for A. flavus mold are
excellent examples of the response of the Inspection Service to the
peanut industry's need for an aflatoxin control program. The
recently developed alcohol meter to detect undesirable flavor and
freeze damage in farmers stock peanuts (Dickens, et al., 1986) is an
example of a quality control procedure that could be incorporated
into the grading system if the industry requested that it be used.
Other quality control procedures are under development. The
benefit/cost ratio for each quality control procedure should receive
careful evaluation by the peanut industry. When the important
quality factors are incorporated, the peanut grading system will
provide an excellent quality evaluation program for the marketing
of U.S. peanuts.


The use of trade names in this publication does not imply
endorsement by the United States Department of Agriculture of the
products named, nor criticism of similar ones not mentioned.


Dickens, J. W. 1961. Kernel splitter and inspection belt for
peanuts. Marketing Research Report No. 452. U.S. Govern-
ment Printing Office, Washington, DC.

Dickens, J. W. 1962. Shelling equipment for samples of peanuts.
Marketing Research Report No. 528. U.S. Government Printing
Office, Washington, DC.

Dickens, J. W. 1964. Development of a pneumatic sampler for
peanuts. Trans. of Am. Soc. Agric. Engr. 7:384-387.

Dickens, J. W. 1977. Aflatoxin control program for peanuts. J.
Am. Oil Chem. Soc. 54:225A-228A.

Dickens, J. W. and J. B. Satterwhite. 1969. Subsampling mill for
peanut kernels. Food Technology 23:90-92.

Dickens, J. W. and J. B. Satterwhite. 1971. Diversion program for
farmers stock peanuts with high concentrations of aflatoxin.
Oleagineux 26:321-328.

Dickens, J. W., A. B. Slate, and H. E. Pattee. 1986. An electronic
meter to measure the concentration of alcohols and aldehydes
in peanuts. Proc. Amer. Peanut Res. and Educ. Soc. 18:34.

Dickens, J. W., T. B. Whitaker, R. J. Monroe, and J. N. Weaver.
1979. Accuracy of subsampling mill for granular materials. J.
Amer. Oil Chem. Soc. 56:842-844.

Farmers Stock Peanuts Inspection Instructions. 1986. U.S.
Department of Agriculture, Agricultural Marketing Service,
Fruit and Vegetable Division, Washington, DC 20250.

Inspectors Instructions for Aflatoxin. 1983. U.S. Department of
Agriculture, Agricultural Marketing Service, Fruit and Vege-
table Division, Washington, DC 20250.

Kramer, H. A. 1959. Spout-type automatic sampler for farmers'
stock peanuts. Marketing Research Report 353, U.S. Govern-
ment Printing Office, Washington, DC.

Marketing Agreement for Peanuts. 1986. Peanut Administrative
Committee, P. O. Box 18856, Atlanta, GA 30326.

Milled Peanuts Inspection Instructions. 1986. U.S. Department of
Agriculture, Agricultural Marketing Service, Fruit and Vege-
table Division, Washington, DC 20250.

Whitaker, T. B. and J. W. Dickens. 1979. Evaluation of the Peanut
Administrative Committee testing program for aflatoxin in
shelled peanuts. Peanut Sci. 6:124-126.

Whitaker, T. B., J. W. Dickens and R. J. Monroe. 1980. A water
slurry method of extracting aflatoxin from peanuts. J. Amer.
Oil Chem. Soc. 57:269-272.

Shelling Edible Peanuts for Quality
and Marketability

G. Max Grice

This paper is limited to the shelling of runner and spanish

In order to have a good quality and marketable peanut after
shelling, the following factors must be considered: field produc-
tion, the harvesting of the crop, and drying and handling of the
peanuts at the buying point. During field production, the producer
must have used good practices for the growing and harvesting
periods. The harvested peanuts must then be dried properly, for
which the accepted procedure is to never exceed 950F (350C) or 8
to 110C above ambient conditions, based on the relative humidity,
whichever is lower.

Assuming that all of the above processes have been done
correctly and the product is of good quality, the shelling process
may begin.

The definition of the term "Shelling for Quality and Marketa-
bility" is the ability to mill farmers stock peanuts into a finished
product that--l) is free of foreign material, 2) has the desired
count per ounce, 3) rides and falls through the prescribed screen
for that grade, 4) meets USDA and customer specifications on grade
factors, 5) is free from aflatoxin and 6) has a good flavor. In
order to accomplish the above and produce a good quality product
the shelling process encompasses many operations, including
receiving, precleaning, shelling, screening, separating, sorting,
sizing and packaging.

In the receiving operation, the facilities such as the dump pits,
elevators, sand screens, etc. are properly maintained and engineered
as to not do damage to the peanuts.

The precleaning operation is one of the most important steps in
the shelling process when shelling for quality. This operation
encompasses several steps such as destoning, aspiration and screen-

ing. The destoning removes the large stones, clay balls, and all
heavy foreign material from the peanuts. The product is then
aspirated, and light material such as sticks and light peanuts are
separated and sent over the top stick deck for separation. This
aspiration should pull about 30 to 40 percent of the peanuts up to
the top deck of the precleaner. The peanuts then drop through a
louvered screen, and a rug pulls the sticks off the end of the
screen and separates them from the peanuts. The heavy peanuts go
over a bottom screen which has slots large enough to let the loose
shelled kernels, small stones, clay balls and dirt fall through, and
the farmers stock peanuts ride the screen. These peanuts are then
mixed back with the peanuts from the top screen. At this time,
most shelters use additional stick machines and stoners to insure
proper cleaning of the peanuts. Samples are taken at this stage of
the shelling process to insure a proper cleaning standard has been

The peanuts, hopefully free from all foreign material, are sent
through a presizing operation before going to the shelters or they
are conveyed directly to the bins over the sellers. This operation
varies from sheller to sheller. The shelling operation is accom-
plished by baskets and sheller bars. The baskets in the lead
sheller are spaced so the larger peanuts will stay in the basket
until the sheller bar, set at desired distance from the basket,
cracks the shell and allows the kernel to fall through the basket to
a shaker below, along with the small unshelled kernels. The shaker
then separates the unshelled peanuts from the shelled peanuts and
hulls are aspirated and removed. The shelled whole round kernels
are separated from the splits and small kernels through aspiration
to bins above the gravity operation, commonly referred to as
'gravities'. The unshelled peanuts go to the secondary or return
sellers, and the same process that we just spoke of takes place
again, the shelling, shakers, etc. Samples are drawn out of each
sheller to determine the amount of nubs unshelledd peanuts), sound
whole kernels and splits. By doing this, it can be determined if
the sellers are set correctly.

The peanuts are now shelled except for some of the small nubs
which go on to nub shelters. This is the final shelling stage.

The gravity operation is a very key operation in obtaining a
high quality, clean, edible shelled peanut. This is one operation
that should be operated and monitored properly at all times.

After the gravity operation, shelled peanuts are moved with
easylift elevators through shelled-goods stoners, then to bins
located above the electric sorting eye machines. Foreign material,
damaged or discolored kernels are rejected by the 'eyes'. Separa-
tion in this area is critical to turning out high quality shelled
peanuts. Many sellers handpick after the 'eyes' to assure the
quality of the shelled peanuts. The pickouts go to oilstock and the
accepted product goes to the sizing area where the peanuts are
sized into the edible grades. Runner edible grades are Jumbos,
Mediums, No. Ones, Small No. Ones, Splits and Oilstock. Spanish
edible grades are Jumbos, No. Ones, Small No. Ones, Splits and
Oilstock. These are the basic sizes for the runners and spanish
types, but of course there are many special cuts or sizes made for
different manufacturers. Samples should be taken of the different
grades or sizes during the sizing operation to assure the proper
counts and quality factors set for that particular grade.

After the sizing operation, the peanuts are conveyed to bins
above the packaging operation. Peanuts are usually packed in 110-
pound burlap bags or in 2000-pound or 2270-pound boxes. Some
customers use bulk lots for bulk trucks or hopper cars. During the
packaging operation, the Federal State Inspection Services takes a
sample (160 pounds) of each lot which is divided into sub-samples
for grading and aflatoxin testing to assure the quality of peanuts
to customers and/or consumers.

Quality assurance by sellers usually consists of taking one bag
out of each lot and actually counting pieces of foreign material
that might be left in the peanuts. From this sample final checks
on amount of splits, sizing and counts, and a taste test are

After completion of these quality checks, the peanuts are
stored in cold storage at a temperature of 2-50C and 55-70% RH
until ordered out by the customer.

Peanut Blanching--Processing, Utilization, and
Effects of Quality and Product Shelf Life

Wilbur A. Parker

The term "blanching" in peanut processing means the removal
of the testa or seed coat from shelled raw or roasted kernels. For
raw peanuts this is usually done by partially drying the peanuts to
loosen the seed coat and then processing the kernels through
various types of blanchers which subject the kernels to thorough,
but gentle, rubbing type friction action, followed by aspiration.
This process not only removes the seed coat but significantly
reduces dust, mold contamination and other foreign materials.
Roasted peanuts are processed immediately through the various
blanchers without additional drying and then processed through
split nut blanchers to produce a maximum level of splits. Removal
of the seed coat produces a weight loss of 3.0 to 3.5% for the
shelled peanut kernels depending upon the peanut variety and grade
being processed.

The spin and buff blanching operations at Seabrook Blanching
Corporation typically involve the following processing steps.

1. Thorough incoming quality control tests on the shelled
2. Extensive pre-cleaning steps that involve scalping, deston-
ing, gravity separation, etc.
3. Cutting, which involves processing each kernel through
specialized custom equipment that places a microscopic cut
along each longitudinal axis of the kernel to facilitate
removal of the seed coat after the drying process. This
process is patented by Seabrook, and contributes to a more
efficient whole-nut blanching process that results in less
4. Drying by carefully controlling the time and temperature.
5. Cooling with a combination of refrigerated and ambient air.
6. Seed coat removal, for whole-nut blanching, involves var-
ious blanching processes that include spin or buff blanchers
depending on the end product use.
7. Electronic sorting to remove damaged and defective kernels
and foreign materials.

8. Manual inspection of the sorted kernels.
9. Packaging in a variety of sizes from 15.9 kg boxes to 909
kg bulk bags or boxes.
10. Extensive quality testing at all stages of processing and on
the final product.

Two other blanching processes are in general use in addition to
spin and buff blanching. These are split and water blanching, and
generally involve the same processing steps as spin and buff
blanching. Split blanching is the most commonly used blanching
process to remove aflatoxin contaminated peanut kernels from
contaminated lots which fail to meet the Peanut Administrative
Committee (PAC) guidelines.


Each blanching process has unique utilization applications.
Typical utilization applications and benefits for each blanching
process are as follows.

Spin Blanching:

Oil roasting with reduced foaming
Extended shelf life of roasting oil because of less peanut meal
and fines
Premium cocktail peanuts
Removal of damaged peanuts and foreign material
Partially defatted flours

Buff Blanching:

Surface abrasion for dry roasting
Pre-roast treatment for color solution
Confectionary coatings
Removal of damaged peanuts and foreign material
Reduced calorie peanuts

Split Nut Blanching:

Cleaned and blanched for removal of damaged kernels and for-
eign materials by extensive electronic sorting and gravity
For peanut butter processing where the kernels are first
roasted and then blanched.

Peanuts for confectionary products, especially those that are
coated and have a high consumer risk from foreign
Split blanching is typical for lots that fail to meet the PAC
guideline of 25 ppb for aflatoxin content. Such lots are
split nut blanched for removal of moldy, damaged kernels
to meet PAC requirements for aflatoxin content prior to
interstate shipment.

Water Blanching Extra large virginia peanuts:

Prolonged storage of blanched peanuts at ambient conditions--
virtually free of insect contamination, including eggs.
Use in confectionary and bakery products requiring a special
Use in dairy (ice cream) products requiring special texture.
Use in gourmet and oriental foods.
Manufacture of "blistered" peanuts.


Typical specifications for spin and buff blanched peanuts are as

Physical Specifications Chemical Specifications

Whole Kernels 80-85% Moisture 4.5-5.0%
Split Kernels 15-20 Oil 49-51%
Rednose1 3.0% Iodine Value 95
Unblanched2 1.0% Free Fatty Acids 0.30%
Damaged Kernels 1.0% Peroxide Value 5.0 meq
Aflatoxin 5.0 ppb

1. Seed coat at 1/4 inch or less, largest diameter.
2. Seed coat 1/4 inch or greater, largest diameter.

The specifications for split blanched peanuts are typical of those
values given above with the exception that the split kernels run
between 96 and 99% and the whole kernels run between 1 and 4%
on lots that represent good split, blanched product.


Shelf life, as measured by peroxide value and flavor, shows little
or no change when compared to the redskin peanuts over a period
of 50 weeks. Several tests on Extra Large virginias, Jumbo and
Medium runners support this shelf life. Furthermore, numerous
tests on export lots, taking several months in transit and storage
show no change in chemical or flavor quality.


Extensive quality control tests are run on both the incoming
shelled product and the blanched finished product to produce and
maintain high quality. Quality tests that are normally included in
the production of blanched peanuts are described in the following

Physical Tests: Physical tests include cutting, which is a dye test,
moisture content, splits, rednose, unblanched, meal and fines,
damaged kernels, metal contamination, foreign material by count
and roast quality (kernels with excessive brown spots that are
unacceptable for salted nuts).

Chemical Tests: Chemical tests include oil content, free fatty
acids, peroxide value, aflatoxin, pesticide residues, dimethyl sulfide,
extraneous materials, and moisture content.


Over the last 40 years, blanching has evolved into a continuous,
high capacity progress, using both the water and heat systems.
Blanched peanuts have been the source of several new products in
the United States, Europe and Japan. In particular, the blanching
industry has provided a method for the peanut industry to upgrade
millions of pounds of peanuts that failed to meet grade standards.
Using state-of-the-art equipment and process controls, blanched
peanuts have a shelf life of 9 to 12 months, enabling long term
storage and world-wide exports.

Peanut Quality: The Needs of
International Users

Douglas T. Ross

It is an honor to be invited to join such an august body of
scientific and technical people, all with one aim in mind--to
improve the production, handling and processing of the lowly but
beautiful peanut.

If one were to criticize any part of this impressive program, it
would be to note a major omission. Only one of your 120 presen-
tations mentions the final judge of our product. I would like to
make amends for this and tell you something about that person who
makes all our occupations and investments possible--the consumer.

On behalf of the international buyers and marketers of your
very fine peanuts, let me tell you some of the key issues we
encounter in finding peanut (and other) products which best fit
consumer needs. International marketing requirements for peanut
products probably vary only in degree of emphasis from those of
the domestic market.


Know your competition. All the following data have been
established on the basis of percentage of market share.

The ma ior producing countries, which are also regular active ex-
porters, are India, which is the largest producer of peanuts with
33% of world production; China, which in 8 years has doubled
production from 13% of the world production to 26%; and the
United States with a fairly flat 8-10% of world production.
Argentina follows with a flat 2%.

The major exporting countries are the United States, whose
world market share is showing steady growth, and is currently
about 40% of all peanuts exported; and China, which rose from
nowhere 8 years ago to a high of almost 30% in 1980, and has a
steady and positively trending 14-15% in recent years. These
countries are followed by Argentina and India.

U.S. Share of Shelled Exports. 1982 vs 1985:
5 Key Importing Countries

Comparing 1982 with 1985, the U.S. export support strategies
have been paying good dividends with share increases for the
United States, particularly in the top five importing countries.
These are the United Kingdom, Canada, Japan, Netherlands, and
West Germany. Your market share is greater in Canada, where you
continue to dominate with well over 90% of our market. In the
other four countries your market share is growing well.

U.S. Exports to Canada

In terms of total trade, Canada continues to be your number one
trading partner. We are also historically your largest single export
market for shelled and unshelled peanuts. For very many years, we
have enjoyed either first or second place with a consistent and
reliable 20% or so share of all the peanuts you export.

Total Canadian Peanut Imports

In fact, apart from the drought year, over the last 9-year
period, over 90% of all the peanuts we imported into Canada came
from the U.S.

We are also consistently one of your largest customers for
peanut oil, although it accounts for less than 2% of our total usage.
Its usage in Canada is depressed by the availability of domestic and
other U.S. oils that cost about half the delivered Canada price for
peanut oil.

Annual Peanut Product Consumption--U.S. vs Canada vs UK

Peanut butter consumption in Canada and the United States has
reached a mature stage, roughly equivalent in the two countries to
a level of 3 pounds per person annually. No other countries use
peanut butter at anything close to that level. However, your
export strategies are working well, and we are starting to see some
significant growth in usage in the countries in which you are most
active, particularly the Netherlands and the United Kingdom.


Let me present you with a hypothesis: "The United States is
the largest exporter of peanuts, with the highest quality and many
years of leadership. She cannot be shaken from that position."

That is a very questionable hypothesis. The mighty can fall if
they don't work hard to prevent it. India enjoyed a 40% share of
world exports until 1976; now it's only a fraction of that level.
Furthermore, their peanuts are not considered to be nearly as
reliable and as of such high quality as American peanuts. That
situation could change. Nigeria lost its major share of world
exports in the 70's because of bad crops and lack of attention to
quality control. That situation also could change.

What are the major threats to the United States and to the
world export market for peanuts? Again let us think in terms of
the ultimate judge--the consumer. The public taste is fickle. It is
difficult to accurately predict the speed and severity of change.
Think about the major public preference shift from red to white
wines. It happened in the western world far more quickly than
most vineyards could switch their grapevines. In March of this
year, Britain's largest retailer announced the introduction of
comprehensive nutritional labeling and a program to remove all
nonessential additives from their 3000 private label products.


Peanuts and peanut butter have a great image among consumers.
But with modern technology, knowledge and, above all, instant
communications, the image of a product could change, possibly
irreversibly, overnight.

Situations which could change that image might arise from
certain quality characteristics of peanuts. There are no immediate
solutions, but I hope the members of APRES will accept the
challenges and find the answers. We need to address the following

1. Aflatoxin

The tolerance level in the United States is 20 ppb; in Canada it
is 15 ppb; in most EEC countries it is 5 ppb or even lower. There

are countries which require that be no measurable aflatoxin. You
should not feel comfortable at current U.S. levels. Neither should
we in Canada feel comfortable at 15 ppb.

All of us in the growing, handling and processing business,
particularly in North America, have a tendency to feel that the
aflatoxin levels we allow are something that the world will have to
live with. Let me assure you from dealing with consumers and
observing some of the investigative media, that aflatoxin could
become a major issue overnight, and we would lose a significant
proportion of our market.

A recent National Peanut Council Chairman set as an objective
the elimination of aflatoxin, within 3 years, in peanuts being
processed into human food. That is the primary quality issue and
challenge to this group.

2. Chemical Residues

How can you grow good peanuts with fantastic yields if you
don't use chemicals? We don't know, but we must seek alterna-

What we do know is that chemical residues in foods is becoming
a big issue. So far, our industry has been fortunate in not being
front and center when this issue has been raised by the media.
Yet, to those of you who are involved with the research production
and application of chemicals, I urge you to think of the potential
destructive forces that can come into play at the public level. One
adverse report can lead to syndicated bad reports, and the destruc-
tion of a product category virtually overnight.

3. Fat Content

Have you noticed the growth of light beer, light entrees, and
light dairy products? The public taste is swinging towards foods
and beverages that are perceived to be lower in calories and
perceived to be healthier.

Peanut products have a relatively high fat content. Excellent
nutritive sources as they may be, they certainly don't fit into the
category of "light" products. The excellent arguments we could
advance about low cholesterol, and saturated vs unsaturated fats in

peanuts and peanut butter, tend to be rather academic. "Light is
right" with today's consumer. This could have a detrimental effect
on our peanut consumer market categories.

These are potentially the three key quality-related threats to
the future health of our industry and the biggest challenge to this
Society. But there are others--more specific quality issues that
research and industry tackle all the time. The objective is to
further improve our products and strengthen their image in the
eyes of the buyer and, ultimately, the consumer.

Quality Issues for the Manufacturer

The manufacturers' and importers' concerns continue to be:

-excessive foreign material
-size inconsistency
-the need to provide a reliable, consistent product.

Failure to address these concerns results in additional processing
costs and difficulties in achieving quality levels.

Quality Issues for the Marketer

The marketing groups, who are closest to the consumer, are

-improved and specific flavor characteristics
-maintenance of a good flavor and aroma throughout
processing and on the shelf
-maintenance of a reasonable shelf life
-improved appearance
-and, most importantly, product distinctiveness.

The Beautiful Peanut

"Beauty is in the eye of the beholder." At all stages of peanut
development, production, processing and marketing, it is essential
that everyone remembers the consumer is the beholder--the final
judge of acceptability of our products. The total focus of quality
must relate to fulfilling consumer needs in every way.

Evaluation of Peanut Flavor Quality

Michelle M. Fletcher

One of the most critical indicators of peanut quality is flavor.
The ultimate judge of this property is the consumer when he or
she bites into that roasted peanut snack or peanut butter sandwich.
If the product doesn't taste right, the consumer will respond by
refusing to purchase the product. It is therefore important to
monitor the flavor of peanuts used in foods. This paper reviews
factors affecting peanut flavor perception and the Critical Labora-
tory Evaluation of Roasted Peanuts (CLER) method for judging
peanut flavor quality.

While there are several established sensory methods used for
flavor evaluation of foods, the CLER method is the only sensory
method designed specifically for peanuts. A CLER score is a
numerical value of the relative organoleptic quality level of a given
sample of roasted peanuts. The sample size used is 20 peanuts,
each scored individually. The scores for each peanut are added
together for the final score, which ranges from 0 to 100.


Flavor is an important aspect of peanut quality, but it is also
difficult to measure, as there are many factors influencing an
individual's perception of flavor and texture. The subjectivity in
judging peanut flavor may be reduced by controlling conditions
affecting individual flavor perception. The original CLER method
has been redesigned to provide better control over variables
affecting sensory perception. Some of the key factors to control
in evaluating peanut flavor quality are: (1) degree of roast, (2)
roaster type and conditions, (3) sample presentation, and (4) the
panelists' training.

The point at which peanuts stop roasting is an important
variable to control. A peanut sample roasted to different intensi-
ties will evoke different flavor responses for a given panelist. By
presenting samples with a narrow range of roast levels, somewhere
in the middle between under and overroasted, these individual

biases can be reduced. For example: suppose an individual prefers
a darker roast. If part of the same peanut sample is roasted to a
medium roast, and part to a darker roast, and presented to this
person, he is going to score the darker roasted sample higher in
peanut flavor. The objective of maintaining control over the roast
intensity is to avoid this type of misleading flavor response.

Another variable to control in evaluating peanut flavor quality
is the type of roaster used to prepare the peanut sample. It is
important to use the same roaster, roasting process, and roasting
conditions in preparing samples to be compared to one another.
Each roaster type has a distinctive heat transfer rate and produces
different degrees of roast evenness. Peanuts heated in a microwave
will be exposed to a different treatment than peanuts fried in
vegetable oil. For comparative evaluations of peanuts, the same
operating conditions should be maintained in the roaster. Specifi-
cations should be set and followed for: (1) temperature setting of
heat input, (2) sample size in weight or volume, (3) approximate
roasting time, (4) type and quality of oil used for fryers, (5) sample
bed depth, for static bed roasters, (6) speed of rotation, for
rotisserie roasters, (7) air velocity, if applicable, (8) method of
cooling, (9) time and temperature required for cooling.

It is critical to maintain control over the time elapsing
between the period when the sample has been prepared (roasted and
cooled), and the time of sample evaluation. When comparing
samples, the amount of time passing between preparation and
evaluation should be equal for each sample. As the sample ages
and is exposed to the atmosphere at room temperature, reactions
occur which may lead to development of rancid notes in the
peanuts. Heating reduces the shelf-life of the oil component of the
peanut by destroying natural and antioxidants. Peanuts in roasted
form are more susceptible to oxidative rancidity than peanuts in
raw form. This type of reaction may change the evaluator's
perception of fresh, stale, and rancid attributes in a roasted peanut
sample. Other factors to control in presenting the sample include:
(1) temperature of sample, (2) size of sample (one peanut vs. many
peanuts vs. ground peanuts), and (3) appearance or color of sample.

The individual evaluating the sample influences the flavor
perception response. A trained panelist should more readily
recognize, identify, and quantify peanut flavor character notes than
an untrained panelist. A non-smoker should be more sensitive to
taste than a person who smokes. Cleanliness of palate is necessary
so the panelist can focus on the sensory evaluation of the peanut

sample only. To accomplish this while tasting peanut samples,
rinsing between samples with warm (490C) water is advised. The
proximity of the other panel members may influence the amount of
discussion of the sample's characteristics. For the CLER method, it
is best to separate panel members during the evaluation to prevent
interference with scoring caused by interactions between panelists.


The CLER method of evaluating peanut flavor was originally
developed in the early 1960's by CPC International, as a means of
monitoring and controlling the flavor of peanuts used in Skippy
peanut butter. It was approved by the Peanut Quality Committee
of the American Peanut Research and Education Society (APRES) in
1970 (Holaday, 1971). The procedure entails roasting a peanut lot
sample, tasting 20 individual peanuts, and scoring each peanut for a
final rating of 0 to 100. The peanuts are characterized as having
good peanut flavor, low peanut flavor, low level off-flavor, or bad
off-flavor. The panelists select the term which best describes the

Choosing one of these categories involved some degree of guess
work on the panelists' part. This is because it is possible for a
peanut with a low level of off-flavor to be equally low in peanut
flavor. A peanut with a high peanut flavor will, by definition, be
low in off-flavors; a peanut with low peanut flavor may have some
degree of off-flavors. Consider the original CLER scoring system
shown in Table 9.1. For each peanut, good peanut flavor = 5, low
peanut flavor = 3, low level off-flavor = 1, and bad off-flavor = 0.
Two different panelists may perceive the same flavor notes in a
peanut, but choose to describe the flavor differently. One may
score the sample as having low peanut flavor with a score of 3
points; the other may describe it as having low levels of off-flavors
with a score of 1 point. This arbitrary selection factor contributes
to the variability of the method.


The CLER method was recently modified to improve the
original procedure. The revised CLER method is similar to the
former CLER method because it requires the evaluation of 20
roasted peanuts per sample. Because conditions are more con-
trolled, the new CLER method is considered a more reliable

Table 9.1. Original Critical Laboratory Evaluation of Roasted
Peanuts (CLER) Scoring System Form.


Peanut No.:




- 1 I t t + f--I

Good Peanut

Low Peanut
----- _- ----- --__-7/
Low Level
__ __-----------------_//



SCORE = 100 (5 x BOF) (4 x LLOF) (2 x LPF)

indicator of the sensory characteristics of a given peanut sample.
Major changes include a new sample preparation procedure, flavor
attribute definitions, and a different scoring system.

The procedure for the revised Critical Laboratory Evaluation of
Roasted Peanuts (CLER) Method is as follows.


1. Farberware Electric Roaster Model 355, (Farberware, 1500
Basset Avenue, Bronx, NY 10461) installed with Watlow digital
temperature controller, Series 808 or equivalent (Watlow Co.,
1265 East Sarborn, Winona, MN 55987).

. i I I I 1 I I

2. Modified Roaster Cover Drill 16 evenly spaced holes of 1/4"

3. Stainless Steel perforated distribution baffle for Farberware
Roaster cylinder. Fabricate to following dimensions: 6" diam-
eter top, 4 3/4" diameter bottom, 7 3/4" length.

4. Olde Tyme Peanut Butter Mill, (Olde Tyme Food Products, East
Long Meadow, MA 01028) or equivalent.

5. Low temperature incubator, Fisher Model 307, (Fisher Scien-
tific, 50 Fadem Road, Springfield, NJ 07081) or equivalent.

6. 12" x 18 1/2" stainless steel tray.

7. Oven mitts.

8. Stop watch.

9. Stainless steel bowl, 1 1/2 quart capacity.

10. Gardner/Neotec Colorgard System, Model 1005 Colorimeter,
equipped with a 38-mm viewpoint aperture, and custom
program in peripheral Epson, HX-20 data terminal, or equiv-

11. Standard plates, Gardner/Neotec (black and white tiles).

12. Plastic petri dishes, Sargent-Welch No. 526026KA (100 x 15) or
No. S26026-10AA (60 x 15).


A. Sample Preparation

1. Weigh 550 + 1 grams of peanuts into a stainless steel bowl.

2. Transfer the peanuts into the glass cylinder of the roaster.
Insert the baffle so that it touches the bottom of the

3. Cover the cylinder and place the cylinder over the circular
base of the roaster.

4. Swing the locking arm over the cover. Turn the knob of
the locking arm to the closed position. For a proper
closure, it may be necessary to remove the gasket from the
cylinder cover.

5. Set the heat input by pushing in the setting knob and
turning to 450 + 10F.

6. Turn on unit. Start timer. The glass cylinder should
rotate as the peanuts are roasted. Visually check peanuts
to determine when they have reached a medium dark roast,
measured as a 24-27 Y(G) color value on the Gardner
colorimeter. Roast time required is generally 15-25 minutes
for a 550-gram peanut sample. Roast time varies with
peanut variety, size, oil and moisture content.

7. Shut off unit when peanuts have reached target roast
color, 24-27 Y(G) color value. Remove cover and baffle
and pour peanuts onto tray. Immediately place into 0-45F
incubator to arrest roasting process. Remove tray when
peanuts have reached room temperature. Time required to
cool a 550-gram sample is generally 10-20 minutes.

8. Blanch a 150-gram subsample of peanuts, grind to a slurry
using Olde Tyme Mill, and mix thoroughly.

B. Color Measurement of Sample

1. Fill a plastic petri dish with the slurry, so there are no
voids in the sample portion exposed to the light beam.

2. Obtain the sample temperature in OF just prior to placing
it on the sensor view port.

3. Place the sample on the sensor, so the sample completely
covers the sensor viewing port.

4. Immediately press the sample key.

5. Enter the sample temperature upon query from the data
terminal screen (Temp?). Press return.

6. Record the Y(G) color value of the XYZ reflectance mode.
If color is not between 24 and 27, weigh a new peanut
sample, and roast again. It is recommended to place some
24 to 27 roast color peanuts near the roasting peanuts to
help inexperienced operators to judge the end of the roast

C. Organoleptic Measurement

1. Sample 20 peanuts crosswise from the tray. Do not select
the physically damaged peanuts.

2. Remove the skin and nib of one peanut and taste. Score
the peanut for peanut flavor and off-flavor according to
intensity level ranging from 0 to 5. Describe flavor notes
and physical characteristics of peanuts as described in
attribute list. Record numbers and comments on the score
sheet. Rinse mouth well with warm (490C) water after
tasting the peanut sample.

3. Repeat step 2, above, for each of the 20 peanuts.

Peanut Flavor Attribute Definitions

A list of flavor attribute definitions common to roasted peanuts
has been incorporated in the revised CLER procedure. These
descriptive terms provide a common point of reference for scoring
peanuts, and may be used in training personnel. The terms are
divided into peanut flavor attributes. As peanuts are tested, flavor
notes characteristic of each peanut may be recorded on the score
sheet. They are defined as follows.

Peanut Flavor Attributes

Almond: roasted almond flavor
Coffee: roasted coffee-bean flavor
Fresh: strong, clean, clearly defined flavor character-
istic of fresh roasted peanuts
Nutty: nut-like flavor, typical of fresh roasted peanuts
Popcorn: flavor of popped corn
Smoky: flavor resembling smoked nuts
Sweet: natural sweetness of the peanut; basic taste

Off-Flavor Attributes

Acrid: bitter and astringent sensation peculiar to burned
Astringent: sensation of shrinking, drawing, or puckering of
skin surface, leaving a dry feeling in the mouth
Barnyard: hay, alfalfa, or grain type flavor
Beany: similar to raw beans, such as green beans or
Bite: stimulates taste buds at back of tonque and oral
cavity; sharp, pungent, unpleasant sensation
Burnt: common to over-roasted or charred peanuts
Cardboard: slight degree of woody or musty notes; slight
chemical note; like actual cardboard
Earthy: like odor of moist earth or soil; similar to odor
of peanut shells
Fruity: flavor of over-ripe fruit, like rotten bananas
Green: flavor of raw, under-roasted or immature
peanuts; beany
Machine Oil: like odor of machine oil
Mealy: smooth, musty, with sour aftertaste; similar to
milled cereal products
Medicinal: medicinal flavor similar to odor of medicine
cabinet, hospital, or various types of medicines
Metallic: metallic flavor causing burning sensation in back
of throat
Musty: resembling odor of moldy soil with slightly sour
Onion: flavor of raw onions
Off-sweet: initial sweetness followed by sensation of rotten
fruit (ethylene)
Oily: flavor of oil
Rancid: rank taste, resembling flavor of old oil
Raw: beany
Rotten: offensive flavor characteristic of a decomposed
Soapy: flavor of soap
Solvent: flavor of chemical solvent
Sour: causes an acid or tart sensation on tonque
Stale: absence of fresh flavor; flat and tasteless
Unclean: lacking clearly recognizable fresh peanut flavor
Woody: flavor of wood, similar to odor of fresh sawdust

These definitions were composed by the Nut Products Product
Development Group of Best Foods Research Center, Union, N.J.

The objective in developing definitions is to allow for a common
reference point as a basis for scoring. The same descriptors and
definitions do not have to be used for every panel implementing
the CLER method. The emphasis should be on discussing and
agreeing on flavor attribute definitions, rather than accepting the
terms as defined in this paper.

Comments made in response to a peanut sample may provide
insight regarding the history of the sample. For example, frequent
recording of the terms chemical, medicinal, or solvent of sample X
indicate that sample X may have been stored or shipped next to a
chemical, or sprayed with a pesticide. Rancid comments may
indicate extended or improper storage conditions.

Intensity Scales for Peanut Flavor and Off-Flavor

The revised CLER scoring method has two separate intensity
scales for the off-flavor and peanut flavor notes of each peanut.
The scoring system is as follows:

Peanut Flavor: Off-Flavor:

None 0 High 0
Low 1 Moderate-High 1
Low-Moderate 2 Moderate 2
Moderate 3 Low-Moderate 3
Moderate-High 4 Low 4
High 5 None 5

The terms "good" peanut flavor and "bad" off-flavor have been
eliminated from the score sheet, so panelists may concentrate on
peanut flavor intensity and off-flavor intensity. A peanut flavor
score of 0 means the sample does not have any flavors character-
istic of peanuts. A score of 1 means the peanut flavor is just
perceivable. A score of 3 represents a medium level of peanut
flavor. A score of 5 represents maximum peanut flavor. On the
other hand, for off-flavor intensity, a score of 0 accounts for a
level so high the sample must be expectorated. A score of 2
denotes medium intensity off-flavor. A score of 4 means the off-
flavor is just noticeable. A rating of 5 is given if no off-flavors
are present. The scores for peanut flavor and off-flavor intensity
are added together for each peanut. The maximum score for an
individual peanut is 10. The CLER score is the sum of the scores
of the 20 peanut samples divided by 2.

An example of the revised CLER scoring form is shown in
Table 9.2. The new CLER scoring form has a place for comments
describing the peanut sample on the following properties: (1) off-
flavors; (2) roast (light, medium or dark); (3) texture--used to
describe the following: (a) soggy, when the peanut feels softer and
moister than normal, (b) hard, used to describe a peanut that is
harder than normal, and (c) mealy, when small grains or particles
are felt in the peanut; and (4) blanchability, describing the ease of
removing the peanut skin.

To comment on every property for every peanut would increase
the time required for each CLER score evaluation, and usually is
not necessary. It is recommended to record comments only when
the peanut sample is unusual in one of the above mentioned


Add Peanut Flavor Score and Off-Flavor Score for each peanut
(maximum score = 10). Add scores of the 20 peanuts (maximum
score = 200). Divide this number by 2 for the final CLER score.


Peanut Flavor Score = 2, 4, 3
Off-Flavor Score = 3, 4, ... 4
Score Totals = 5, 8, .. 7

Add: t + t2 +.. + t20, where t = score totals.

If 5+8+ ... +7= 139,
then 139 -2 = 69.5 CLER Score.

Acceptable Range = Score of 50-100
Unacceptable Range= Score of 0-49


The revised CLER method results in scores which are a better
indicator of peanut flavor quality, because of better control over
the sample preparation and organoleptic evaluation procedures.

Table 9.2. Revised Critical Laboratory Evaluation of Roasted
Peanuts (CLER) Scoring System Form.

Color Name



CLER Score

Peanut No.:

Peanut Flavor









------------------------ --A---

__ -

Peanut Flavor Intensity:

0 = None
1 = Low
2 = Low-Moderate
3 = Moderate
4 = Moderate-High
5 = High

Off-Flavor Intensity:

0 = High
1 = Moderate-High
2 = Moderate
3 = Low-Moderate
4 = Low
5 = None

Peanut Score =
Peanut Flavor Score
+ Off-Flavor Score

CLER Score =
Peanut Score/2

--- --- ------

The variabilities of the former and the revised CLER proce-
dures were evaluated by several panelists at Best Foods Research
Center. For both methods, the average CLER score value for each
of ten samples was used in the analysis. An F-test was performed
on the data to determine the equality of the variance between the
two methods. Since a significant difference between the variances
was found, the sign rank test, a non-parametric procedure, was
used to analyze the data. There was a significant (P < 0.05)
difference between the variability of the revised CLER and former
CLER methods. The revised CLER method had significantly lower
variability (10.35) than the former CLER method (52.54).

Following the introduction of the revised CLER score procedure
into the Skippy plants, data were collected over a 44 month period
to assess the average standard deviation between scores for a given
sample. A value of 5.3 was found to be the average standard

Derby Foods reported a standard deviation of 10 in 1973, using
the former CLER score procedure. The APRES publication of the
former method itself lists a standard deviation of 14.37.

Though the modified CLER procedure remains a subjective test
for measuring overall flavor quality levels of a given peanut lot, it
represents a significant improvement over the former method.


I gratefully acknowledge Mr. Art Krisinski, Section Leader -
Dressings and Nut Products Research, Best Foods Research and
Engineering Center, for his support in the CLER procedure


Ahmed, E. M. and C. T. Young. 1982. Composition, quality, and
flavor of peanuts, pp. 670-684. In H. E. Pattee and C. T.
Young, (eds.), Peanut Science and Technology, Amer. Peanut
Res. and Educ. Soc., Yoakum, Texas.

Brown, M. L., J. I. Wadworth, H. P. Dupuy and R. W. Mozingo.
1977. Correlation of volatile components of raw peanuts with
flavor score. Peanut Sci. 4:54-56.

Buckholz, L. L. Jr., H. Duan, E. Stier, and R. Trout. 1980. In-
fluence of roasting time on sensory attributes of fresh roasted
peanuts. J. Food Sci. 45:547-554.

Holaday, C. E. 1971. Report of the peanut quality committee. J.
Amer. Peanut Res. and Educ. Assoc. 3:238-241.

Oupadissakoon, C. S. 1980. Relationship of Chemical and Or-
ganoleptic Measurements of Raw and Roasted Peanuts. Ph.D.
Thesis: North Carolina State University, Raleigh, NC.

Oupadissakoon, C. S. and C. T. Young. 1984. Modeling of roasted
peanut flavor for some virginia-type peanuts from amino acid
and sugar contents. J. Food Sci. 49:52-58.

Pearson, J. L. 1968. Current procedures for panel evaluation of
peanut quality, Proc. Fifth National Peanut Research Con-
ference, July 15-17, Norfolk, VA. p. 117 (Abstr.).

Pattee, H. E., J. A. Singleton and E. B. Johns. 1971. Effects of
storage time and conditions on peanut volatiles. J. Agr. Food
Chem. 19:134-137.

Rodriguez, N. C. 1976. A discussion of sensory evaluation panel
techniques designed for peanut butter. Proc. Amer. Peanut
Res. and Educ. Assoc. 8:20-22.

Sharon, D. 1963. Measurement of peanut quality and factors
influencing it. Proc. Peanut Improvement Working Group.
July 29-31. Oklahoma State Univ., Stillwater, OK. pp. 1-15.

Syarief, H. D., D. Hamann, F. G Giesbrecht, C. T. Young and R. J.
Monroe. 1985. Interdependency and underlying dimensions of
sensory flavor characteristics of selected foods. J. Food Sci.

Thomas, M. C. 1968. Some factors that affect quality in peanut
products as determined by organoleptic evaluation. Food Tech.

Tiemstra, P. J. 1973. Determining the quality of raw peanuts and
manufactured products, pp. 624-656. In Peanuts: Culture and
Uses, Amer. Peanut Res. and Educ. Assoc., Stillwater, OK.

Peanut Processing in the United States:
Conventional Techniques

James J. Heinis and Clyde T. Young

Sixty-five percent of the U.S. peanut crop is processed into
peanut butter, salted peanuts and confections. Although the
roasted form predominates, raw peanuts serve as the basis for
boiled peanuts and peanut brittle (Woodroof, 1983). The other
fraction goes into the export market or the production of peanut
oil which is widely used as a salad oil (Wilson, 1975) and for
deep-fat frying. Peanut oil is prized for its high smoke point
(2300C) and lack of flavor carry-over (Woodroof et al., 1946).


Peanut quality and flavor precursors depend on cultivar and
maturity (Sanders et al., 1982). The inherent flavor quality, how-
ever, can be altered by moisture availability, pre-harvest drought
stress (Young and Schadel, 1984), and curing (Pattee et al., 1985).
Changes in levels of amino acids, sugars and fatty acids, which
serve as flavor precursors, may be accompanied by altered patterns
of carbonyl and sulfur compounds that are associated with objec-
tionable flavor defects (Pattee et al., 1985; Young and Heinis, 1987).

Prior to processing, care must be taken during storage to
prevent volatile absorption by the peanut from solvents, paints,
ammonia and agricultural products such as cheese and apples.
Refrigeration at 1-50C and 55-70% relative humidity (RH) permits a
2-year storage life (Woodroof, 1983). After removal from storage,
the processing cycle begins.

Roasting conditions depend on the type of final product. Typi-
cally, dry (hot air) roasting is used for peanut butter and in-shell
peanuts, while oil roasting (cooking) is preferred for salted peanuts
and confections where kernels are desired and a more intense
roasted flavor is required (How and Young, 1985; Young et al.,
1975). Flavor defects arising out of improper roasting can include
underroast and burnt or overroast, to give a few examples. Slight
overroasting is common in cracker fillings (Matz, 1976).

Testa (seedcoat) and germ removal from the seed through
blanching or "white roasting" is essential to avoid bitter, gray,
rancid peanut butter (Matz, 1976; Woodroof, 1983). For oil-cooked
nuts, blanching takes place prior to roasting. Excessive blanching
temperatures can cause off flavors (Pattee and Singleton, 1971;
Woodroof, 1983).


During 1982, peanut butter (PNB), spreads and imitation PNB
accounted for $796.7 million in sales (U.S. Department of Com-
merce, 1982) in an industry dominated (76%) by CPC International
("Skippy"), Proctor and Gamble ("Jif"), Beatrice ("Peter Pan") and
Borden ("Bama"). Private labels accounted for the remaining 24% of
the market (Southwest Georgia Planning Commission, 1982).

Per-capita PNB consumption in the U.S. (1.4 kg) far exceeds
Canada (0.20 kg) and the Netherlands (0.16 kg) (Wilson, 1975).
Smooth (creamy) grinds are popular (65% of the U.S. peanut butter
market) where PNB competes with other nut butters, luncheon
meats, jams and cheese.

Peanut Butter Standards

Standards and specifications depend both on nutritional policy
and technology. In the United States, the Standard of Identity
(Zamula, 1985) ensures the quantity of peanuts in commercial PNB.
The PNB must contain at least 90% peanuts and have a maximum of
24.0% protein without added artificial color/flavors, nonnutritive
sweeteners or preservatives (USDA, 1978). Occasionally vitamin A
fortification is specified by the U.S. Department of Defense. In
spreads and imitation butters, peanut and nonpeanut ingredient
levels (e.g. soy bits) must be declared. Peanut spreads must be
nutritionally equivalent to PNB with respect to niacin, vitamin B6,
folic acid, iron zinc, magnesium, copper and have at least 24%
protein. Imitation peanut butters are not required to meet these

Composition and Ingredients

The traditional "old-fashioned" PNB formulation used peanuts,
salt and sugar [spanish:virginia ratios of 1:1 or 2-3:1 (Thompson,

1917]), but oil separation, rancidity and texture problems limited
distribution and shelf-life. Stabilizer addition to commercial PNB,
commonplace by 1945, overcame many of these shortcomings and
permitted rapid expansion of the PNB market. A typical formula-
tion contains at least 90% peanuts, 1.6% salt (typical maximum),
4.25% sucrose (6% maximum), and 3.25% stabilizer (5.5% maxi-
mum), levels of which can vary depending on the desired final
product flavor, texture and storage stability (Woodroof, 1983).

The market-type of peanuts used in PNB has changed greatly
since 1968 because of the processing characteristics of the various
market-types as well as their relative cost. Traditionally, runner-
spanish blends were essential, since the oil content of virginias was
too low to give an acceptable PNB, while formulas with pre-
Florunner cultivars had problems during container fill. Florunner
is now widely used, since it is in good supply, the oil content
(46-52%) is near the permissible maximum (55%), and it gives good
quality PNB. Virginia (45-52% oil) and spanish (46-54% oil)
market-types are generally $0.03-0.05/lb. more expensive than
runners (Southwest Georgia Planning Commission, 1982).

Stabilizer, used to prevent oil separation during storage and
particularly at temperatures above 350C (950F), permitted expan-
sion of the domestic market. Mono- and diglycerides from rape-
seed, cottonseed and palm oil are especially suitable because of
their hydrophilic and lipophilic properties and beta-prime crystal-
line structure (Gunstone and Norris, 1983). Peanut butter using
these stabilizers tends to have a smooth, creamy texture because
this beta-prime form has the smallest crystal size, intermediate
melting point and density while requiring less stabilizer addition
(Weiss, 1983). In contrast, stabilizers from peanut, corn, lard,
soybean or sunflower oils, for example, form beta crystals. Peanut
butter containing these stabilizers can then develop such surface
defects as spots and a dull surface. These defects are less evident
for soybean-rapeseed blends (50:50), which promote rapid flavor re-
lease (Brekke, 1980).

Proper stabilizer choice also depends on melting point (Cecil,
1975), level used in the formula, texture, process, packing season,
fill and storage temperatures. Low fill temperatures (35-410C) use
rapeseed oil hardfat (1.6-1.8%), Durkee 07, Durkee 27 and Myvatex.
High fill temperatures (49-540C) and chill tunnels use cottonseed
hardfats (1.8-2.0%) or Dur-Em 127. At the highest fill tempera-
tures, monoglyceride stabilizers can be used along with glycerol
monostearate (Weiss, 1983), Fix X, Durlac 300 or Shur Set P. For

one stage processes, high melting stabilizers such as Fix X can be

Refrigeration (< 100C) or absorbants can be used in lieu of
stabilizers (Woodroof, 1983). The former method also enables the
butter to be stored up to 2 years without losing its desirable flavor
(Cecil, 1975). These methods, however, find limited use because of
increased energy requirements or product failure to meet the
Standard of Identity, respectively.

Care in product formulation is necessary also because flavor
defects can arise from chemical reactions between and among the
individual ingredients. Maillard reactions between reducing sugars
and amino acids are promoted by high temperatures and can give
dark peanut butters with altered flavor and texture (Weiss, 1983).
Although sucrose-honey combinations have a unique flavor and
consistency, they can tend to be overly viscous or pasty (Woodroof,
1983). Lipid oxidation and rancidity development can be delayed by
adding lecithin, fatty acids or fatty acid-polyglycerol esters (Weiss,
1983) or grinding with dry ice (Gutcho, 1973). The latter method
cools the product and lessens the extent of thermally induced

Peanut Butter Processing. Formulation. Packaging

The complex chemical interaction between the peanuts, salt,
sweetener and stabilizer necessitates that care be taken to reduce
adverse reactions between the components. Seasonal adjustment of
stabilizers is often necessary.

In roasting, peanuts are heated to 1600C in gas-fired roasters
(Woodroof, 1983). Following roasting, the peanuts are cooled,
blanched and milled to a paste. Here, single stage milling leads to
hotter exit temperatures (820C) than two-stage processes (60-770C).
During this second grind (stone spacing of 76-127 mm), stabilizers
are added at 60-740C along with preground dextrose and salt
(Woodroof, 1983). Because of the higher exit temperatures in single
stage grinds, Maillard reactions pose particular problems, especially
when the formulation contains reducing sugars (e.g. dextrose, invert
sugar and corn syrup solids), honey (mainly glucose and fructose)
or molasses. The problem caused by the addition of these latter
products is due primarily to the free unbound moisture. This can
be controlled by using a two-stage process which permits a cooler
grind. In addition, ultrasonic homogenization and smaller peanut

particle size gives improved flavor and creamier textures. More
stabilizer, however, is required for these find grinds and may give
rise to overly hard PNB. Although proper care may be taken in
formulation, salt and sweetener recrystallization can still take place
should the PNB be cooled too slowly (Woodroof, 1983).

Other defects can arise due to post-process mishandling.
Concave surfaces/"pull away"/"bubbles" are found when deaeration
is incomplete or soybean emulsifiers are used in winter. For soft
PNBs, this "pull away" is often reversible. Post-fill disturbances
often induce convex surfaces (Woodroof, 1983), while shaking and
elevated temperatures can even lead to oil separation. Lights rich
in ultraviolet radiation promote rancidity on the exposed surfaces
or sides.

The traditional straight sided 18-oz glass jar also reduces "pull
away" while maintaining food product visibility in an oxygen and
water impermeable container. Plastic or metal tubes and cans have
been test-marketed (Sacharow and Griffin, 1980), and lined fiber
drums, steel drums or boxes are used for bulk volumes (Matz,

Storage temperature and atmosphere are also important in
maintaining shelf-life. Typically, PNB refrigerated at 80C is
acceptable up to 4 years. Packaging under nitrogen atmospheres is
commonly used to delay lipid oxidation and rancidity development.
Under these conditions, the flavor-related methylbutanal/methyl-
propanal ratio is higher (Fore et al., 1976), but once oxygen is
depleted (Fore et al., 1979) the rate of change for this ratio


United States roasted peanut consumption is fairly stable at
0.64 kg/person (Zamula, 1985). Although the salted, roasted form is
dominant, oil cooked, salted, unsalted and low calorie forms such as
whole or mixed nuts are also popular. "Low calorie" peanuts, pro-
duced by hydraulic pressing, have had poor consumer acceptance
because of lower peanut flavor (Gutcho, 1973). Blistered peanuts
are another form whose characteristic crisp texture is produced
when the internal moisture from the hot water pre-roast treatment
flashes into steam during oil cooking.

Processors are centered in the Mid-Atlantic, the Northeast, and
and the Midwest, often near major cities. Capital investment for
the production facility is approximately the same as for a similarly
equipped PNB plant (Southwest Georgia Planning Commission,


Slack-fill coupled with consumer perceptions of peanut overuse
in mixed nuts led to FDA regulations (21CFR 164.110) which stipu-
late a minimum fill percentage and require that mixed nuts must be
composed of at least four different nut meats. The dominant nut
(usually peanuts) can not make up more than 80% of the finished
product (Zamula, 1985). Spanish peanuts must be declared as such,
with other nuts forming the remainder of the product. Fill stan-
dards (21 CFR 164.120) which require that average nut volume be
not less than 85% of the container volume must also be met.
Substandard fills (21 CFR 130.14) must be identified.

Processing. Ingredients and Packaging

For roasted peanuts, jumbo runners, virginia and spanish
market types are selected because of cost, texture and flavor
considerations, although runner use has increased recently. Unlike
PNB, blanching (spin or buff) comes before roasting; often whole
nuts are desired.

Air roasting permits higher throughput where in-tank storage is
used to stabilize the nut structure. In oil cooking, the nuts are
immersed 3-5 min in heated coconut, peanut or cottonseed oil
containing 0.5-3 ppm silicones to raise the smoke point and reduce
foaming (Weiss, 1983). Frequent oil changes are necessary, since
rancidity develops rapidly when "old oil" is used for cooking. When
coconut oil is used, salting takes place at this point before the
cooking fat solidifies.

Salting and coatings are also frequently used, with electrostatic
or in-shell salting being used depending on the desired degree of
salting. The latter process (Cecil and Woodroof, 1959) uses a brine
solution under vacuum which is repeated until the desired salt
content is obtained. Salt must be free of copper and iron to delay
the onset of lipid oxidation, while bitterness occurs when the salt
is high in calcium chloride (Tressler and Lemon, 1951). Electro-
static deposition is preferred in air roasted peanuts (Matz, 1976)

while dendritic (150-420 mm) and fine flake (150-450 mm) salts are
used with the oil-cooked product. Coatings used for spanish
market types, include 28% zein in alcohol, sorbitol-mannitol (7:3)
blends, 5-6% acetic acid activated wheat glutins (Gutcho, 1973) or
honey. These act to improve shelf-life and aid in color retention.

Packaging used to extend shelf-life includes vacuum-packed
cans/glass jars, cellophane/glassine bags (Sacharow and Griggin,
1980) or nitrogen flushed laminated foil packs which serve to limit
the exposure of the product to light, moisture and air. As with
PNB, nitrogen atmospheres are frequently used for roasted peanuts
and can give a 1-2 year shelf-life. Shelled nutmeat shelf-life
ranges from 4 years at -170C to 4 months at 210C and is extended
with antioxidants. At 2-2.5% moisture, salted peanuts are still
regarded as fresh up to 35 days with respect to texture, flavor and
appearance (Woodroof et al., 1945A). Storage at 80% relative
humidity leads to a loss in "freshness" within 15 days (Woodroof et
al., 1945B). Gas flushing studies using four atmospheres (vacuum,
carbon dioxide, nitrogen and air) and the four market types (run-
ner, virginia, spanish and valencia) in Cryovac P-850S nylon-
saran-polyethylene pouches) found significant methyl butanal
differences which were particularly high in valencias (How, 1984).
Under nitrogen, these methyl butanal (associated with "old age")
levels increase with storage, while color and texture are affected
by atmosphere. Staling accompanies flavor decline.


Peanut candies and confections are the major growth area for
processed peanuts. Although filberts, almonds and walnuts offer
significant competition, compatability with a variety of confec-
tionary formulas, small physical size, low cost and high consumer
acceptability have ensured that peanuts will have an ever greater
share of the confection market. This wide consumer acceptance of
roasted peanuts and high domestic production have led to the three
major products (Snicker's, M&M Peanut and Reese's Peanut Butter
Cup) and non-cholocate bars (e.g. Payday) all having peanuts as a
major ingredient (DEBS, 1984).


Although peanut confections encompass many formulations and
products, the requirements of the Federal Food and Drug Law must
still be met with respect to formulation, manner of production, and
handling (Packard, 1976). In these formulas, corn syrup is widely

used in lieu of sucrose (Hurst et al., 1983), and the high use of
hydrogenated fats (Rudolf et al., 1980) is reflected by the low
polyunsaturated/saturated fat ratios.

Processing. Ingredients and Packaging

In these products, nuts are roasted and serve as toppings or
part of the product. Typically, in bar formulations, peanuts provide
"crunch", reduce chocolate sweetness and are slightly overroasted
to provide distinctive flavor (Minifie, 1970).

Split, granulated, or whole peanuts or a ground peanut paste
are used in many confections. For example, whole peanuts form a
part of the nougat formula (Alikonis, 1979) or are part of the
topping in nut roll candies. In aerated bars, peanuts impart texture
and flavor contrast without increasing cost. Whole peanuts can
also be coated as in dragees and hard-coated peanuts (Trevor
Williams, 1964). These use alternating supersaturated sugar/gum
arabic solutions (67%) and powdered granulated sugar with a final
coating of 51% sucrose syrup (Minifie, 1970). In contrast, peanut
butter cups use peanut cremes as fillings. After covering the filled
cups with liquid chocolate over a vibrating table, the cups are
packed into glassine packages.

Raw peanuts are used in peanut brittles. A sugar:corn syrup:-
water blend (30:20:7) is boiled, and the peanuts are added, together
with sodium bicarbonate, to increase brittle expansion and enhance
browning. The batch is spread onto a cooling slab or Teflon belt
and cooled to 370C before packaging. Cooking of raw peanuts
within the batch gives improved flavor volatile retention (Janssen,
1978), but the high moisture content of the sugar solution is
conducive toward rancidity and browning.

Product acceptability depends on peanut quality, i.e., fatty acid
content of the oil, maturity, unique roasted flavor and flavor
defects. Headspace analysis of 20 commercial products has shown
that these peanuts may also have high levels of flavor defects
(Young, 1984) such as "musty flavor", "old age" and "tongue burn".
These may be masked somewhat by the flavor and sweetness of the
chocolate coating. With poorly enrobed products, storage under
high moisture is especially detrimental to storage stability, even
when initially good quality peanuts are used in product formulation.
Moisture uptake is a particular problem in exposed nut rolls and
wafer-type confections.

Shelf-life is greatly affected by product configuration, moisture
content and storage temperature. Products with exposed nuts tend
to have shorter shelf-lives than ones where the nuts are enrobed.
For example, brittles (1.6% moisture) have a 1-4 week shelf life at
room temperature, while caramel nougat bars can remain acceptable
after several years under refrigeration. Refrigerated storage under
low relative humidities is especially beneficial, since it reduces
rancidity development (Woodroof et al., 1947; Cecil and Woodroof,
1962) and stickiness (Woodroof et al., 1950), while staling can be
promoted by high temperatures (Woodroof et al., 1950). To avoid
staling in exposed nut rolls, refrigeration at less than 40% RH is
necessary to give a 4 month shelf-life (Woodroof et al., 1950). One
year is considered to be a typical shelf life for most confections
given 20-60 day distribution times. Further research, however, is
essential in order to learn more about these interrelationships as
well as the effect of water activity on the packaged product.

Proper packaging requires that the inert packaging material
have good barrier properties to light, moisture, oxygen and insects
(Sacharow and Griffin, 1980) in order to hinder moisture access to
the lowest equilibrium moisture component which otherwise would
rapidly diminish shelf life. Both triple laminate packaging and
glassine papers are extensively used for confections. In these
laminates, the most protective film should face the point of highest
humidity. Typically, triple laminates are preferred for vertical
form-fill sealers, while the traditional glassine papers are used for
horizontal form-fill sealers (Griffin et al., 1985). Paper boxes or
folding cartons are used for peanut brittles.


Peanut butter, roasted peanuts and confections are the major
domestic uses of peanuts and vary in formulation, production
technology, standards and packaging. Stabilizer selection and level
in formulation for peanut butter depends on process and handling.
Salt used for salted, roasted nuts must be low in calcium, iron and
copper salts. For all of these products, though, shelf-life depends
on peanut maturity, product formulation and post-process packag-
ing and storage. Although peanuts are sometimes used as alterna-
tive protein sources, this use is limited because of cost and the
large consumption of peanuts in traditional forms.


The authors wish to thank Rick Hull for providing information
on commercial peanut stabilizers.


This is Paper No. 10608 of the Journal Series of the North
Carolina Agricultural Research Service, Raleigh, NC.

The use of trade names in this publication does not imply
endorsement by the NC Agricultural Research Service, nor criticism
of similar ones not mentioned.


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Peanut Quality and Non-Conventional
Processing of Peanut Seed

Esam M. Ahmed

Peanuts are recognized around the world as a major oilseed
crop, grown primarily for their high oil content. Recently con-
siderable attention has been focused on the peanut, as well as
other oilseeds, as a good source of protein to help ease the protein
shortage in many areas of the world. Because of the more common
harsh crude oil extraction techniques, most of this protein is made
unfit for human consumption and is used for animal feed or as
fertilizer (Rosen, 1958; Parpia and Subramanian, 1966).

The peanut is considered to be a high energy food with 46-52%
lipids, 25-30% protein, 4-6% water, 2.8-3.0% crude fiber, 10-13%
nitrogen-free extract, and 2.5-3.0% ash (Rosen, 1958; Ahmed and
Young, 1982). Its nutritive quality is limited primarily by its low
amino acid content of lysine and methionine. It is also marginal in
tryptophan and threonine, and is low in many minerals (Milner,
1962; Woodroof, 1983). Peanut flour, produced from the defatted or
partially defatted meal, contains higher contents of protein and has
a protein efficiency ratio (PER) value of 1.47 in contrast to casein
which has a PER value of 2.50 (Parpia and Subramanian, 1966).
However, Miller and Young (1977) found that growth of rats fed 20
and 15% of the diet as peanut meal was essentially similar to rats
fed casein for 2 or 4 weeks, respectively.

As a by-product of the vegetable oil industry, peanut meal has
achieved little traditional food use because of poor handling and
processing techniques and also because of the problem of aflatoxins.
Aflatoxins, produced primarily by the fungus Aspergillus flavus,
are a problem primarily when improper harvesting and storage
conditions are encountered. Milner (1966) stated that with means
to control the aflatoxin problem in peanut seed, this protein
resource will doubtless achieve wider use for feeding as well as
for industrial purposes. Careful selections of peanut seed can
provide flours of good nutritional quality that are acceptable as
components of low-cost protein-rich foods suitable in a number of
developing countries. A major difficulty in utilizing the peanut oil
industry residual meal is due to the effect of the harsh treatment

to which the proteins are subjected. The meal is cooked to co-
agulate and thereby denature the protein in order to free the oil
for expelling (Rosen, 1958). Milner (1962) states that optimum
protein nutritional quality can be retained in the product only by
avoiding excessive or prolonged temperature treatments in the
blanching and cooking steps that precede oil expression.

The conventional uses of peanut seed in the United States and
the world are as roasted nuts, salted nuts, confectioneries, peanut
butter and paste, and as a source of oil. Expression of oil from
peanut seed results in a protein-rich residue (45-55% protein).
McWatters and Cherry (1982) amply reviewed the potential food
uses of peanut seed proteins. These peanut protein-rich residues
are dried, ground, and used for extending comminuted meat pro-
ducts, for production of beverage-type and fermented dairy-type
products, and for protein supplementation of foods such as bread
and bakery products (Milner, 1962; Schmidt and Bates, 1976;
Schmidt et al., 1977, 1978 and 1980; Ahmed and Araujo, 1978;
Ahmed and West, 1981).

Three types of peanut protein products are available for human
consumption: (1) an oil-free or low-oil protein concentrate (45-55%
protein) manufactured by removal of the skins, followed by oil
removal either by solvent extraction or by mechanical means (con-
tinuous screw press), or by a combination of the two; (2) a lipo-
protein (70% protein, 30% oil) manufactured by disintegrating the
seed in an aqueous medium, removal of a portion of the oil by
separation, followed by recovery of the protein-oil mixture; and (3)
a protein isolate made by the same kind of process as used for
soybean protein (Altschul, 1968).

Applications of protein isolates depend largely on protein
solubility. Wu and Inglett (1974) reported that protein solubility
was inversely proportional to dry heat temperature, but a sigmoid
curve was observed after exposure to wet heat. Neucere et al.
(1969) studied the effects of dry roasting at 1450C for one hour on
the solubility of peanut proteins. Their results show three basic
observations: (1) the concentration of total soluble protein is
decreased considerably by roasting (25 mg/ml untreated, down
to 10 mg/ml after roasting); (2) the antigenic structure of the a-
arachin (major reserve protein) is unchanged; and (3) other pro-
teins, some of which apparently maintain their primary structure,
show modified physicochemical properties. It should be noted that
these experiments were run on dry roasted material. Wet heating
process would severely affect protein solubility (Neucere, N.J. 1972).

Srikanita and Rao (1974) showed that wet heating with steam for
30 minutes at atmospheric pressure did not reduce protein solubil-
ity, whereas heating under pressure significantly reduced protein
solubility. They surmised that the reduced solubility might be due
to protein denaturation or complex formation between protein and
carbohydrates. These results suggested that peanut protein depoly-
merized during wet heating and/or combined with the other con-
stituents of peanut meal; the extent of these reactions depended on
steam pressure. Protein solubility is related to the isoelectric point
of proteins; hence the loss in protein solubility could be attributed
to irreversible denaturation, a change in the isoelectric point, or
both (Neucere et al., 1969).

Several methods have been investigated and applied industrially
to separate the oil and protein fractions using as little heat as
possible so as not to harm the proteins. The impulse rendering
process developed by Chayen and Ashworth (1953) has been applied
to peanuts by International Protein Products, Ltd., Plymouth,
England, since 1960 to produce the lipid-protein isolate "Lypro"
(Smith, 1976). The isolate contains 65% protein and 32% oil, with
virtually no amino acid deterioration or loss of biological value, by
virtue of the absence of heat and harsh process conditions. The
oil that is recovered is light in color, has a faint odor of peanuts,
and is of high quality. Rhee et al. (1972) reported on an aqueous
system for the recovery of protein and oil from raw peanuts. This
procedure utilizes differential pH control and centrifugation to
solubilize the protein, separate the resulting fractions, and precipi-
tate the protein. This procedure yielded a protein isolate of 92%
protein and 3% fat. Rhee et al. (1972) also found that protein
extraction at high pH tends to reduce protein solubility, while
extraction at low pH leaves a considerable amount of protein
unrecovered. They showed that the pH of protein precipitation
should be kept as close as possible to 4.00 + 0.25 to insure maxi-
mum recovery of both protein and oil.

Fletcher and Ahmed (1977) found that mildly extracted peanut
seed proteins could be spun into fibers. They found that the best
conditions for spinning protein fibers were: (1) peanut solution
(dope) pH 11.4, (2) maturation time of 12 hrs for 13.0% protein
dope or 2 hrs for 13.5% protein dope, (3) coagulating conditions of
2 N acetic acid and 20% NaCI and (4) dope extrusion pressure of
15.0 psi. They also found that suitability of dope solutions for
spinning depended on the interaction of protein concentration, pH
and dope maturity. The chemical analysis of the extracted peanut
protein concentrate and spun fibers is shown in Table 11.1.

Table 11.1. Chemical analysis of peanut protein concentrate and
spun fiber (dry weight basis).

Protein Fibers from
Constituent Concentrate 13% 13.5%
protein dope protein dope

Protein (%) 85.53 78.24 77.82

Fat (%) 3.11 0.80 0.50

Ash (%) 1.99 3.42

From Fletcher, D. L. (1975).
Coagulating bath conditions: 2 N acetic acid and 20% NaC1.

The results of the chemical analysis showed a decrease in both
protein and fat and an increase in ash as a result of spinning. The
increase in ash was probably due to the accumulation of salts in
the fiber from the coagulating bath. These salts could likely be
removed by adequate washing of the fibers after spinning. The
decreased fat content could be attributed to the diffusion of fat,
following spinning, into the coagulating bath. The decrease in
protein content could possibly be attributed to the loss of amino
nitrogen from the protein as a result of the high alkalinity of the
dope (pH 11.4).

The responses of peanut seed protein spun fibers to applied
stresses were studied by Ahmed and Fletcher (1977). Increased
tensile strength, stretchability and shear strength were evident for
spun fibers prepared from dope solutions containing 13% protein,
coagulated in a bath media of 2 N acetic acid and 20% (w/v) NaCl
and stored at 1.00C for 3 weeks. In addition, orientation of spun
fiber tows (strands) showed that two tows placed in a 0450 orien-
tation were more resistant to punch shear stresses than tows placed
in 0900, random or parallel orientation. Two tows required higher
punch shear forces than a single tow.

The food industry has attempted for many years to produce
meat analog food products for that segment of the population which
does not consume meats for religious, ethnic, health or economic

reasons. Meat analogs impart a more meaty character to products
than an equal weight of ground meat because unlike meat, they do
not fragment during processing (Ziemba, 1966). Spun peanut seed
protein fibers could be formulated into meat analogs with the
addition of a gelling agent, synthetic colors and flavors. The
major emphasis on simulated meat products must be, to a certain
degree, on the development of better methods of texturization.
Textural characteristics are controllable by selection of a combina-
tion of fiber diameter and strength and by specific orientation of
the spun fibers (Odell, 1969). Most organized meat structures
depend on nonsoluble though non-isoelectric, highly hydrated
proteins (Giddy, 1965). Simulated proteinaceous structures from
non-animal proteins should meet the same criteria.

The successful utilization of plant proteins as ingredients in
manufactured foods depends largely on such functional properties as
solubility, foaming capacity, foam stability, emulsification capacity,
whippability, binding ability, gelation, viscosity, water holding
capacity and fat absorption (Kinsella, 1976). The methods by which
oilseeds are handled following harvest and how plant proteins are
processed often play important roles in their functional properties;
generally, careful handling of peanut seed and mild processing
methods are associated with optimum functionality of the peanut
protein. Most of the studies on functional properties were con-
ducted on oilseed meal, flour or paste, and few on extracted
proteins. Functional properties of defatted peanut, field pea,
soybean and pecan flours were found to be sensitive to complex
interactions involving amount and type of soluble protein, pH,
aqueous and salt suspensions (McWatters and Cherry, 1982).

Most dried food products prepared by the food industry are
either spray or drum dried, and a few are freeze dried. Ahmed and
Schmidt (1979) investigated the effect of method of drying on the
functional properties of peanut seed proteins. Protein solubility,
emulsifying capacity, foaming capacity and foam stability were
higher for the spray dried and the freeze dried than the drum
dried preparations. The lower functionality of the latter prepara-
tions was probably due to the more severe heat treatment during
the drying cycle (1260C for almost 30 seconds) in contrast to the
heat treatment in spray drying (2500C for few seconds) and in
freeze drying where the maximum shelf temperature reached was
600C. Solubility of all preparations was dependent on the pH of
the suspending medium. Solubility at pH 7.0 is of importance since
many food systems utilizing plant proteins as ingredients are at this
pH. Solubilities of protein preparations at pH 7.0 were about 5-11%

less than those at pH 9.0 but 3-13 times higher than those at pH
4.0. Drum-dried protein preparations exhibited less emulsifying
capacity than spray or freeze dried preparations. Storage of
peanut proteins (Ahmed and Schmidt, 1979) resulted in a loss of
emulsifying capacity, especially for the freeze dried preparation.
The method of drying did influence the foaming capacity of peanut
protein preparations. Steaming peanuts prior to protein extraction
led to a considerable loss in foam stability. It is evident that the
method of drying peanut concentrates influences their functional
properties and the selection of method of drying would be depen-
dent on the desired functional properties of the preparation.


Oil expression from peanut seed under sanitary conditions
produces protein products that may be dried, ground, and used as
enhancers of protein content in food products or as extenders in
comminuted meat products. Mild extraction of peanut seed proteins
leads to the availability of peanut protein possessing functional
properties suitable for spun fiber production or dried protein
preparations that could be used in the manufacture of certain food


This is Florida Agricultural Experiment Stations Journal Series
No. 8034.


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