POSTHARVEST GRAIN LOSS
ASSESSMENT METHODS
A
Manual of Methods for the Evaluation
of Postharvest Losses
developed and compiled by
Kenton L. Harris
and
Carl J. Lindblad
published in cooperation with
The
League for International Food Education
The Tropical Products Institute (England)
Food and
Agriculture Organization of the United Nations
Group for
Assistance on Systems Relating to Grain After-Harvest
by the
American Association of Cereal Chemists
under Grant AIB/ta-G-1314
Office of
Nutrition, U.S. Agency for International Development
Cover figure: British Crown Copyright. Reproduced with permission
of the
Controller of Her Britannic Majesty's Stationery Office.
CONTENTS
This volume stems from the joint and
independent efforts of many who have
contributed ideas as well as manuscripts.
Contributors and Authors
Harpers Ferry,
WV, Meeting, September 8 10, 1976
Slough, England,
June 13-24, 1976
Authors
Preface
When world food
production is viewed as a system, loss and deterioration
is seen as a
major food-limiting factor. Postharvest loss reduction would
benefit from
reliable loss estimates and cost/benefit comparisons;
improvements
also must be acceptable and feasible to introduce.
I. Introduction. K.
L. Harris and C. J. Lindblad
Determination of
postharvest grain losses requires a blending of, and
concepts from,
several sciences.
II. Terms of
Reference. K. L. Harris and C. J. Lindblad
A.
Definitions
Postharvest,
losses, food, insects, microbiological defined.
B.
Planning: An Overview for Project
Administrators. K. L. Harris
15
Project planning
involves many disciplines and concepts, from national
priorities
to logistics and local cultural values.
C.
An Overview of the Postharvest System: The
Food Grain Supply
Pipeline. K.
L. Harris, W. J. Hoover, C. J. Lindblad, and H. Pfost
19
Determination of losses should proceed stepwise from understanding
the overall
grain-food pipeline to location of leaks and sites where
losses are
relatively important, can be assessed, and are amenable to
loss-reducing interventions.
D.
Preliminary Examination of Specific Problem
Points and Making On-Site
Rapid
Appraisals. G. G. Corbett, K. L. Harris, H. Kaufmann,
and C. J.
Lindblad
Rapid
on-site appraisals (30-60 days) are both workable and useful to
determine
feasibility for further investigations and for some inputs,
and to
delineate specific problem points.
III. Social and Cultural Guidelines
A.
The Fact-Gathering Milieu. Allan L.
Griff
B.
Anthropologic Signposts. C. C. Reining
Grain loss
does not exist independent of human and social influence.
Loss
assessment and reduction programs need to be seen from within
the local
setting. Cross-cultural sensitivity and understanding are
essential in
planning and executing such efforts. Reminders are given
on who,
what, and how to obtain reliable, useful information on and
within the
social and domestic organizations and in relation to
individuals.
Special attention is given to the role of women.
IV. Representative
Sampling, Interpretation of Results, Accuracy, and
Reliability. B.
A. Drew, with T A. Granovsky and C. J. Lindblad
Basic
statistical requirements for surveys, sampling, probabilities, and other
concepts
required in the assessment of losses are presented.
A.
Introduction
B.
Probability Samples
C.
Detailed Instructions
V. Loss Measurements
as Related to Situations Where They Occur
A.
Background Information. D. A. V. Dendy, with
K. L. Harris
Losses are
discussed as they occur during threshing, cleaning and
winnowing,
drying, parboiling, hulling and polishing, and grinding.
B.
Guidelines for Performing Studies of Farm
Storage Losses. J. M.
Adams and G.
W. Harman
Evaluation
of maize losses in small farms is used to explain loss
methods
development.
C.
Procedures for Measuring Losses Occurring
During or Caused by
Processing
including Threshing, Drying, and Milling of Most Grains,
but not
Maize or Pulses/Groundnuts. D. A. V. Dendy, with K. L.
Harris
Guidelines
for studying:
*
Farm-storage losses
* Total
system losses
*
Operator-induced losses
*
Threshing loss with the straw
*
Threshing loss, grain damage
* Maize
shelling loss on the cob
* Maize
shelling loss, grain damage
*
Dryer-induced loss, laboratory method
*
Dryer-induced loss, method for use in mill
* Batch
dryer testing
*
Continuous dryer testing
* Grinding
loss as bran
Comparison of milling yields by variety
Comparison of operators
Comparison of mills
Due to
insect damage
* Rice
milling losses
Batch
process
One-stage continuous process
Two-stage continuous process
* Rice
hulling losses
* Rice
polishing losses
VI. Standard
Measurement Techniques
A.
Preamble to the Methodology. K. L. Harris
and C. J. Lindblad
General
background of previous work, previously used estimating
procedures
and techniques, standardization of results.
B.
Losses Caused by Insects, Mites, and
Microorganisms. J. M. Adams
and G. G. M.
Schulten
An
explanation of several techniques based either on the weight of a
measured
volume of grain compared with a pre-loss standardized weight
or on the
separation of damaged kernels and the comparative weights
of damaged
to undamaged calculated to the whole sample. Also a
conversion
factor/percent damage method. Weight/unit volume,
counts and
weights of damaged and undamaged kernels, percent of
damage and
weight loss, and conversion factor/percent damaged
methods are presented.
* Standard
volume/weight method for damage by insects and
microorganisms
* Modified
standard volume/weight method when a baseline
cannot be
determined
* Count and
weigh method
* Converted
percentage damage method
C.
Losses in Grain Due to Respiration of Grain
and Molds and Other
Microorganisms. R. A. Saul, with K. L. Harris
Weight loss
due to grain respiration is unimportant until the moisture is
so high that
serious microbial deterioration occurs and rejection for
food use
becomes the dominant factor. Tables are given for calculating
losses based
on time, temperature, moisture, and physical damage. A
formula is
given for calculating losses based on weight of damaged and
undamaged
kernels. Rationale and techniques are presented for basing
losses on
locally applied rejects.
D.
Rodents
1.
General Considerations, Direct Measurement
Techniques, and
Biological Aspects of Survey Procedures. W. R Jackson and M.
Temme
Each
rodent ecosystem has features that tend to make it unique.
Loss
evaluations require preliminary investigation to establish an
environmental and loss perspective as to what features require
and are
amenable to assessment.
2.
Loss Determinations by Population Assessment
and Estimation
Procedures. J. H. Greaves
When
they can be undertaken, census and food-intake
procedures will give useful results. Three techniques are
described:
*
Survey for infestation
*
Census trapping and food intake calculation
*
Lincoln-Peterson method for population estimation
E.
Measurement of Losses Caused by Birds
By brief
summary only.
F.
Moisture Measurement, T. A. Granovsky, G.
Martin, and J. L. Multon
The
measurement of grain moisture is critical for proper assessment of
weight
changes during storage. (See Appendix C for methods.
A
nomograph is
given for calculating weight changes resulting from
moisture content
changes.
VII. Operations
Standardization and Control
From field
observations and sampling through analysis and reporting results.
the operation
requires standardized procedures and written operations
directions and
reporting forms. Supervision and built-in controls are
required.
A.
Handling of Samples in the Laboratory. T A.
Granovsky
B.
Operations Manuals and Laboratory Records.
T. A. Granovsky, and K.
L.
Harris
VIII. Application
and interpretation of Results
In assessing
losses, it is important to plan and follow a system that will
produce the
information required, be it related to traditional patterns,
proposed
interventions, biological parameters, or loss/benefit values.
A.
The Chronologic Approach: Losses as
Reflected by Use Patterns. J. M.
Adams
There is a
need to assess losses in grain as they are related to the use
pattern so
as not to base total loss figures on the final condition of
residual
grain.
B.
Losses and the Economist. M. Greeley and G.
W. Harman
To the
economist, "losses" refer to changes in value, and the magnitude
of the
effort to reduce losses is often dependent on the magnitude of the
monetary
losses. Loss surveys are viewed from this perspective.
C.
Conversion Into Monetary Values. E. Reusse
After
physical and quantitative assessment, food losses need to be
expressed
in monetary terms. This is necessary to establish a common
denominator for cost/benefit analysis in which cost (investments in
potential
improvement measures) and benefits (expected reduction of
food
losses) can be weighed against one another.
Appendixes
A.
Sampling Grain
1.
Comments on Probing Techniques and Probes
2.
Techniques for Sampling Bagged Produce. P.
Golob
Examining every grain in a lot is not
physically possible. Thus,
the
quality of the whole has to be judged on the basis of a sample.
The
sample must be representative of the individual bag, stack, or
lot from
which it is drawn. Various techniques to obtain
representative samples from bagged commodities are described
and
discussed. Emphasis is given to problems of probing for
samples.
B.
Tables of Random Numbers and Their Use. B.
Drew and T.
Granovsky
Sample
selection by means of randomization is not an unorganized hit
or miss
process to assure that an intentional or unintentional bias will
not be
introduced during sample selection and sampling. Procedures
for meeting
these requirements are discussed and described. A table of
random
numbers is given.
C.
Moisture Meters
A review to
help the prospective buyer find which of the many meters
best meets
the work requirements. Data sheets are given.
1.
Guidance in the Selection of Moisture Meters
for Durable
Agricultural Produce. T. N. Okwelogu
List of
meters and characteristics.
2.
Table of U.S. Department of Agriculture,
Federal Grain
Inspection Service List of Meters Used in the United States and
Their
Manufacturers, April 1978
3.
French Table of More Recent Moisture Meters
with Acceptable
pglxapx0.gif (600x600)
Accuracy
D.
Assessment of Profitability of Alternative Farm-Level Storages. M.
Greeley
An approach
is given to evaluating three methods of storage
improvement
for Andhra Pradesh, India. In each case, a cost/benefit
ratio is determined
and compared.
Selected References
Index
CONTRIBUTORS AND AUTHORS
The scope and
format of this manual stem from the Technical Advisory Committee
of the American Association of Cereal Chemists and from two
meetings. One was held
Sept. 8-10, 1976, at Harpers Ferry, WV. The other was held
June 13-24, 1977, at the
Tropical Stored Products Centre, Slough, England. Those
present at these meetings are
as much contributors as are those who eventually wrote the
individual sections.
The 1976 meeting
was a wide-ranging brainstorming session covering the basic concept
of the manual and getting to the fundamentals of
feasibility, format, and scope. It
was a group effort and the benefits stemming from its
interdisciplinary makeup cannot
be overemphasized.
The 1977 meeting
was a technical workshop devoted to defining and clarifying
general goals and specific subjects and writing them down.
It functioned both as a
group effort and as a vehicle for individual contributions.
The American
Association of Cereal Chemists Committee consisted of Edith A.
Christensen. U.S. Department of Agriculture, Inspection
Division, FGIS, Washington,
DC 20250; John H. Nelson. (now) American Maize Products
Company, Hammond,
IN 46336; and Raymond J. Tarleton. American Association of
Cereal Chemists, 3340
Pilot Knob Road, St. Paul, MN 55121.
The
consulting-editing relationship with Hugh J. Roberts of L.I.F.E. and with Peter
Tyler, Tropical Stored Products Centre, warrant special
mention.
Credit is given to
the El Salvador Centro Nacional de Technologie Agropecuaria
(CENTA) for providing field and laboratory assistance in
evaluating portions of this
manual.
Participants at the
two meetings and authors are given in the lists that follow.
PARTICIPANTS AT THE
POSTHARVEST GRAIN LOSSES
METHODS WORKSHOP
Harpers Ferry, WV
September 8-10, 1976
J. Mervyn Adams. (now) The Wellcome Foundation, Ravens Lane,
Berkhamsted,
Herts., England
Keith Byergo. Crop Protection, Office of Agriculture, Bureau
of Technical Assistance,
Agency for
International Development, Washington, DC 20523
Howard R. Cottam. Consultant, 2245 46th St. N.W., Washington
DC 20007
M. G. C. McDonald Dow. Board of Science and Technology for
International Development,
National Academy
of Sciences, 2101 Constitution Ave., Washington,
DC 20418
Maryanne Dulansey. Consultants in Development, 298 West 11th
St., New York, NY
10014
Kenton L. Harris. Consultant, 7504 Marbury Road, Bethesda,
MD 20034
William J. Hoover. American Institute of Baking, Box 1448,
Manhattan, KS 66502
Henry Kaufmann. Cargill, Inc., Box 9300, Minneapolis, MN
55440
Carl Lindblad. Consultant, 1706 Euclid St. N.W., Washington,
DC 20009
Floyd E. O'Quinn. 7328 Range Road, Alexandria, VA 22306
Priscilla Reining. International Office, American
Association for the Advancement of
Science, 1515 Massachusetts
Ave. N.W., Washington, DC 20005
Hugh J. Roberts. League for International Food Education,
1126 16th St. N.W.,
Washington, DC
20036
PARTICIPANTS AT THE
SLOUGH, ENGLAND
WORKSHOP ON
POSTHARVEST
GRAIN LOSS METHODOLOGY
June 13-24, 1977
J. Mervyn Adams. (now) The Wellcome Foundation, Ravens Lane,
Berkhamsted,
Herts., England
Bill Andrews. TPI (TSPC), London Road, Slough, Berks,
England SL3 7HL
Andy Baker. TPI (TSPC), London Road, Slough, Berks, England
SL3 7HL
Robin Boxall. Institute of Development Studies, University
of Sussex, Brighton, Sussex,
England
Geoffrey G. Corbett. FAO, Via delle Terme di Caracalla,
00100 Rome, Italy
David Dendy. TPI, Industrial Development Department, Culham,
Abingdon, Oxon,
England
Jacques Deuse. IRAT, B.P. 5035, Montpellier, France
Bruce Drew. Pillsbury Company, 311 2nd St. S.E., Minneapolis,
MN 55414
David Drummond. Ministry of Agriculture, Fisheries and Food,
Pest Infestation Control
Laboratory,
Tolworth, Surrey, England
Rennie Friendship. TPI (TSPC), London Road, Slough, Berks,
England SL3 7HL
Peter Golob. TPI (TSPC), London Road, Slough, Berks, England
SL3 7HL
Martin Greeley. Institute of Development Studies, University
of Sussex, Brighton,
Sussex, England
Geoffrey Harman. TPI, 56/62 Gray's Inn Road, London WCIX
81U, England
Kenton L. Harris. AACC/L.I.F.E., 7504 Marbury Road,
Bethesda, MD 20034
Noel Jones. TPI, 56/62 Gray's Inn Road, London WCIX 81U,
England
Carl Lindblad. AACC/L.I.F.E., 1706 Euclid St. N.W.,
Washington, DC 20009
Matthias Von Oppen. ICRISAT, Hyderabad, India
Elizabeth Orr. TPI, 56/62 Gray's Inn Road, London WCIX 81U,
England
Harry Pfost. Department of Grain Science and Industries,
Kansas State University,
Manhattan, KS
66506
Peter F. Prevett. TPI (TSPC), London Road, Slough, Berks,
England SL3 7HL
Barbara Purvis. ESHH, FAO, Via delle Terme di Caracalla,
00100 Rome, Italy
Eberhard Reusse. FAO, Via delle Terme di Caracalla, 00100
Rome, Italy
Robert A. Saul. 1412 Martin Road, Albert Lea, MN 56007
Gerard G. M. Schulten. Royal Tropical Institute, 63
Mauritskade, Amsterdam-Oost,
Netherlands
Harlan Shuyler. FAO, Via delle Terme di Caracalla, 00100
Rome, Italy
Philip Spensley. TPI, 56/62 Gray's Inn Road, London WCIX
81U, England
Malcolm Thain. TPI, 56/62 Gray's Inn Road, London WCIX 81U,
England
Peter Tyler. TPI (TSPC), London Road, Slough, Berks, England
SL3 7HL
David Webley. TPI (TSPC), London Road, Slough, Berks,
England SL3 7HL
AUTHORS
J. Mervyn Adams. (now) The Wellcome Foundation, Ravens Lane,
Berkhamsted,
Herts., England
Geoffrey G. Corbett. FAO, Via delle Terme di Caracalla,
00100 Rome, Italy
David Dendy. TPI, Industrial Development Department, Culham,
Abingdon, Oxon,
England
Bruce A. Drew. The Pillsbury Company, 311 2nd St. S.E.,
Minneapolis, MN 55414
P. Golob. TPI (TSPC), London Road, Slough, Berks, England,
SL3 7HL
Theodore A. Granovsky. Department of Entomology, Texas A
& M University, College
Station, TX
77843
John H. Greaves. Pest Infestation Control Laboratory,
Tolworth Surbiton, Surrey,
England
Martin Greeley. Institute of Development Studies, University
of Sussex, Brighton,
Sussex, England
Allan Griff. 5324 Wakefield Road, Bethesda, MD 20016
Geoffrey W. Harman. TPI, 56/62 Gray's Inn Road, London WCIX
81U, England
Kenton L. Harris. 7504 Marbury Road, Bethesda, MD 20034
William J. Hoover. American Institute of Baking, Box 1448,
Manhattan, KS 66502
William B. Jackson. Bowling Green State University, Bowling
Green, OH 43403
Henry Kaufmann. Cargill, Inc., Box 9300, Minneapolis, MN
55440
Carl J. Lindblad. 1706 Euclid St. N.W., Washington, DC 20009
Guy Martin. I.T.C.F. Cereal Laboratory, 46 rue de la Cleff,
75005 Paris, France
Jean-louis Multon, Institut National de la Recherche
Agronomique, 44072, Nantes
Cedex, France
T. N. Okwelogu. Produce Inspection Headquarters, PMB 1012,
Enugu, Anambra
State, Nigeria
Conrad C. Reining. Department of Anthropology, The Catholic
University, 620 Michigan
Ave. N.E.,
Washington, DC 20011
Eberhard Reusse. FAO, Via delle Terme di Caracalla, 00100
Rome, Italy
Robert A. Saul. 1412 Martin Road, Albert Lea, MN 56007
Gerard G. M. Schulten. Royal Tropical Institute, 63
Mauritskade, Amsterdam-Oost,
Netherlands
Manfred Temme. Environmental Studies Center, Bowling Green
State University,
Bowling Green,
OH 43403
POSTHARVEST GRAIN LOSS
ASSESSMENT METHODS
PREFACE
When world food is
viewed in terms of a system of production, distribution,
and utilization, it becomes obvious that in our attempts to
improve the system
we have allocated most of our resources to the production
component. Distribution
and utilization have been comparatively neglected. But
hunger and
malnutrition can exist in spite of adequate food production.
They can be the
result of unequal distribution of food among nations, within
nations, within
communities, and even within families. Loss and
deterioration of available
food resources further adds to the problem. Hence, maximum
utilization of
available food is absolutely essential.
Of the agricultural
commodities consumed as food, grains (cereals, legumes,
oilseeds) contribute the bulk of the world's calories and
protein. The food
grains system is depicted in Fig. 1, which shows the many
points at which
pgl1x2.gif (600x600)
losses of food occur. The reduction of postharvest grain
losses, especially
those caused by insects, microorganisms, rodents, and birds,
can increase
available food supplies, particularly in less developed
countries where the
losses may be largest and the need is greatest.
In September 1975,
the growing international awareness of the need for
reducing postharvest food losses culminated in a resolution
of the Seventh
Special Session of the United Nations General Assembly
stating that "the
further reduction of post-harvest food losses in developing
countries should be
undertaken as a matter of priority with a view to reaching
at least 50% reduction
by 1985." Yet, following the Seventh Special Session,
an Interdepartmental
Subcommittee reviewed past and current activity and
concluded: "There is
no agreed methodology of post-harvest loss assessment.
Moreover, loss data
are generally unrelated to the cost of loss reduction.
"
In its
interpretation of available information on losses, the Subcommittee
concluded that "there can be no agreed single figure
for the percentage of
post-harvest losses on a global scale or even on a national
basis. There is
clearly a need for more accurate assessment of these losses,
to establish firm
justification for the development and introduction of
measures designed to
reduce them where the cost/benefit ratios of corrective
measures are favorable."
The goal of this
volume is to provide postharvest grain loss assessment
methods yielding standardized and reproducible results so
that effective grain
loss reduction efforts can be undertaken in developing
countries. The assessment
information from such a manual may provide essential
justification and
motivation for introducing measures designed to reduce grain
losses.
This volume is
prepared in large part for use by policymakers who need loss
information both in determining national priorities and
requirements and in
bringing their efforts to bear on the small farmer and other
small-volume grain
handlers. It is also directed to the individual investigator
who seeks a basic
guide in his specific investigations. The manual is aimed
primarily at loss
assessment in developing countries.
Although a
methodology for assessing postharvest grain losses will not in
and of itself reduce those losses, the methodology is
essential to postharvest
operational programs so that priorities for loss reduction
can be determined.
In addition to serving as a much-needed assessment tool, the
methodology and
other activities proposed can serve as a means to persuade
all concerned that
change is necessary and that effective techniques for
reducing losses are available.
Even financial constraints can disappear when priorities are
reordered.
As detailed later in
this Preface and in Chapter II, the enormous variability
of local postharvest situations dictates that no complete or
definitive loss
assessment methodology for all situations is now possible.
Thus, this edition is
not proposed as a final and absolute piece of work. For
example, there exists
very little experience which can be drawn from in loss
assessment of cereal
grains such as sorghum, millet, teff, and major oilseeds.
Judgment will be
required to adapt known assessment methods to those grains
and to other loss
situations not dealt with in sufficient depth here. Further,
the editors realize
that expansion and refinement of the loss assessment
techniques presented in
this manual are desirable and necessary as a continuing
process.
Increasing food
production by increasing acreage or yield per acre has been
a readily applied concept while reducing losses to increase
food supplies was a
less obvious strategy. This occurred in spite of the
availability of a considerable
body of information on postharvest grain losses, and in
spite of several
decades of research and development on losses and their
control.
Progress in
reducing postharvest food losses requires the identification and
elimination of the constraints to the application of
existing technology. The
major constraint may be a lack of finances, but it is
equally possible that lack
of knowledge and of trained personnel, as well as political
and cultural constraints,
exists. In 1975 an FAO Subcommittee position paper
identified four
constraints to the effective use of available technology for
reducing on-farm
losses: 1) lack of arrangements for producing the necessary
inputs, 2) inadequate
distribution channels for the necessary inputs, 3) lack of
purchasing
power or credit arrangements for the farmer to buy the
inputs, and 4) inadequate
information to the farmer on how to use the inputs.
While calling for
integrated country programs to address these constraints,
the Subcommittee stressed the need for creating "an
awareness throughout
national extension services that on-farm losses are serious
and can be significantly
reduced." Postharvest loss reduction intervention must
be made, however,
with specific techniques applied to reduce specific losses.
While there
may be broad sweeping national needs, not only are the
techniques specific,
but they must be applied at specific intervention points.
Until data are available
to show the potential gain from the elimination of losses
amenable to
reduction, motivation to reduce those losses will not be
strong. But aggregate
data reflecting losses on a global or even on a national
basis are not really
useful even if it were possible to obtain them. They are
singularly unpersuasive
to a farmer, trader, or warehouseman who must lay out his
money and time.
Losses vary by
crop, variety, year, pest and pest combination, length of
storage, methods of threshing, drying, handling, storage,
processing, transportation
and distribution, rate of consumption, and according to both
the
climate and the culture in which the food is produced and
consumed. Given
such enormous variability, it is not surprising that
reliable statistics regarding
the type, location, causes, and magnitude of postharvest
grain losses are not
available. Yet reliable and objective methods for generating
them are needed if
priorities are to be given to the reduction of losses. This
is needed in regional
and national planning and in motivating those organizations
which may fund
loss-reduction programs, and on down to the local level.
Meanwhile, it is
prohibitively expensive and unjustifiable to mount countrywide
assessment studies of losses in the whole postharvest
system. As detailed
in Chapter II, an expert judgment is needed to identify the
most serious grain
loss points in a country's postharvest food supply system in
order to mount
in-depth assessment efforts at those high loss points.
Stated another way,
changes will not be widely accepted until and unless
they are practical for and clearly benefit the individual
who is to make the
change. Although losses and savings are far from the only
elements which
must be considered in loss reduction efforts, reliable
figures can go a long way
in convincing those dealing with grain, and certainly for
motivating those
organizations which may fund the loss reduction programs.
Extent of loss is
important, but not all-important. Other factors should be
considered in deciding on the nature of interventions, or
whether to intervene
at all: The value of the grain in economic lines; the fact
that there will be social
change effected by intervention programs; competition or
conflict, or both,
with other national priorities; effect on price stability
and similar economic
considerations; the relationship and possible conflict of
economic factors that
affect the consumer, grain grower, grain trader, and
national balance of payments
mean that interventions need to be subjected to an
integrated, multidisciplinary
evaluation and actually field tested within the social and
economic
structure before they should be implemented on a broad
scale.
Both
"guesstimates"(1) by knowledgeable people and estimates without
factual
basis, particularly by people with vested interests, have
had a useful role in
the past, will continue to be used in the future, and are
especially useful when
timely opinions are needed as to where the more serious
losses occur. In using
guesstimates to justify cost/benefit comparisons or to
reshape established
practices, however, one needs to recognize the possible bias
of the estimator:
Was it put in perspective by a thorough gleaning of the
information, was the
judgment based on an in-depth and long-standing knowledge of
local or even
country-wide conditions, was it made to reveal some
situations and cover
others? It is critical to understand that guesstimates are the
type of estimations
that requires the most expert judgment.
If large area or
national survey figures are taken without sufficient regard
for variations in the individual components, these figures
may not be useful to
locate specific intervention points.
Finally, we might
ask why, in the face of a need for accurate figures that has
not gone unnoticed over at least two decades, have there
been so many postharvest
loss estimates made with obvious biases, and why has a
methodology
not been forthcoming from the scientific community?
As stated above,
the guesstimates have served a useful purpose. They have
also been accepted by those seeking national resources and
changes as well as
by those allocating international resources. Although the
scientific need was
there, the political- and transformation-related
requirements did not call for
scientifically derived figures. Now, with increased
sophistication and increasingly
limited resources requiring benefit-related priorities,
there is a need to
know what the postharvest losses really are. Without such
information, it is
impossible to assess needs or to calculate improvements.
However, there has
been another factor that has stood in the way of assembling
this manual. It
needs to be mentioned, for its recognition is the key to the
present status and
ultimate fate of this volume. This factor has been the
simple absence of anyone
to do the job.
Within the L.I.F.E.
consortium, the American Association of Cereal Chemists,
under a contract from the Office of Nutrition, Technical
Assistance Bureau,
U.S. Agency for International Development, has broken the
impasse on
-------------------------
(1)This term is
used to connote estimates with some facts by knowledgeable people.
how and by whom the job was to be done, and it has developed
and printed
this volume with the hope that it is a volume to be
evaluated, tested, and
improved by actual use in the field. We look forward to the
inevitable changes.
Kenton L. Harris
Carl J. Lindblad
August 1978
I. INTRODUCTION
K. L. Harris and C. J. Lindblad
This volume is
directed mainly to grain loss situations in developing countries.
Determination of
losses to food crops requires careful blending of the concepts
and procedures of several sciences while each is given its
necessarily
detailed attention. Nowhere is this more true than in
dealing with postharvest
losses to grain. Information gathering ranges from A to Z,
and at the outset
emphasis needs to be given to the cultural-social aspects
discussed in Chapter
III.
While many of the
methods contained in the manual relate to the evaluation
of damage caused by a single organism or mechanical effect,
such selective
attacks rarely occur in nature. Interactions between major
causes of losses
must be expected.
A basic concept of
this manual is that it be applied in its entirety. Care needs
to be taken that personal, national, economic, cultural, and
other biases do
not generate unwarranted project plans or conclusions. To
illustrate, large
influential farmers may want technologies developed to suit
their own needs
which may be completely inappropriate for small farmers
whose grainhandling
systems are less mechanized or capital intensive, grain
storage scientists
may want to continue in their own research area to the
exclusion of other
equally important areas, national governments may favor one
political region
or group over another, or international development agencies
may have their
own priorities.
There are many ways
to produce a list of intervention points. Consideration
could be given to technological improvements that would both
cost the least
and prevent the greatest amount of grain losses to the
benefit of the entire
country as a whole. However, political, economic, and social
priorities need to
be taken into account in locating and identifying
intervention points. What is
technologically ideal may be very different from what is
practical and feasible
within the actual social, economic, and political environment.
A balancing of
technical and social sciences is essential in assessing and
reducing grain losses.
For the purposes of
identifying loss points which are critical and amenable
to reduction, this manual uses the pipeline concept to
describe the location and
flow of grains. In this way, losses can be viewed
individually and in perspective;
however, the pipeline concept is not limited to technical or
physical
factors. Social realities come into play and perspective is
required to both
understand those attendant social influences and to prevent
them from being
blindly introduced as unrecognized bias. The pipeline
approach weighs individual
loss points in relative magnitude. Combined with
consideration of social
realities which influence amenability to in-depth assessment
and loss reduction,
the pipeline concept serves to 1) identify critical loss
points for in-depth
assessment and 2) provide a basis for development of
improved technologies
for postharvest loss reduction.
The influence of
personal judgment, and therefore bias, cannot be avoided
though the investigator or official may be unaware of its
role. The investigator
must also constantly guard against yielding to pressures
based on unsubstantiated
assumptions. An example of the consequences of this kind of
oversight
is seen in the countless huge, empty, and decaying grain
bins installed across
the developing world under incorrect assumptions. They serve
to demonstrate
that what is feasible in one situation will not necessarily
be successful in
another.
The compilers of
this manual have operated under the well-reasoned opinion
based on some practical experience that interventions to
reduce grain loss
are often best channeled to the farmer/producer. There are a
number of
reasons for this alignment. One technical reason is that the
best form of loss
reduction is early prevention -- grain which is in good
condition will deteriorate
more slowly than grain which is, for example, already
infested with insects
or poorly dried. Following that logic, to assure good
quality food grain
throughout the pipeline, it seems practical and desirable to
have it enter the
pipeline under optimal harvesting, drying, and storage
conditions. Another
factor is that, in developing countries, much of the grain
is stored and consumed
in the rural areas, in large part by farm families.
A loss assessment
study that does not have built into it the strong possibility
and intention of benefiting the situation under study is of
no consequence. The
purpose of loss assessment is effective and expeditious loss
reduction. Loss
assessment need not and should not be a largely academic
exercise.
Loss-causing damage
may not divide into neat, exclusive categories. Moldy
kernels may be insect infested and vice versa. Insects can
cause shattering, and
shattered kernels more readily support certain insects. Bits
and pieces lost
through holes in bags or in processing may have been
produced by too rapid
drying. These and other situations are more the normal than
the exception and
need to be duly noted and judgment applied in interpreting
data.
Certain concepts
are dealt with in only one section of the manual though
they have applications throughout many facets of loss
assessment and reduction.
For example, while the subject of economics is in a separate
section, it
has applications throughout the manual. It bears on sampling
and how, when,
and where the samples are taken. It bears on the selection
of study situations
and how they impinge on each other, and it relates to
cultural factors. Similarly,
cultural factors are dealt with in a separate section though
their implications
are also pervasive as they bear on sampling, analyses, and
the whole
problem of functioning in a system without undesirably
changing or destroying
it.
Early in the
preparation of this first edition, an attempt was made to prepare
a manual that could be used by trained and untrained workers
alike. This
proved to be impossible. The ideal of writing for those
without any background
in grain storage, biology-entomology, food marketing, or the
socio-economic
sciences was attempted and abandoned as impractical. The
material
is, therefore, prepared for people with at least some
pertinent experiential or
academic background.
One of the
important matters not covered in this manual is the matter of
mold toxins. This does not downgrade the seriousness of the
mycotoxin problem.
Important as the problem is, this volume is concerned with
measuring
losses of stomach-filling grain, not whether its nutritional
value has been
reduced. While strongly noting that food contaminated with
mold toxins is to
be avoided, as regards mold-caused losses, this manual deals
only with such
losses of grain actually discarded for human food because of
the presence of
mycotoxins.
II. TERMS OF REFERENCE
A. Definitions
K. L. Harris and C.J. Lindblad
This manual deals
with food grains, cereals, and pulses and the word
"grain" is broadly used to include all of these.
It deals exclusively with the loss
of food from the food chain and largely follows the
definitions of Bourne (1).
In it, a working definition of the term "postharvest
food loss" is set forth as
given below:
"POST
HARVEST" means after separation from the medium and site
of immediate growth
or production of the food.
Post harvest
begins when the process of collecting or separating food
of edible quality
from its site of immediate production has been completed.
The food need not
be removed any great distance from the harvest
site, but it must
be separated from the medium that produced it by a
deliberate human
act with the intention of starting it on its way to the
table.
It does not include
steps between cooking and eating as covered by Bourne
and agrees with Bourne to "not cover inefficiencies in
human metabolism and
utilization of the food." In this manual, however, the
pathway ends when the
food grain or the food prepared from the grain, or both,
reaches the point
where it is to be finally prepared (cooked) for consumption.
Three periods of
time may be identified during which food may be lost,
and each period has
its characteristic problems, and means of overcoming
these problems.
a. Preharvest are
losses that occur before the process of harvesting
begins, for
example, losses in a growing crop due to insects, weeds and
rusts.
b. Harvest losses
occur between the onset and completion of the process
of harvesting, for
example, losses due to shattering during harvest of
grain.
c. Post harvest
losses occur between the completion of harvest and the
moment of human
consumption.
Postharvest
intermixes in varying degrees with portions of the maturing-drying-processing
period and often no sharp distinction can be made. Thus,
maize held in the field for drying is also maize held for
storage and use. This
manual does not imply that any artificial sharp distinction
must be made.
Harvest and post
harvest losses are sometimes combined into a single loss
because there are
some elements of common concern between them. A
suitable
descriptive term for these combined activities would be "post
production
losses". The following schematic representation shows the
relationship among
the various types of food losses:
1. Preharvest
2. Harvest
} Post Production
3. Post
Harvest }
In addition to
Bourne's postharvest grain, this manual includes the ripe crop
remaining in the field, whether standing in its original
position or not, for
further drying or holding, or both, until it is brought in
or removed from the
growing position, eg, maize drying/storage in much of Latin
America.
"FOOD"
means weight of wholesome edible material that would normally
be consumed by
humans, measured on a moisture-free basis.
Inedible portions
such as hulls, stalks, [and] leaves . . . are not
food. . . . Feed
(intended for consumption by animals) is not food [unless
specifically of
interest to the individual assessment exercise].
The method of
measuring the quantity of food in the post harvest
chain should be on
the basis of weight expressed on a moisture-free basis.
There will be times
when information on losses in nutritional units and
economic losses
will also be needed but these should not be the prime
means of measuring
post harvest food losses.
"GRAIN
LOSS," as used in this manual, concerns the loss in weight of
food that would have been eaten had it remained in the food
pipeline.
"LOSS"
means any change in the availability, edibility, wholesomeness
or quality of the
food that prevents it from being consumed by people.
Food losses may
be direct or indirect. A direct loss is disappearance of
food by spillage,
or consumption by [insects], rodents, [and] birds. An
indirect loss is
the lowering of quality to the point where people refuse to
eat it.
This definition
is a people-centered definition. "Food" means those
commodities that
people normally eat and excludes the commodities that
people do not
normally eat. If the food is consumed by people it is not
lost; if it is not
consumed by people for any reason at all then it is
considered a post
harvest food loss.
Food losses are, at
times, simply as they are locally defined or as they locally
occur. For example, grain which is discarded because of
discoloration is a loss.
Processing losses
occur when edible portions of food are removed from
food channels by the process or by spillage or breakage from
the process. Rice
hulls are inedible. Their removal does not constitute a loss.
Rice pieces
diverted from the food-chain are a loss. Rice bran is edible
to some, inedible to
others. The handling of each similar situation needs to be
clearly defined as it
occurs. Corn cobs or cores are not a loss. The corn seedcoat
is removed in
making corn grits. It is not removed in making many other
foods. How it is
handled needs to be defined in each appropriate instance.
Where quality
deterioration results in a loss in weight or in the food not
being eaten at all, eg, rejected in the marketplace, the
rejected food is a loss. In
this volume, quality is a consideration only as it relates
to loss in weight of
food, but how it is handled needs to be defined
appropriately in each instance.
The term
"insects" includes true insects (six-legged arthopods) and
grain-damaging
mites.
Microbiological
losses and microbial losses are used interchangeably to refer
to losses caused by molds, yeasts, and bacteria.
Literature Cited
1. BOURNE, M. C. Post harvest food losses -- the neglected
dimension in increasing the world
food supply.
Cornell International Agriculture Mimeograph 53 (1977).
CHAPTER II
B.
Planning: An Overview for Project Administrators
K. L. Harris
Determining
agricultural losses involves many disciplines and goes to the
heart of established cultural patterns. Administrators need
to recognize the
complexities of what they have to deal with and understand
that unless defects
in planning and implementation are overcome, the results
will be jeopardized.
While this is an obvious platitude, it is of special
importance here since the
nature and quality of the operation can set the stage for
the nature and quality
of other programs that may follow in the technical and lay
community.
Without attempting
to set forth an administrative manual, the following
details are to be noted:
1. Project
planning, depending on circumstances, may require inputs from,
for example, agricultural economics, agricultural
engineering, agricultural extension,
administration, anthropology, biology-zoology,
cultivators/grain
owners, education, entomology, food marketing, grain storage
science, microbiology,
political science, rural sociology, and statistics.
2. Revealing the
status of the food grain supply may be a delicate matter
that impinges on matters of national and international
security, as well as on
local, national, and international commodity markets and on
foreign exchange
balances.
3. One needs to be
aware of social factors; special village allegiances and
requirements; the role of women, the family, and other
groups; and whether
information is best collected by lower-status field-workers,
peers, higher-ranking
individuals, etc.
4. Logistic
requirements are imposed by terrain, delineated and undelineated
boundaries; presence or absence of containers, scales,
meters, transport;
local customs and work patterns; and training requirements
and capabilities.
5. Assessment work
needs to be understood in terms of cultural factors:
local vames and definitions and local social and
agricultural systems.
6. The assessment
must relate to local needs -- individual, national, and all
in-between.
7. One should be
aware of the interrelations between postharvest losses and
preharvest.
Basic survey
operations, schedules, and plans are set forth in Table I and
Fig. 2. The time needed for such a survey will obviously
depend on the size of
pgl2x17.gif (600x600)
the country and accessibility of the sampling areas, but the
decision on the
selection of farmers must take place before any final work
begins so that
sampling visits can start immediately after harvest or any
other start-up time.
Modifications to the sampling pattern may be made in the
case of crop failures
or similar unavoidable circumstances.
The nature of the
operation -- and planning for the operation -- will
depend primarily on the factors that are to be investigated
and how they are to
be investigated. This is the subject of this manual.
This manual deals
with 1) obtaining a planning overview of grain movements,
the grain pipeline, 2) determining what portions of the
pipeline should
TABLE I
Basic Plan of Operation
Timing
Stage
Weeks
Activity
Personnel(a)
Preharvest 6
1
Familiarization with local
CO
agricultural structure and
geography
2
2 Preliminary survey
for choice CO, ES
of sampling areas
2
3
Fact-finding visit to chosen
CO, ES
sampling areas for information
on storage practices to
identify
strata and select appropriate
method of obtaining farmers
Harvest(b) up to
4 4
(If required, construction of
CO laborers
experimental stores)
2
5
Initial visit to selected farmers
CO, Exp, ES,
to obtain basic information and
LA
baseline samples (also purchase
grain for experimental silos)
Postharvest(b) 1-3
6 Examination of baseline
samples Exp, LA
in laboratory and check on
proposed methodology
1
per 7
Monthly sampling visits to selected
LA, ES
month farmers to collect
samples and
record consumption patterns
1
per 8
Laboratory examination of field
LA
month samples (and experimental
samples)
7
9
(If required, brief questionnaire
CO, ES
survey of other farmers to confirm
storage pattern)
2
10
End-of-season visit to selected
CO, Exp, ES
farmers to check consumption and
thank for cooperation
Next
Harvest
4
11 Analysis of results in terms
of Exp
loss per sample and integration
with consumption pattern
12 Preparation of report
CO, Exp
(a)CO = Country project officer; ES = extension staff; Exp =
expert TSPC;
and LA = laboratory
assistant.
(b)Drying, processing, bulking, etc.
Adapted from: Tropical Products Institute, Tropical Stored
Products Centre,
Slough, England.
be further investigated both because of the size and nature
of the losses and
their feasibility for reduction, and 3) conducting the
detailed investigations.
This manual also
stresses the use of existing in-country data on what grains
are produced in what quantities in what regions and
consumption patterns.
CHAPTER II
C. An Overview of
the Postharvest System: The Food Grain[\N
Supply Pipeline (Determining the Interrelationship and
Relative
Magnitude of Losses)
K. L.
Harris, W. J. Hoover, C. J. Lindblad, and H. Pfost
The flow of grain
from its sources, ie, the farm field or import docks, to the
eventual consumer is depicted for the purposes of this
manual as a pipeline
with many possible interconnecting pipes and reservoirs.
Losses, or leaks, can
occur along the entire pipeline -- during harvesting,
drying, transport, storage,
and processing. As presented in the Preface, the purpose of
viewing the
food grain supply system as a pipeline is to assign
individual loss points (eg,
on-farm losses) relative importance in terms of loss in
other parts of the grain
pipeline (eg, transport or warehousing losses). This
relative perspective is necessary
to see the importance of the total amount of grain actually
lost in any
given point as opposed to the percentage of grain lost which
passes through
that point. Failure to obtain such a perspective has
resulted in overly high and
low loss figures arrived at by extrapolating from observed
losses at specific loss
points without putting those losses into the perspective of
the grain moving
through the total system.
This failure and
the need to obtain an overview often apply to expatriates
and others entering a system for the first time.
One needs to use
all possible local information to determine how and when
the grain moves from harvest to consumer, routes for
movement and holding
patterns, and where and how processing is accomplished. Most
of this information
is known locally.
Grain does not move
in a straight line and uniform sequence from producer
to consumer. Harvested grain can be specially dried and
otherwise treated to
go into special household use; some into an even more
special seed-grain
storage. This grain may remain there or move out for food or
trade under
special conditions influenced by factors such as family,
weather, or government.
It may even be replaced by other local or imported grains. A
portion of
the harvest may be held for short-term storage, a part for
long-term storage,
and the rest sold or otherwise traded off the farm.
All of these
factors, and more, need to be kept in mind in determining where
and what should be tested.
Delineation of the
test sites involves looking closely at general loss situations
and careful on-site evaluations of specific individual
sites. Selection of "amenable"
sites (villages, cultivators, markets, transit systems,
warehouses) requires
incorporation of many factors. Accessibility must be
balanced against
the location being atypical because of proximity to outside
influences. Traditionalism
must be balanced against the need for outsiders to be
accepted into
the delineated area. Language can be a key barrier, and an
absence of direct or
completely competent and trusted lines of communication is
unacceptable for
loss survey teams. Sex roles must be considered as to who
really does the
harvesting, threshing/cleaning, storing, and marketing of
the grain. All parameters
need to be considered, and should cover the entire social,
cultural,
physical, commercial, and political setting.
Even the simple
village market has flowing through it all these effects, and
more, so that if there were to be a single measurement it
would, in reality,
consist of measurements of many factors, each weighted as to
volume.
Knowledge of actual
high-loss and low-loss situations is required in determining
the need for, location of, and types of interventions.
However, inordinately
high- and low-loss situations must be put into perspective
rather than
giving them overemphasis as has been the case in some
instances.
To further
illustrate, out-of-condition grain held by market speculators may
suffer very high losses, say 30%. Taken by itself, this
level of loss might
identify grain speculators as a critical focus for improved
storage technology
intervention. However, if in fact only 5% of the total grain
supply is ever
handled by such speculators who specialize in
out-of-condition grain, the real
value of the total losses at this speculator level becomes
30 x 5%, or 1.5%
rather than 30% of the total grain supply.
A useful
investigation of postharvest grain losses requires detailed knowledge
of the entire postharvest food grain supply pipeline.
Figures 3 and 4 are
pgl3x200.gif (600x600)
two representations of supply pipelines. Figure 3 emphasizes
marketing patterns;
pgl3x20.gif (600x600)
Fig. 4 emphasizes the processing flow through to the
consumer. At any
pgl4x21.gif (600x600)
one point, grain or grain products may move out of one
pipeline, around
several intervening steps, and re-enter further along in the
sequence. Similarly,
movement occurs in both directions. Grain gleaned from the
field or from
spillage on a farm or in a rural market can go immediately
to a consumer or
may be bartered back into a trade channel. What might be
loss to a farmer by
spillage at a local market, or to a transport company, may
in reality be a mode
of payment for services rendered at an otherwise unacceptably
low pay scale.
In each country,
district, or community area, there exists a marketing system
for food grains. It is imperative that the flow of grain
through the various
facets of this marketing system be quantified so as to
establish priority points
for observance and measurement of losses, and to
subsequently focus attention
on loss prevention programs. Figure 5 shows a quantified
flow in which
pgl5x22.gif (600x600)
different grains and oilseeds follow different routes.
Moreover, different
parts of the pipeline have different flow rates. While a
particular grain may be in a storage chamber for some time,
it may be in a
milling process for a very short time. The types of losses
at those two locations
are different; one is a loss which increases over time, and
the other is probably
a one-time loss due to such things as poor physical
handling, equipment, or
packaging.
To follow the
pipeline analogy, the two types of losses occur in the reservoirs
and in the pipes. Once grain has passed through a leaky pipe
(eg, a poorly
adjusted grinder), it is not subject to that particular loss
any longer. However,
grain in a holding reservoir (eg, rodent-infested bin) is
subject to those losses
for as long as it remains there. Loss assessment methods and
calculations for
the two types of losses can be quite different.
This, of course,
complicates the task of assessing losses. Separate measurements
are required for the different types of losses that occur
due to mishandling
or poor equipment settings, in addition to the biological
deterioration
caused by insects, rodents, or moisture or other climatic
conditions. Sampling,
tracing, eventual utilization, and testing of overall losses
really entail making
and evaluating individual, components in a system and
calculating their overall
effects. Moreover, since effective loss reduction
interventions need to be
directed to the reduction of specific leaks, it is the
individual loss figures that
need to be evaluated, not overall national figures.
Note: With the acknowledged limitation of development
resources and perhaps
even greater limitation of available, trained personnel, the
pipeline concept
is an approach that is recommended as a means of quickly and
inexpensively
focusing on significant losses in the overall system. It is
also an effective
procedure for effective resource allocation.
There is every
reason to believe that the presence of a survey in the system
will itself affect the system and the results of the survey.
This will not be
discussed other than to note that economic, cultural, and
political factors
governing the flow and treatment of grain can be expected to
respond to the
survey itself, thus partially skewing the results.
CHAPTER II
D. Preliminary
Examination of Specific Problem Points and
Making On-Site Rapid Appraisals
G. G.
Corbett, K. L. Harris, H. Kaufmann, and C. J. Lindblad
Two of the most
critical aspects of postharvest grain loss methodology are
the need to not attempt more than is feasible, and to
rapidly seek and identify
for investigation major loss situations that seem both
amenable to study and
responsive to improvement through practical interventions.
By using a pattern
that has found almost universal application by expatriates
from international
and national agencies whether dealing with the most
primitive situations or the
most sophisticated, this first appraisal has become accepted
as a 30-day exercise.
However, 30 days may be too little or too much time,
although this will
only be determined by the complexity of the system and the
nature of the
questions being asked.
As with any
investigation, some early judgment is made that the work is
needed and that there is a reasonable likelihood that useful
results will be
obtained. After that there is a need to work with local
officials in a preliminary
fact-finding canvass of the situation that goes into the
entire nature of the
grain pipeline, as explained earlier, and then into
individual problems and
their projected solutions. This includes all of the grain
movement logistics,
personnel, political and cultural ramifications, etc., that
will be called into, or
will force themselves into, the final study.
It would be well
for this preliminary canvass to proceed solely as a prelude
to a larger study, but such will not always be the case when
immediate developmental
decisions must be made before detailed information can be
made available.
Interrelated
aspects will proceed together during the 30- to 60-day preliminaries:
Assessment exercises
may be undertaken by expatriates to determine losses,
while locals seek to determine how to reduce the losses.
One task is the
probing for specific problem points; the other is the job of
making rapid on-site appraisals.
One looks ahead to
a more definitive investigation; the other comes to
on-site loss and intervention judgments within the
rapid-assessment time span.
In one case we are
developing a strategy to conduct a survey; in the other,
the survey and loss reduction efforts may be rapidly under
way.
Preliminary Examination of Specific Problem Points
An initial survey
is needed to determine what the problem is and what has to
be done. In the initial survey the best possible information
available should be
used to ascertain the order of magnitude of the losses in
the whole postharvest
system and to identify the major points and causes of
losses. As the loss figures
are evaluated and observed to be accurate or inaccurate,
they may serve as
data to evaluate the local system. It is important to obtain
information from
people who are knowledgeable of the factors being assessed
as well as from
voluble proponents of biased or special interest positions.
Already available
reliable information, or lack of it, will help to decide the
depth and focus of
the preliminary mission.
The key element is
to identify those problem points that can be adequately
isolated, are likely to yield useful information, and are
amenable to study and
loss reduction intervention.
Few locations in
the grain pipeline will be neatly packaged, single-entrance,
single-exit, one-measurement situations. It may be necessary
to make measurements
over a period of time, to identify the points at which
important losses
are occurring, and to make an estimate from the data and
evidence available of
the order of magnitude of these losses. After such a survey
(which will probably
reveal the need for longer-term assessment of losses), it
will be possible to
define immediate, as well as longer-term actions. At the
same time, the cost/
benefit implications for both the operators concerned and
the country as a
whole must be considered.
The composition of
the 30- to 60-day preliminary investigation mission will
vary according to the complexity of the grain industry and
the local information
and expertise available. At least a grain marketing
economist and a grain
storage specialist (entomologist-biologist) should be
included plus a processing
specialist if it is anticipated that processing losses at
village or industrial level
are important.
Members of the
preliminary mission must have experience in the organization
and operation of the grain industry in developing countries.
The social
skills acquired by direct experience are invaluable and
essential for the judgments
which must be made during the preliminary survey. As
experience is so
critical here, interns would usefully be included in the
mission; however, large
missions (more than four) are often hard to accommodate
within traditional
social structures.
The mission will:
1. Map the pipeline
using available government statistics and other inputs
from key informants.
2. Conduct an
initial survey of the postharvest grain sysem to establish who
is handling, storing, transporting, and marketing the
harvested crop; what
part of the crop is handled and stored by each operator, and
for how long,
including farm storage for self-consumption purposes; and
the condition of
handling, storing, and processing.
3. Review all
available data on quantitative and qualitative losses occurring
in the system(s) and identify the major causes and extent of
loss.
4. Prepare an
inventory of available storage, transport, marketing, and
processing facilities and assess their adequacy in capacity,
design, and condition.
5. Review the
present activities being undertaken to reduce postharvest
losses and list the resources available for these activities
from both internal and
external sources.
6. Design a phased
action program to investigate or implement under the
project terms of reference.
In conducting the
preliminary study, remember that grain losses occur in
situations that cause or allow them to occur, and as the
losses occur, evidence
is left of what has and is happening and what will probably
continue to
happen.
There are many
clues to both general and individual aspects of grain losses
that can be disclosed by the rapid assessment of a
situation. Knowing that key
elements in insect depredations are moisture, temperature,
numbers and kinds
of insects, length of storage, storage sanitation, and insecticide
use and other
control practices, one can keep the presence or absence of
these factors in
mind and come to some general or specific conclusions based
on known scientific
principles. Estimates of 30% losses to maize stored for
several months
under humid tropical conditions may be quite reasonable. The
same figure
when applied to a cold, dry climate or to grain used up in
three months may be
unreasonable.
Many farmers are
well aware of these factors. Out-of-condition grain is
often passed along to the local market or government agency.
Grain for long-term
storage may be dried, put in better storage, or treated wth
a protectant.
Loss-prone varieties may be used first or sold off the farm.
Some conclusions
will be fairly straightforward. For example, if grain goes
into bagged and naturally aerated storage that has evolved
within the culture,
reasonably good storage quality may occur. If the same high
moisture grain
goes into sophisticated silo storage without the necessary
sophisticated drying,
there will be a high potential for loss. Poor sanitation,
insects, molds, leaking
roofs, rats, uncleaned bins and bags, high atmospheric
humidity, and extreme
temperature variations all affect grain losses.
Generally, when
insect damage is very difficult to find, the weight losses due
to insects are also negligible. One may know what a 250/o
loss in maize looks
like in one region and carry this mental picture to other
regions and other
situations. The significance of frass, of extensive moth
webbing, of adult or
larval insects may be so well known that they automatically
lock into a fairly
accurate judgment -- a judgment that may well be sufficient
for the experienced
person to come to a general conclusion on the extent of the
losses
themselves. This, in addition to contributing to a decision
on whether a situation
should be tested or surveyed in depth, may be as much as the
situation
warrants, especially if the losses are estimated at around
5%. At this low level,
even an in-depth assessment based on currently known
sampling procedures
would probably be subject to an error as large as the loss.
In short, it is
possible to do an overall appraisal based on an expert evaluation
of the system with attention to pertinent parts of the
harvest-to-consumption
flow or patterns, and to such loss-inducing and
loss-reducing
factors as:
1. Moisture
2. Temperatures
3. Insects,
rodents, birds (kinds, numbers, association with the grain)
4. Length of
holding
5. Local quality
and quantity controls
6. Types of bins
and other holding vessels
7.
Sanitation-insanitation
8. Trading quality
factors
9. Use and nonuse
of pesticides
10. Evidence and
nonevidence of grain damage; kinds and amounts
a. Frass and
webbing
b. Exit holes
c. Darkened
(rotten) kernels
d. Degermed
kernels
11. Mechanical loss
factors
12. Location in the
harvest-to-use pattern
The need to apply
the physical loss parameters and to know what stimulates
or retards losses cannot be overemphasized. Many unreasonable
guesstimates
would have been avoided if more attention had been paid to
such criteria. Of
course, these same criteria will provide an operational
arena for in-depth
assessment and loss reduction.
Finally, one needs
to remember that just as losses do not occur in a vacuum,
neither do loss assessments, and one should expect the
presence of a survey -- with
or without an overt attempt to make improvements -- to
induce changes.
III. SOCIAL AND CULTURAL
GUIDELINES
The overall aim of
this chapter is to introduce some of the complex
cultural-social-anthropological factors to postharvest grain
loss assessment/
intervention activities. The message is made up of a variety
of signals that pass
in both directions: from the situation being investigated to
the investigator and
from the investigator to the situation. It is a dynamic
process.
In grain loss
assessments the need is to find out what the situation was or is.
The investigator wants to affect the milieu as little as
possible while he assesses
it. Thus he needs to be in tune with what is happening so
that the assessment
will be an assessment of what he sets out to assess -- not
of what his presence is
bringing about.
This chapter is a
result of many discussions, not only with Allan Griff and
Conrad Reining, but with many others. Griff, Reining,
Harris, and Lindblad,
together with Edna Loose and Maryanne Dulansey, examined,
analyzed, and
reasoned the subject many times together. What has resulted
is the foundation
statement of Part A and the evocative of Part B. Part A is
self-explanatory.
Part B is purposely set forth so as to leave the assessor
with many questions
into his own investigations.
A. The Fact-Gathering Milieu
Allan L. Griff
It seems obvious
that planners and field-workers of grain recovery programs
should be familiar with the social and cultural background
of the places where
they are working. But far too often this knowledge is
insufficient and incorrect,
and the result can be error and waste. Cultural awareness is
no guarantee
of success, but it can help.
This chapter is but
a brief outline of how culture operates, and its place in
the early stages of planning a program. It will raise many
questions. It may
slow down some projects until adequate understanding of the
people is
achieved. It may improve communications enough to get some
projects off a
comfortable and self-perpetuating dead-center. But if one is
committed to
tangible results rather than just good appearances and
completed missions,
culture cannot be ignored -- rather, it must be understood.
Culture is on our
side. Few want grain losses, but only a good understanding
of the roles of
social and economic behavior of the people involved (ie, the
culture) can make
this a contributory factor and not an adversary.
Culture is not Static Tradition
First, we must
erase the stereotype view of culture as stubborn adherence to
tradition and resistance to change. All cultures contain the
seeds of change as
well as the inertia to resist change. This is the basis of
cultural evolution.
Changes can and must occur for a society to survive, but
they must be opposed
and tested to ensure that they achieve their aim, that the
gains are worth the
losses, and that change does not occur so fast that the
people cannot adapt to
it.
In this light, we
should realize that what we think is good change, or even
what a country's leaders think is good, is never 100% good.
There is a price to
pay for all change, and much resistance arises because the
price is too high for
some or just cannot be paid without excess hardship, despite
apparent longer-term
value.
Some people in some
countries are used to a logical, scientific sequence of
cause and effect and can thus predict the future, more or
less. This enables
them to confidently invest time, labor, and money in the
future. It gives a
sense of control.
But in many
developing societies, the people have little control and they
know it. Their plans have been thwarted by natural
catastrophe, or by magic,
or by the will of forces distant and far more powerful
(including both gods and
central governments). Given the crawling pace of development
among the
world's rural poor, we cannot blame them for being a little
skeptical about
proposed changes. This is not necessarily blind tradition.
It may be healthy
and justified caution.
And stability
itself has a positive value in all societies as it reinforces behavior
by promising future returns for today's behavior patterns.
Without stability,
people lose the incentive to keep past social values, as
future outcome can
no longer be predicted. The result is an explosive
proliferation of values (witness
America and Europe today) and a disincentive to plan for the
future at
all.
Evolved Versus Imposed Change
Many cultural
changes have been imposed on people, often suddenly, with
remarkable results attesting to the equally remarkable
adaptability and resiliency
of people. Conquerors and rebels have imposed languages,
religions,
food habits, and codes of law on other people since
prehistoric times. They
have often also brought innovations that were eagerly
adopted by the local
people, such as the gun and horse among American Indians,
and baseball and
hamburgers in Japan.
On the other
extreme, some changes took many generations to evolve, perhaps
because they were not very important or were not enhanced by
political
association, or perhaps the price to be paid for the
benefits was high. Where
agricultural innovations were concerned, the risk was often
simply too great.
Some people lived and still live too precariously to
experiment even if the idea
looks promising.
Development
strategists today are caught in the middle. They do not want to
impose, yet cannot wait for evolution to do the job unaided.
So we have
derived an intermediate form of "coaxed" change,
in which we decide before-hand
what change is desired. People do indeed want to better
their lot, but
may be convinced that such efforts are futile and may be too
polite or too
scared to tell us so, or may not even realize why they
resist. Therefore, it is a
good idea to look at the recent history of the subject
community to see how
changes take place in that community.
Study the Past
Every group has its
own ways of change. They usually are those that minimally
disrupt the effective social order, and are also in tune
with the popular
trends as evidenced by past change. Thus, both present and
past -- in this case,
related to the economic and interpersonal structure of food
storage and use -- must
be appreciated to see what might work and what might not. To
this end,
the following questions will be useful:
1. Has the
community made technological or agricultural changes in the
recent past? If so, through what channels were the changes
introduced? Were
there models to copy? Key people whose support and influence
were critical?
Economic or other incentives? Were the changes mainly
imposed, coaxed, or
naturally evolved? Are the changes now an irreversible,
integral part of the
culture, or are they artificially supported by current
leadership and likely to
revert to original status if the support were removed? (The
potential permanence
of a change is as much a measure of success as the change itself.)
2. Have any change
attempts failed in the recent past? What were their
histories and apparent reasons for failure?
With regard to the
"who" questions, the models are particularly important
and simply any model will not do. Certain people will be
followed, others
rejected, still others ignored. The one who acts first may
not be the real leader;
he may be marginal with nothing to lose by trying or he may
be acting under
the influence or command of others. The area of influence is
also important -- a
man who can command respect and honor among civil servants
may not
count for much among the farmers, or an older leader may be
resented by the
young, and vice versa. It pays to learn local history to see
how things got done
before, and for expatriate workers it is certainly an error
to assume one's own
national patterns of power and influence will apply.
It is also
dangerous to believe everything we are told. Observation of attitude
and even tone of voice may be as important as the actual
words said.
Double-checking critical statements is essential; relying on
one or two data
points is as inadequate in social science as it is in
physical science.
How Do You "Learn" a Culture?
The most obvious
answer is time -- implying that people who have spent
years in a group become expert observers of that group. This
is not always
true. Of course, time is necessary, but a competent observer
must also know
how to observe, must be himself/herself relatively free from
familial or political
involvement that might affect observations, and must be
articulate enough
to transmit them to others.
In dealing with
local sources of information, all individuals are not equal.
Some are "balloons" -- innovators who are free to
change and the first to do
so, and some are "anchors" -- social-role
conservatives who provide and
represent stability. Local landowners and similar elites are
often in this class,
while their children may well be balloons as with a
relatively secure future they
can afford to be different. This balloon-anchor continuum is
a convenient way
to characterize local contacts and ultimately to ensure that
one's information
does not all come from one type.
Just as people's
responses depend on their individual characters, they also
often depend on how they view their questioners. Association
with the local
government or a donor agency may be helpful in some cases
and a handicap in
others, and a strong personality may turn a respondent in
many directions. As
an agent of change, an investigator must not imagine himself
free from bias
either. Attitudes toward development and efficiency are
hardly universal. But
he can try to stand back and put his own values aside for a
while, at least while
working, to enable him to learn what makes a host community
tick. This will
be necessary to work within it to achieve the goals he has
accepted for the
project or, when that is impossible, to get out gracefully.
Talking to natives
or experienced foreigners may be the next best thing to
living for years in a place, but these are not the only
alternatives. For some
people, it is easier and better to watch and listen to
others without asking
questions. It is certainly less intrusive. Often, a
conversation about events
seemingly unrelated to grains and farming will reveal ideas
and attitudes which
affect the proposed actions. Economic insecurities, anxiety
about family nutrition,
worry about too much centralized control, and local labor
problems are
examples of things worth listening to. Reading local
newspapers and attending
local public functions where appropriate are useful
techniques; beware,
though, of being inadvertently classified with a political
party or social class
that is linked with the newspaper or the function. In any
case, keeping eyes
open, and perhaps keeping a diary of observations, will pay
off. And if your
function and aim become well known, you will receive much
useful information.
In some groups, the
very existence of a foreigner implies change and is a
threat to some and an object of economic courtship to others.
It is hard for
foreign experts to avoid getting tangled in political games;
if we have money to
spend or control, we are obvious objects of interest and
concern. In some of
the more cosmopolitan places, however, where agricultural
development and
extension work is commonplace, a new face is more easily
accepted. Unfortunately,
the very places where acceptance is easier are also those
with more
complex and intricate social and economic relationships, so
the job is proportionately
more complex.
Culture or Cultures?
It is convenient
but rare to find a homogeneous community with similar
beliefs and behavior. More often there is a continuum of
behavior from traditional
to daring, and sometimes a sharp age distinction, separating
the younger
people who grew up after World War 11 in an atmosphere of
independence and
international communication, from the older generation for
whom tomorrow
was expected to be the same as today or yesterday. Sometimes
the split is
between urban and rural, or factory workers and farm
workers, or on racial or
religious lines, and, of course, there may be more than two
groups involved.
The careful observer, then, will not automatically assume
"one culture" but
look for signs of pluralism that will help him to identify,
classify, and eventually
understand the different attitudes and behaviors of
different people.
Advance Preparation
Much can be learned
before ever setting foot on the location to be studied or
assisted. In almost every area of the world, hundreds of
observers have already
been there and, consequently, there are hundreds of books
and articles telling
about the people and their cultures, ranging in quality from
useless to marvelous.
Therefore, it is inexcusable not to study in advance.
Most field-workers
get basic country information through their own agencies,
the host governments, or their own government post
descriptions. These
are adequate if they are up-to-date and not too strongly
aimed at visiting
businessmen and officials who do not have much contact with
the rural people.
A more subtle problem is the definition of a country or
region through the
eyes of its own U.S./Europe-educated officials and managers.
These people
may ignore basic aspects of the culture because, with good
intentions, they
think they are useless blocks to progress.
Sources
More detailed
cultural information is available and worthwhile. Some sources
are:
1. The American
Anthropological Association, which has a division concerned
with agricultural development, with names and members keyed
to regions
and experience topics. Contact John Bennett, Washington
University,
St. Louis, Mo., or Iwao Ishino, Michigan State University,
East Lansing,
Mich.
2. The anthropology
department of the nearest major university. In checking,
you may find a student just back from a year's fieldwork
there and eager
to tell you what he knows, or a professor who is a
recognized authority. Or the
faculty may know who in other universities would know what
you want, as this
discipline is a complex and well-functioning information
network in itself. (A
word of warning: "anthropology" outside the
English-speaking world sometimes
is narrowly defined as study of physical characteristics and
perhaps of
primitive tribes. In these areas, study of the
culture-linked aspects or agricultural
behavior may be found in departments of sociology,
ethnology, economics,
or in agriculture itself.)
3. The Human
Relations Area Files at Yale University, New Haven, Conn.
which has cultural information on most of the world. You do
not have to go to
New Haven to use it, as many other universities have access.
4. A meeting of
appropriate professionals, such as the American Anthropological
Association which meets each year in November, with numerous
speakers, and its subdivision on agriculture meets at that
time as well. A
related and useful organization is the Society for Applied
Anthropology which
meets in the spring of each year. Details on both groups are
available from
their common headquarters at 1703 New Hampshire Ave. N.W.,
Washington,
DC 20009.
5. The Society for
International Development, an organization of development
professionals -- economists, technical consultants,
officials, and field-workers
in aid organizations, and a few anthropologists. Most of the
members
have international field experience. There are chapters all
over the United
States and Europe as well as in some developing countries.
The New York and
Washington chapters are the largest and hold several
meetings each month; the
Washington group even has a rural development subdivision.
For more information,
contact the North American office, 1346 Connecticut Ave.
N.W.,
Washington, DC 20036, or the world headquarters at Palazzo
Civiletta del
Lavoro, EUR, 00144 Rome, Italy.
Sources in Developing Countries
If you are already
in the field, it may be difficult to reach many of the
sources noted above. If there is time, you can write to them
(offer to pay for
Xerox, book, and airmail costs). But if you have to gather
knowledge yourself,
there are still a few things you can do.
If you have
prepared a grain flow sheet (or pipeline chart) -- a diagram
showing the channels and amounts of grain as they move from
farm to consumers
-- there will be certain key locations that control
movement. Going to
these places and watching who does what can be very useful,
if it can be done
without obvious intrusion. For example, watching who buys
grain at a central
market will yield information on purchase quantities, which
in turn tells us
about home storage. If no money changes hands, there may be
a credit situation
which controls purchase.
Watching harvesting
and transportation of grains is also useful, and often
possible in the role of technical expert. But it will help
to learn who the
workers are, who owns the vehicles or animals, what happens
to spilled grain,
and other such factors. The object is to understand the
economic relations
among the people and ultimately to understand the potential
effects of any
proposed changes.
Officials and local
counterparts in a grain saving program are certainly
available sources of information, but must be heard with
caution. Some are
farmers themselves, or have worked in the grain pipeline for
years, but others
may not really know how the majority of farmers and
consumers behave; or
they may not want to talk in detail about behavior that they
consider old-fashioned
or even embarrassing. We do not wish to imply that all or
even most
local officials are devious or misinformed; we warn only
against uncritical
acceptance of their descriptions without other indications
or feelings that they
are sensitive to and reporting what is going on around them.
There are many
information sources in developing countries beyond the
officials. Many countries have a strong awareness of their
own cultures and
have much published research. Appropriate university
departments and libraries
as well as government officials can be helpful.
It is often useful
to look at people through the eyes of observant and
articulate members of one's own culture. They can anticipate
problems and
reactions, and their advice should be sought. These might
include anthropologists
in the field, workers for volunteer organizations, or
missionaries.
Key People
It is important to
identify key people who can influence acceptance of
changes, but it is also important to distinguish between
apparent influence and
real influence. Some people in important positions may
really be servants of
the position and cannot promote certain changes even if they
wanted to. (This
also is true in Europe and America.) Thus, personal and
logical argument will
be useless and may even embarrass the official who knows you
are right, but is
reluctant to explain why he must disagree.
Some positions of
authority are temporary and others permanent, so it is
important to know the system by which people come in and out
of power. This
can be quite complex -- in some areas, for example, people
move up both
religious and political ladders, switching back and forth in
a traditional pattern.
Many of these
traditional systems are breaking down in the face of modern
technology, communications, and other influences. Sometimes
a foreign fieldworker
finds himself/herself a symbol of change, with corresponding
personal
alignments and antagonisms, even before he ever says or does
anything. This is
a hard position to be in and some projects are doomed to
failure or dormancy
(a more polite and often more profitable alternative) no
matter what the
technical or economic merits of the proposed actions. Even
if nothing can be
done, it certainly is good to be aware of such situations
and perhaps ask other
colleagues about them on arrival, as part of initial
briefing.
The Culture of Development
The development
business has its culture, too, involving both foreign agents
of change and local managers. Everyone has his/her own
interests, and it is
reasonable to expect people to act in their own interests.
It is often easy to
blame inaction on a few individuals, or on one class of
people or another, but development is not that simple. In
reality, people of all
classes will resist risk, even as they desire growth and
improvement of their lot,
if they sense the chance that their status might change for
the worse.
From this need to
minimize risk emerge the relations among government
people, local businessmen and farmers, technical experts,
and representatives
of foreign and domestic money sources. These relations
build, of course, on
existing socioeconomic patterns, and are themselves dynamic,
changing as
needed to maintain development money input with minimal
disruption.
In each location,
this network is unique, and there can be no fixed guide to
inform the newcomer, but a discerning fieldworker can easily
see what is going
on. Observe the social relations of the participants -- who
is invited by whom,
who accepts and who can reject, who pays at lunches or
dinners, what reciprocity
is expected and what is given, who visits and who stays put,
and who
waits for whom at appointments. Watch language cues, too,
such as the use of
the familiar verb forms, first names or nicknames, and
dialect or slang in
direct conversation.
In any such
network, some people are more free to act than others, and this
degree of freedom should be noted for the people one must
work with. In
general, technical experts have more freedom (but less
power) than political
officials, young or old people more than middle-aged family
heads, people
from another area more than others with local family and
business connections.
These are guides, of course, and not rules, and there will
be many
exceptions.
In some places,
there are long-standing patron-client relations which keep
subsistence farmers in permanent debt and service, or else
maintain them as
low-paid farm workers. To the patrons, anything that may
increase the economic
power of their clients -- even a grain use survey -- may be
seen as a
threat to the current status, often already endangered by
the communications
revolution. Some patrons are very troubled by this; others
do not care. They
will all usually cooperate with government and
change-agents, and many really
do want their people to eat better if that were possible
without disrupting the
entire structure that they feel responsible for maintaining.
In fact, where
leaders are sufficiently secure as to be benevolent in deed
as well as word, there
is the greatest chance for successful change, as the
leadership can then get
things done.
A special problem
is the self-perpetuating project which employs many
people including international civil servants, is government-sanctioned
and
supported, and has no place to go if it succeeds. Thus,
projects are kept in a
state of incipient success to assure the flow of money and
support, as well as
the absence of disruptive change. Seldom is this a conscious
conspiracy; more
often it arises from the very nature of the situation.
Much of this is
common knowledge among careful analysts of the development
business. We include it here, though, because it may be
useful for fieldworkers
new to development, and also because the interface between
fieldworkers
and local officials is an area worth more attention and
understanding,
even among the experienced.
What Are We Looking For?
To understand local
behavior with respect to food production and consumption,
observe these areas:
1. What is the
money flow in the food system? What credit system is used?
Are farmers truly independent, or are they dependent through
debt, or laborers
on land owned by others? Is there a social reciprocity
system that
reinforces a dependence situation? And on whom are they
dependent? Can
they afford the extra inputs to invest in new seeds,
techniques, or equipment
that would ultimately recover more grain?
2. What is the
belief system of the people regarding food supply? Do they
see it as a purely commercial transaction or are
supernatural forces involved?
3. Do they
understand the connection of more food with better nutrition
and health, ie, do they see themselves as having some
control over their health?
4. What are the
social connections to securing and consuming food? Is
much food given away, or eaten in larger gatherings, and how
would that
affect the costs, risks, and benefits of saving more food?
Can social obligations
be used by hungry people to buy food, and thus give more
incentive to
grain recovery? Food has many social and personal functions
in addition to
nutrition and these should be well understood so that
suggested changes permit
continuity of these functions.
5. What do the
people do with extra money? If saved grain is sold for cash,
then the saving may be less critical. If extra money opens
problems of taxes or
extra grain opens increased obligations within a social
reciprocity system, a
saving may be disadvantageous to the grain owner.
Other questions and
attitudes are explored in Part B of this chapter.
Social and Economic Ecology
Even with current
ecological awareness, it may still be necessary to recognize
the interrelation that exists. The facts of ecology are well
known for animals
and plants and the physical environment, but are
surprisingly neglected in the
social and economic spheres. There are social and economic
ecologies, too,
and the effects of a survey or proposed change are felt in
many ways, and
among many people other than those directly involved.
Social ecology may
be linked to economics, if economics is broadly defined
to include all actions that maximize security and the
ability to cope with one's
surroundings. People relate to one another, form and break
alliances, cooperate
and compete. Some hope only to stay alive, to break even
with life, while
others -- more and more as the potential for change becomes
known -- try to
improve their levels of wealth, power, and prestige. The
individual entrepreneur,
in fact, may well be a role learned from colonials, who
brought with
them the idea that work and intelligence (cleverness) can
raise a person from
low to high in a lifetime -- a phenomenon previously seen
only via miracles
and natural events, not under one's own control.
To understand
social ecology, it is useful to describe levels of wealth and
power within a community and to learn the paths by which
people can get
there. Some positions will be very stable, others
precarious, and the degree of
stability should be noted as well. Then, the effects of a study
or a proposed
change can be cast against this background: What will happen
to X if we do
this? Or how does X see this change as affecting his
community and his
position? Remember that he may see the exercise from a
different vantage
point than that of the investigator.
It also helps to
learn how people define security, what their real aims are,
and whether they understand that they can better their lot
without incurring
enemies who now have less. Competition may be based on the
philosophy that
if I get more, someone else will get less. Riches breed
anxiety in such a system,
and it serves as a device to inhibit excessive
differentials.
Local social
customs define associations. Such customs act as social glue to
serve as markers of who belongs where, or who wants to move
where, or who
can trust whom, or what set of rules a person is following.
Customs can also
define social boundaries to identify different groups within
a community.
Economic ecology
can also be viewed in numbers. This is the grain pipeline,
but determined from farmer to consumer, with attention paid
to debts incurred
and values received along the line, not only in money but
also in
services and promises of services. Prices may be less to one
person than another;
that is not always unfair, as it may be the seller's way of
repaying a debt
or earning a future favor. Credit is all-important in
understanding the pipeline
as the farmer's actions may well be linked to his credit
sources and their limits.
Another
socioeconomic factor is visible difference. A man may not want to
do better than the others, at least visibly, if envy is to
be avoided. In some
societies, invisible success is tolerated but in others it
is betrayal of the common
good, and only a cooperative or communal effort will work,
as no one
would be obviously climbing over the others. A knowledge of
attitudes toward
envy and success should be useful in planning the scope of
proposed changes.
Outside development
processes have reached almost everywhere in the world
and the remembered effects of local involvement have not
been universally
favorable or unfavorable. Onset of a new program, either
survey or direct
assistance, is an intervention into today and brings with it
future concerns. The
investigator will get more done more accurately when he
knows the actions and
interactions of the people he is working with, when he
recognizes the similarities
and differences among them, and when he knows where they
have been
and which way they are going.
CHAPTER III
B. Anthropological Signposts
C. C. Reining
The researcher or
project manager needs a clear understanding of the cultural
and social setting in order to meaningfully assess grain losses.
At its most
basic level this means knowing who does what to the grain,
how, when, and
why. It is easy to see that measurements of tangibles should
never lose sight of
the people who produce, process, and consume those
tangibles. However,
there is a need for understanding the human social and
cultural factors which
go far beyond that immediate level and which will
dramatically influence the
degree of success of a loss assessment effort.
Because so often
the project managers in grain loss programs are outsiders
to the area being studied, there may be a high incidence of
cross-cultural
communication gaps which can impair the progress and
accuracy of loss surveys.
However, with careful effort, much can be done to overcome
such
cultural perception difficulties. As cross-cultural
communication gaps are
likely to occur throughout the span of the project, the
effort and time spent in
developing a cultural understanding will more than repay
itself in later-saved
time and expense.
Good social and
cross-cultural communication skills will be required in
selecting, training, and supervising field-workers; in
determining what questions
need to and can be asked in field surveys, and in
ascertaining how to
phrase them for ease of comprehension; in identifying which
individuals are
the best informants for specific questions; and in allowing
for and putting into
proper perspective potential biases including those of the
local farmers, grain
handlers, extension workers, field investigators, and the
project manager himself.
Particular objectivity will be needed when local ideas and
values differ
from those of the investigator.
The continual need
to balance and blend technically ideal procedures and
approaches with social, cultural, and political realities is
a process which will
influence conscious and unconscious cultural values and
perceptions. More
than any other discipline or subject area involved in grain
loss assessment and
reduction, the sociocultural one lends itself least well to
a step-by-step or
procedural treatment in this manual. The cultural
observation guides provided
at the conclusion of this chapter should not mislead the
reader. No such guide
could be comprehensive. The guides presented here are
provided as a tool -- a
thought-provoking means of helping project managers and
their personnel to
formulate their own process for understanding the salient
aspects of the local
culture and to develop the greatest possible depth of
understanding.
In many
circumstances, the limited time available for survey planning will
make invaluable the short-term services of expert
anthropological or sociological
assistance. It is assumed that every project would benefit
from the assistance
of such expert staff members, although the reality of
limited project
funds and personnel will often mean that such professional
assistance will be
brief. Where such assistance is not available, a suggested
analytical tool for
identifying the human element in the grain pipeline is in
following through
each relevant process or stage in the pipeline to trace what
might be called the
"grain handlers' pipeline." This can be usefully
broken down as to who (age,
sex, and social position) does what, when, where, and why.
As the situation is
studied in more depth, critical and subtle elements will become
clear, including
who has the decision-making authority and which individuals
might be most
and least amenable to changes in their present grain
handling and storage
procedures.
In spite of recent
widespread recognition that women's roles in developing
countries have been largely overlooked, it is useful to
emphasize this issue
again here. In subsistence farming cultures, women often
perform many of the
tasks in grain handling and storage. Too often researchers
and project planners
have failed to see and describe the role played by women. As
a result, vital
parts of the intricately interwoven cultural framework have
remained unobserved
and unaccounted for, only to be unpredictably changed,
alienated, or
harmed when programs are initiated to improve the situation.
An outsider,
defined as any person who does not live in the community,
finds it difficult to find out who does what, why, how, and
when. When the
investigator is a man and the major tasks are performed by
women, the problems
for an unknowing man can be insurmountable. It is not
satisfactory to
ask the men of the village what the women do, how they do
it, when they do it,
and why. It is not uncommon to have the men say that a
certain task is done a
certain way, and to find out later that their perceptions
are off, when the task
is performed by women. In addition to men's lack of
awareness about particular
details of women's work, one must add the cultural
constraints imposed on
outsiders, particularly those who are men, in communicating
directly with the
women. This takes time and carefully selected and
well-prepared investigators.
Female survey
workers may be necessary in some cultures to gain access to
women. However, it is overly simplistic to assume that a
female worker will
necessarily be more perceptive or reliable than a male in
specific women-oriented
investigational work. If there is a severe access problem in
outsider
men even being able to talk to women, it may be essential to
have female
investigators, although in selecting field investigators,
the more perceptive,
imaginative, reliable worker is always preferable, whether
male or female.
When project
managers and their field-workers do not speak the same language
and especially when there is a marked difference in their
cultural or
social backgrounds, the inevitable communication problems
caused by translation
and cultural differences need to be recognized and dealt
with. Fieldworkers'
understanding of instructions and the reliability of their
observations
must be carefully verified. This verification needs to be
done in a number of
ways:
1. Regular personal
observation in the field by project managers to check
on workers' methods and reliability.
2. Rephrase
questions and instructions to assure full understanding and
accurate communication between director and workers.
3. Check several
sources of information for cross-checking of observations
and assumptions.
4. Get to know
field-workers' ways of thinking, biases, weaknesses, etc.
5. Keep to a
minimum the number of intermediaries between project director
and the village situation, to minimize communication
problems and distortion
of information.
In summary, it
would be hard to overestimate the importance of social and
cultural awareness and understanding on the part of loss
assessment project
managers and their personnel. Personal flexibility and
willingness to learn will
be great assets in order to gain this understanding.
Countless decisions will be
made which draw on this cultural understanding in balancing
and adapting the
project's technical needs and scientific ideals with social
and cultural realities.
The following
cultural observation guides are intended to help bring to light
salient cultural factors, although no amount of study and
instruction will
replace the learning opportunity of direct, personal
experience in living and
working in a cross-cultural setting.
1. Social Organization
a.
Describe the levels of wealth, power, and
prestige in the community.
(Comment:
Relations between social classes can have a profound effect
on handling
basic items such as grains.
b.
Who and what comprises the basic production
unit?
c.
Who and what comprises the basic consumption
unit?
d.
If they are not the same, why is there a
difference?
e.
How do these units form into larger units?
f.
What are the local names of these units and
do they have meanings?
g.
Which persons or positions are the leaders
within each level and how do
they
communicate?
h.
Who does the harvesting, transporting,
drying and other preparation,
and storing?
i.
Who removes grain for sale or consumption?
j.
Who has control of the grain before and
after storage?
k.
What is the relation between producers or
producing units and purchasers
of the grain?
l.
Are there any legal restrictions on the sale
or transport of grain?
m.
What are the differences in storage of
grains intended for sale as compared
to those
intended for home consumption and for seed?
n.
If there are crops intended entirely for
sale, what are the differences in
responsibilities and in handling?
o.
What types of occupational specialists are
involved in the grain production
and storage?
p.
Who obtains the materials for storage facilities?
q.
Who builds the storage facilities?
2. Domestic Organization
a.
How large is the usual household and what
kinds of relatives does it
contain?
b.
Does it contain any unrelated persons, such
as permanent servants or
temporary
laborers?
c.
Is the household the basic unit or a subunit
of production and/or
consumption?
d.
How does the household link with the rest of
the community?
e.
What kinds of work are usually done by
women?
f.
What kinds of activities are avoided by, or
restricted for, women?
g.
What kinds of work are usually done by men?
h.
What kinds of activities are avoided by, or
restricted for, men?
i.
Who makes the decisions about the various
stages of production, storage,
processing, and sale or consumption of
grains in the household?
j.
Can exceptions be made to the rules about
who makes the decisions and
under what
circumstances?
k.
Who does the training in storage techniques?
l.
What happens to stored grain in the event of
death(s)?
m.
How is transfer of authority made on the
death of heads of consuming
and/or
producing units?
3. Cultural Factors
a.
Are losses permitted because of lack of
awareness?
b.
Are losses felt to be inevitable?
c.
Are the people concerned about their grain
losses?
d.
What do they think should be done and why
haven't they done it?
e.
Which grains do the people believe store the
best or longest?
f.
Which grains do they believe are hard to store?
g.
How do they explain the differences in
storage characteristics?
h.
How do they accommodate these differences?
Do they have different
methods? Do
they consume some grains more quickly than others?
i.
How does the availability of other crops,
such as root crops, influence
the storage of
grains?
j.
What are the indigenous materials used to
help prevent damage to
stored grain?
k.
What do the people see as the tangible
causes of damage to stored
grain?
l.
What are felt to be the intangible or
supernatural forces controlling
losses?
m.
How do they attempt to influence both the
tangible and intangible
factors?
(Comment:
There are serious problems of categorization here, both in
Western and indigenous terms. Often the
distinction between "magical"
and
"scientific" becomes blurred, as when a local remedy that is
felt to have
mostly spiritual qualities may, in fact, have demonstrable
effects on
stored grain, while other devices believed to have more direct
effects do not
have any discernible ones. Most preventative practices are
a blend of
empiricism and mysticism.)
n.
What will be eaten that might have been
damaged?
o.
What are the local guidelines for what
should and should not be eaten?
p.
What is done with spoiled grain? For
example, is it fed to chickens or
other domestic
animals?
4. Transition and Change
a.
Is a need for change or improvement felt by
the local people?
b.
How do they want to change the situation?
c.
Is their knowledge of desired change sound
enough to understand the
ramifications?
d.
Can they afford the new materials?
e.
Will they be able to sustain the new
equipment and techniques?
f.
How do innovations get into the community?
Are there key positions or
individuals
for introducing innovations?
g.
What improved procedures have been
introduced? By whom? Successfully?
h.
Have storage systems of various indigenous
systems in the same kind of
environment
been compared?
(Comment: Most
communities have had a long time to experiment with
adapting to
their particular setting. It is usually difficult to improve
upon the local
arrangements given the resources available. If introduction
of new
techniques is deemed necessary, it may be more effective to
consider
transfer from a similar indigenous setting rather than from
Western
culture.)
5. Individual Factors
a.
The local person
i.
How typical is the person supplying the
information?
(Comment:
Often the typical or normal person is too busy to want
to spend
time talking with outsiders. The persons most available too
often are
marginal to the community.)
ii.
What does the informant see himself or
herself getting from the
interview?
(Comment:
It is very human to constantly assess any situation to
maximize
the returns. Beware of creating false hopes.)
iii. What are
the biases and interests of the interviewee?
iv.
Is the interviewee skewing the information
to fit the situation as
perceived?
(Comment:
There is often a tendency to tell the interviewer what the
interviewee thinks he wants to hear. Misunderstanding is altogether
too
frequent. Consider the difference in response if the interviewee
thinks
there may be a tax imposed on the stored grain, as compared
to the impression that compensation may be
paid for lost grain.
v.
Are the interviewees saying what should be
rather than what is
actually
the case?
(Comment:
It is important to distinguish between the real and the
ideal. Observe what they do as well as
recording what
they
say.)
b.
The interviewer
i.
What are the biases of the interviewer?
ii.
What are the biases and interests of
interpreters, if used?
iii. Are
problems perceived from the viewpoint of the interviewer or
from that
of the interviewee?
IV. REPRESENTATIVE SAMPLING,
INTERPRETATION OF RESULTS,
ACCURACY, AND RELIABILITY
B. A.
Drew, with T. A. Granovsky and C. Lindblad
A. Introduction
Basic Assumptions
Every scientific
measurement is based on some kind of assumption regarding
the real world about which the measurement is supposed to
supply some
information. Conducting a survey to measure average grain
losses is such a
measurement and it is based on the following assumptions:
1. Cultural and
economic conditions, level of knowledge of farmers, farming
practices, varieties
grown, and harvesting and storing practices are
essentially
uniform throughout the area to be surveyed. If this assumption
is to be
verified by local observation, one will have to understand the
cultural milieu.
If it is nonuniform in ways that can possibly affect what
is to be
studied, sampling becomes more complicated and the advice of
experts should
be sought.
2. All grain to be
considered is stored in the same manner in units of
approximately
the same size. That is, the largest unit is no larger than
five times the
smallest. If the size variation is greater, then they should be
sampled and
analyzed separately as two or more populations.
3. Size of farms is
uniform to within a factor of 5. That is, the largest farm
is no larger
than five times the smallest farm (in area producing crops for
storage). Again,
if the size variation is greater, then they should be
sampled and
analyzed separately as two or more populations.
These assumptions limit
the survey described to a single stratum. This is all
that can be done using the simple sampling plans outlined
here. More complicated
plans should involve the help of experts in sampling as well
as in grain
loss assessment.
Uses of Survey Data
In designing a
sample plan it is essential to know the purpose or purposes for
which the results are to be used. For example, one might
wish to determine the
calorie losses which are incurred due to parasites, in order
to determine
whether to supplement the farmers' diet, or one might wish
to determine the
extent of losses in grain held in storage in order to decide
whether to treat
it with pesticide. In one case, medical-nutrition concepts
are involved; in the
other, grain losses.
The ultimate use of
the results will influence not only the precision and
accuracy which are required, but also what is measured and
what additional
data must be collected. Thus, the measurements which are
made and the
ultimate use of the results, including the level of loss that
is acceptable, must
be decided before the survey is designed.
Editors' note: Given the present refinement of loss
assessment methods, it is
generally accepted that
[+ or -] 5% accuracy(2) is the best practical limit which can be
expected (with rational allocation of resources and time
against the potential
value of the reduced grain losses). At the same time, where
losses are expected
to be 15% or less, a [+ or -] 10% accuracy level could all
but obscure any meaningful
information. Where such is expected to be the case, rapid
expert assessment
of critical loss points may be economically justified while
an extensive in-depth
loss survey is not. For certain economic evaluations, no
less than [+ or -] 5% accuracy
can be tolerated for analysis to be meaningful.
Determining Area to be Surveyed
In making a survey
over a large area such as a whole country or region, the
sample population should be divided into parts to reduce the
problem to
manageable proportions or to obtain a uniform population.
This is called
multi-stage (stratified) sampling.
In such a situation
there are two valid alternatives for sampling a
population. These are: To include in the sample of a
population all of its
subdivisions, or to include a random sample of subdivisions
of the population.
Section B presents
these sampling methods in detail. The rule for this choice
is to take all the subdivisions when there are only a few,
say 10 or less. If there
are more than 10 subdivisions, then as many as are
consistent with available
resources should be chosen using random numbers. At such a
point knowledge
about the differences between particular subdivisions may
make a valuable
contribution to deciding whether to choose all or a sample
of subdivisions.
Advice from knowledgable people in this area should be
sought.
Types of
subdivision are extremely dependent upon the local situation but a
country (nation) may be divided on political boundaries such
as states or into
units based on geographic considerations such as lowlands,
uplands, river
valleys, and arid regions. The last division would be
preferred when knowledge
or advice is available about the impact of such conditions
upon storage losses.
In such a case, resources might be allocated to the various
regions in proportion
to the likelihood of postharvest losses.
The next
subdivision might be on the basis of villages or small administrative
or political units. Here the units of the subdivision should
be listed and
random numbers used to choose as many units as can be
measured with
available resources. Remember that excessive variations in
size of storage unit
may require separate analysis of samples as two or more
populations.
_________________________
(2) In this manual
accuracy is expressed in absolute terms. Thus 20 [+ or -]
5% means from 15 to 25%.
If there are
different types of stores within the unit (administrative or political
unit), then each type of store should be considered as a
unit in the next
subdivision. It is the last possible subdivision to which
this manual refers.
Accuracy
Accuracy of an
assessment of grain losses depends on obtaining a truly
representative sample and making an accurate measurement on
the sample. No
matter how accurately one measures a sample in the
laboratory, the result will
be of little value if the sample is not representative. It
is equally pertinent that
no matter how representative the sample may be, the final
result will reflect all
the shortcomings of the laboratory measurement.
CHAPTER IV
B. Probability Samples
Bias
The rest of this
section will be devoted to methods to ensure a representative
sample and to avoid all sources of systematic error often
called bias. If we
always sample the best-looking stack in the field, or the
one nearest the house,
or the one the farmer chooses; if we always take samples
right by the entrance
into a granary, or where the grain looks good, then we may
be putting a bias
into the sample. Even if we try to choose in a way to avoid
bias we may
over-correct. If we try to avoid choosing units that are
easy to reach, we may
unconsciously choose units that are hard to reach. The only
way to avoid bias
is to take the choice out of our hands, to give it to a
table of random numbers.
The method is called "probability sampling," and
its result is a "probability
sample."
A Random Sample or a Representative Sample?
When establishing a
sampling pattern, confusion exists between the terms
"representative sample" and "random
sample." Representative sample usually
refers to a "stratified random sample," in which
strata are defined and
represented in the sample in proportion to their size in the
sampled material.
If 1) the strata
have something to do with the property to be measured and if
2) a random sample is taken within each stratum, the
variance of the estimate
may be lower than that of a completely random sample. Both
conditions are
necessary, however. The following examples will clarify what
is meant by such
pglx490.gif (486x486)
terms as randomization, stratification, random sample, and
stratified random
sample.
The two sampling
patterns given below are not recommended for use in a
loss assessment survey, but are presented for clarity.
Systematic Sample
A sample is
taken every so many units, eg, every 10th bag as it is
moved from
location to location.
Some problems
to be encountered are assumed damage or loss is
uniformly
"normally" distributed, which is rarely true for insect
populations, the
sampling pattern may conform to some inherent
distribution
pattern of the damage, and no random component is
included and
therefore statistical procedures cannot be used.
Centric Systematic Pattern
A sample is
taken from the exact center of each unit. If such
samples are
analyzed using parametric statistics and compared to
samples obtained
by the random pattern, results may truly reflect
what is present.
All problems
present with systematic samples are also present
with centric
systematic pattern.
The sampling
patterns illustrate the advantages of having some
knowledge about
the material to be sampled, and show one way to
use such
knowledge. But when there is no knowledge from which
strata may be
deduced, complete randomization is the only way to
obtain a
representative sample. This applies to each cell or stratum
in any scheme of
stratification. A random sample should be taken
within each cell
or stratum. Otherwise, the advantages of stratification
may be lost.
Properties of Probability Samples
This section
presumes that a probability sampling plan will be used. The
reasons for this are:
1. With this type of sample one may calculate confidence
limits within
which the actual
value of the result is reasonably certain to lie.
2. Generally one may determine in advance how many samples
must be
taken.
3. This type of sample is guaranteed to be representative.
The actual value is
the value which would be obtained if the loss in every
unit in the area were to be determined.
Observational Units
The observational
unit is the container, location, or process from which a
sample will be removed to determine the loss evident in the
sample. This is the
smallest division or unit in which grain is held. It might
be stacks in a field,
small silos or granaries on a farm, or woven baskets. It
would be a single
basket rather than all of a farmer's storage baskets; it
would be individual bags
rather than the whole warehouse. Accuracy of the entire
survey will depend on
the accuracy with which the loss is determined on each
observational unit.
To facilitate
sampling, the observational unit should be as small as possible.
This makes it easier to get a representative sample since it
will be possible to
mix all the grain thoroughly and reduce the sample taken by
quartering or
using a sample divider. This may be feasible where the grain
is in baskets or in
stacks in the field. In silos or granaries it may not be
possible and, unless the
sampling is done with skill, the sample may contain a
systematic error which
cannot be removed by any later calculation or analysis.
When any container
is sampled as a unit, the assumption is that the defect,
contamination, or other characteristic to be determined is
uniformly or at least
randomly distributed within the unit. As a practical matter
such is usually not
the case.
Insects/mites,
moldy kernels, rodent depredation, and insect-eaten kernels
are more usually in location-oriented pockets (see Appendix
A).
With time and money
constraints and often with cultural-traditional limits
also imposed, the best that can be done is to design the
mechanical sampling so
that the sampled grain will be as representative as
practical of both the undamaged
material and the layered or pocketed defects.
In any study the
investigator needs to report what was done and why so that
the significance of the data can be understood by those who
will use it.
Where grain is stored
in storage units of variable sizes or types, a person
with competence in statistics should be called upon to help
design the sampling
plan.
Number of Samples
To decide roughly
how many samples must be taken, two items of information
are needed: the desired confidence limits, ie, the estimate
of the overall
average loss within 1, 2, 5, or 10%, and the range of losses
to be expected. The
range is the difference (in percent) between the highest
expected result and the
lowest expected result.
With these two
items, one can find from Table 11 how many observational
units will be sampled and measured to get a representative
sample. If the
number to be sampled is too costly for available resources,
the desired confidence
limits will have to be lowered. If the range is
underestimated, the number
of samples taken will be insufficient. Therefore, it is
generally recommended
to make liberal estimations of the range expected unless the
population is
well known.
For example, as
shown in Table 11, if the lowest result that is expected is
25% loss and the highest expected result is 85% loss, then
the range is 85 - 25
= 60, and if the desired precision is [+ or -] 5% the sample
must include at least 81
units. If a sample of 81 units gives a result of 40% loss,
the results should be
interpreted as 35-45% loss (40 [+ or -] 5%).
The above procedure
is calculated on American Society of Testing Methods
(ASTM) Recommended Practice E122-58 and is based on
statistical theory.
Other procedures for determining sample numbers which are
based on intuition
such as arbitrary numbers and square root samples do not
allow specifications
of desired precision in advance.
Table II is
mathematically calculated to assure representative sampling regardless
of total population size. It is based on the range of
results expected
and desired confidence limits.
If the actual
number of units is less than the number given in the table, then
all of the units should be sampled.
Preliminary Surveys
A preliminary rapid
fact-finding survey, mentioned in several places in this
manual, is of value in gathering information to assess the
homogeneity-nonhomogeneity
of the system.
Answers to the
following kinds of questions should be obtained by the
preliminary survey:
* Are there large differences
in culture? Income level? Farming, harvesting,
drying, storage
practices? Crop and variety grown?
* In what size unit
is grain stored? What is the largest unit found? The
smallest? How
many of each class?
TABLE II
Required Number of Samples
Range of Results Expected
100 80
60
50 40
30
20 10
5
(%) (%)
(%)
(%) (%)
(%)
(%) (%)
(%)
[+ or
-]1% 5,625
3,600 2,025
900
225
Desired [+ or
-]2% 1,406
900 507
225
57
Precision [+ or -]5%
225 144
81
36 9
...
[+ or
-]10% 57
36 21
9
3 ...
...
Note: This table was derived by standard calculations based
on a conservative estimate of
population-defined standard deviation = range/4.
Sample numbers
in this table were calculated using eq. 1 in Recommended practice for
choice of
sample size to estimate the average quality of a lot or process, ASTM E122-58,
American
Society for Testing Materials (1958).
* How big is the
largest farm (village)? The smallest? How much land does
each actually
cultivate with crops that will be stored? Can you make a list
of all the farms?
Can you locate them on a map?
* How many storage
units of each size class are there on the biggest farm?
On the smallest?
Can you estimate the number on an average farm?
It may be of value
to collect other data in a preliminary survey to facilitate
subdivisions into strata or for other purposes. As the
preliminary survey uncovers
separate strata, it uncovers material that needs to be
sampled separately
if adequate overall coverage is to be obtained. It is also
necessary to look at the
total situation (eg, the subsistence or the marketing
systems) and then determine
what elements are to be measured. In other words, what
components do
matter? What are the expected ranges of the variables? What
should be ignored
as trivial?
One needs to know
all of the possible ways the population stratifies: geographically,
climatologically, politically, and culturally (size of
installation,
wealth, mechanization, kinds of storage).
The pipeline
concept (see Chapter II) is a means of sorting out, for example,
situations, locations, economic and political factors. It is
a means of focusing
on a situation to reduce the study to a homogeneous stratum.
Designing the Probability Sample
To design a
probability sample, it is necessary to use a method that ensures
that every observational unit in the area to be surveyed has
a known probability
to be included. When it is known in advance how many units
there are and
where each one is, then a list is made and the units are
each given a number in
series from one on up to the total number. Then a table of
random numbers
(see Appendix B) is used and those locations whose numbers
come up are
sampled and measured until the required number have been
done.
If the number of
units and their locations are not known, an estimate of the
total number of units from the preliminary survey can be
used to calculate
what proportion of all units to sample. For example, if one
wants to sample
200 units and he estimates that the area to be sampled may
contain 2,000 units,
then he takes one unit chosen at random for every ten units
found. A method
for doing this is to make up lists of random numbers for
farms containing
various numbers of units and put them in envelopes for the
sampler. When he
comes to a farm that has 51 units, he first numbers each of
the 51 units. Then
he opens an envelope labeled
45 to 51" which contains five random numbers
(between 1 and 51 inclusive). He then takes samples from the
five units given.
In sampling farms
if the number and location of farms are known, each
farm is given a number and the farms to be visited are
chosen with the table of
random numbers.
Taking samples on a
farm which has more than one stack or granary should
also be done at random, taking into account any known
pattern of use or any
other known nonhomogeneity. It is best to decide in advance
how many units
will be sampled on a farm and to have sets of random numbers
of the correct
size in envelopes. Then the sampler can number the units
(baskets, stacks)
found, and choose an envelope labeled for that many units
that contains the
required random numbers (see Appendix B).
Note: In sampling it is always a good precaution to identify
extra sampling
points and to take samples from these sites to replace the
inevitable accidents,
dropouts, or loss of sampling sites.
CHAPTER IV
C. Detailed Instructions
Choosing Farms or Villages
All the farms
(villages) in the area to be surveyed should be listed and the
number of samples that are required should be determined
(see Table II).
If there are more
farms than samples required, and if the farms are all the
same size (within a factor of 5), then
* Give each farm a
number from 1 to as high as necessary.
* Use a table of
random numbers to choose the farms to be sampled. The
farms chosen may
be visited in any order that is convenient.
* Obtain samples
from one observational unit (stack, basket, crib, etc.) on
each farm. Choose
the unit with random numbers after seeing how many
units there are
on the farm.
If more samples are
required than there are farms, and if the farms are all
the same size (within a factor of 5), then
* Determine (or
estimate) how many observational units there are in the
area to be
surveyed. The total number of units is called N and will be
greater than the
number of farms, if several observational units are
present on each
farm.
* Determine the
number of samples necessary from Table 11. This is n. The
fraction n/N is
the sampling proportion.
* On each farm (or
in each village) count the number of observational
units and
multiply by the sampling proportion. The result, rounded to
the next highest
whole number, is the number of units to be sampled.
Sampling on Farm or in Villages
Labeling of
Samples. All samples must be labeled and retain their identity as
to date collected, exact location of source, how sample was
obtained, grain
type, variety (if known), time in storage, and type of
storage.
Procedures for
Sampling
Standing Grain in
the Field
* Choose an area
(in square meters in broadcast crops or linear area in row
crops) that will
yield 1 to 1.5 kg of shelled grain.
* Divide the field
into units of the chosen area.
* Give each unit a
number starting with 1 and going as high as necessary.
* Choose as many
random numbers from the table furnished as there are
samples to be
taken.
* Harvest and shell
the grain in the unit areas whose numbers were chosen.
* Package the grain
from each unit for transmission to the laboratory.
In the Field in
Stacks (If Each Stack Contains More Than 2 kg of Shelled
Grain)
* Give each stack a
number starting with 1 and going as high as necessary.
* Choose as many
random numbers from the table furnished as there are
samples to be
taken.
* Shell each stack
whose number was chosen.
* Reduce the grain
by coning and quartering or by using a sample divider
(see Appendix A)
to a sample of 1.5 kg.
* Package the
sample for transmission to the laboratory.
Note: If each stack contains less than 2 kg of shelled
grain, choose twice as
many random numbers as there are samples to be taken.
Combine the grain
from two stacks into a single sample for transmission to the
laboratory.
When the Shelled
Grain is Stored in Baskets
* Give each basket
a number starting with 1 and going as high as necessary.
* Choose as many
random numbers as there are samples to be taken.
* Reduce by coning
and quartering (or use a sample divider) each basket
whose number is
drawn to a sample of 1 to 1.5 kg.
* Package the
sample from each basket for transmission to the laboratory.
When the Unshelled
Grain is Stored in Small Units (Such as Baskets and
Bags). If the grain is stored in small units on the cob,
head, or panicle, shell the
contents of the whole unit before coning and quartering to
yield a 1- to 1.5-kg
sample.
When the Unshelled
Grain is Stored in Large Cribs, Silos, or Granaries. To
sample grain stored unshelled in cribs, silos, or granaries,
unload and shell the
entire lot. Then cone and quarter (or use a sample divider)
to obtain a sample
of 1 to 1.5 kg. Or unload the grain equally into baskets and
then use the
method for unshelled small units (choosing baskets by
stratified random sample).
Note: In storage, ears of cob maize or panicles of
sorghum/millet and maize
can be labeled randomly as the crib is filled. The farmer
can then be asked to
set these ears aside as he encounters them during emptying.
Determining an
adequate sample of ears or heads from a crib can be a
problem, however. This
procedure should be used only after careful study of its
applicability to the
local situation.
Large Bulk Storage
Units, Shelled. Obtaining a representative sample from
a large bulk container is difficult. Ideally the grain would
be transferred into
another container in such a way that samples could be
obtained from the grain
as it falls into the new container. A container small enough
to be handled
easily should catch the entire falling grain stream until it
is full or passed
through the entire stream and the caught grain placed into a
larger sample
container. This procedure would be repeated at frequent,
regular times
throughout the transfer.
When all the grain
has been transferred, the sample that has been collected
may be reduced by coning and quartering or by using a sample
divider to 1 to
1.5 kg for transmission to the laboratory.
If it is not
possible to sample the grain during a transfer, then a probe may
be used. It is recognized from research results that a probe
sample is not
representative (see Appendix A). When probe sampling is used
a note should
be made of that fact in the final report. In using the
probe, an effort should be
made to reach every part of the storage container. Several
times as much grain
as is necessary for the final sample should be taken and
then reduced by coning
and quartering or by using a sample divider. Samples should
be taken with the
probe in at least the positions shown in Fig. 6, using a
compartmented probe
pgl6x57.gif (426x426)
that samples at all levels.
Mass Storage in
Bags. Obtaining a representative sample of a large mass of
grain stored in bags can only be done if every bag is
accessible. To sample such
a store requires that one chose enough random numbers and
then move the
grain one bag at a time to a new location diverting bags for
sampling corresponding
to the random numbers. The diverted bags should be sampled,
preferably
by coning and quartering the whole bag or putting it through
a sample
divider to obtain 1 to 1.5 kg of sample for the laboratory.
The remainder can
be returned to the bag and to the store.
A less satisfactory
alternative is to obtain a sample from each randomly
chosen bag by probing. A probe long enough to reach
diagonally from corner
to corner of the bag should be used and the bag should be
probed on both
diagonals and in enough other locations to obtain 1 to 1.5
kg of grain from
each bag.
It should be noted
if every bag is not available to be sampled so the result
will refer only to those bags that were accessible. The bags
sampled should be
chosen by assigning numbers to those that are available and
using a table of
random numbers to choose the bags.
Sampling procedures
should always be reported, especially when the sampling
is suspected to be nonrepresentative as in the case of
stacked bags,
unshucked or unshelled grain heads and cobs, and when there
are visually
observed concentrations of insects or mold, or both.
V. LOSS MEASUREMENTS AS
RELATED TO SITUATIONS WHERE
THEY OCCUR
Many, if not most,
postharvest losses occur as a result of externally applied
adverse factors, as when insects, rodents, and birds consume
the grain. Other
losses occur while, or because, the grain is in an otherwise
useful state or
process. Losses are often sustained while the grain is being
threshed. These
losses are brought about by (deficiencies in) the threshing
process.
Grain must be
transported from farm to urban centers. During this process,
bags or vehicles may leak and grain is lost along the way.
The transporting
process is useful; it also may result in losses.
In this section,
measurement procedures are dealt with as they relate to the
process the grain is undergoing. The techniques for
analytical-type testing not
given herein are in Chapter VI.
Processing losses
are affected by prior induced quality factors such as checking
and cracking rice and corn, and a methodology should put
such factors in
perspective.
Methods are not
given for all the procedures needed to determine prior-to-processing
damage that brings about subsequent losses during
processing.
Also methods are not given for all processing damage that
causes losses during
further manipulation.
A. Background Information
D.A.V. Dendy, with K. L. Harris
Two basic concepts
are used in this chapter. One is to measure the situation
(usually output) of a given operation and to compare it with
an ideal (hand or
special machine) operation. The other is to measure losses
by weighing the
various food, feed, and other streams and making direct calculations
of what
does not end up as food.
Whether the loss is
waste is not a matter that depends on methodology. Bran
can be waste, feed, or food, independent of loss-assessment
methodology.
What results as
food may be compared to total food value, to food obtained
by the best possible process or best possible commercial
process, or even by an
experimental process. The methodology simply needs to be set
up to make the
required measurements.
Shelling of Maize
Stripping of maize
grain from the cob is known as shelling. Losses occur
wherever mechanical shelling is not followed by
hand-stripping of the grains
remaining on the cob. Certain shellers damage the grain,
making insect penetration
easier and subsequent storage losses higher.
Threshing
Losses occur during
threshing by spillage, by incomplete removal of grain
from stalk, or by damage to grain during threshing. They
also occur after
threshing due to poor separation of grain during cleaning or
winnowing.
Incomplete
stripping usually occurs in regions of relatively high labor cost at
harvest time, where the method of threshing leaves some
grain unthreshed but
labor is too expensive to justify hand-stripping. Workers in
Malaysia observed
that 1.13% of paddy was lost by falling outside the threshing
tub; it was also
noted that up to 11.7% was left on the straw.
Certain mechanical
threshers have cleaning equipment designed for only dry
grain. A wet season's harvest, eg, of paddy, will clog the
screens and grain will
be lost with leaf and broken stalk.
Use of oxen for
threshing paddy provides a trodden straw said to be more
easily digested. If the threshing floor is muddy or cracked,
grain will be lost.
There can be a 5%
increase in cracked and broken kernels after combine-harvesting
paddy compared to hand-harvesting and hand-stripping.
Cleaning and Winnowing
Cleaning is
customary before milling. At the home, hand-cleaning is a combination
of hand winnowing with hand removal (eg, of stones); losses
can be
very low when carefully done or high when siftings are
allowed to scatter on
the ground or winnowing done with the same result. With
correct equipment,
losses should be low in mills, but equipment undersized for
the quantity of
extraneous material, such as dirt, will cause losses of grain
by removal with the
dirt or by the dirt being carried forward into the milling
stages. Loss assessment
is difficult as losses are usually low; high losses are
spotted by operators
and the extraneous matter is recleaned.
Drying
Two losses are frequently
caused by drying: removal of grain and portions
of grain from the drying system, and damage to the grain
leading to a subsequent
loss.
Grain which is
dried in yards, on warehouse floors, or on roads will be
partially consumed by birds and rodents. Wind, either
natural or from passing
vehicles in the case of road drying, will blow some grain
away. Although very
little grain is removed on vehicle tires, damage by vehicles
may cause subsequent
losses. Mechanical dryers may cause damage leading to removal
of parts
of the grain (such as bran) from the system either in the
air flow or in subsequent
cleaning operations.
The principal
loss-factor occurring during drying is caused by kernel cracking
("checking") of grains such as rice, which are
eaten whole. Usually the
greatest damage occurs through re-wetting which happens when
grains of
different moisture content are mixed in a dryer, and when
rain or dew re-wets
grain in a yard. The damage is manifested as broken grains
during milling,
especially in the polishers.
Primary Processing (Milling)
This includes all
processing operations carried out on grain in the home or
mill, such as cleaning, parboiling, hulling, de-branning,
grinding, and separating
(classifying). Secondary processing (cooking, baking,
fermenting, extruding)
is excluded; such losses as occur are usually unavoidable,
being intrinsic to
the process and preventable only by a change of process --
more a subject for
the sociologist than technologist.
In the home and
small mill, grain processing is effectively a batch process in
which relatively small quantities of grain are processed by
one or more operations
and the product collated, then brought together for sale or
other processing.
In large mills, the processes are continuous and loss
measurement is
performed periodically by sampling product streams. All of
the pre-milling
history affects the fate of the grain during milling.
Parboiling
Though easily
quantifiable losses of soluble materials occur during parboiling
of paddy, these losses are more than offset by the
improvement in nutritional
value of the kernel.
Hulling, Polishing, Especially Rice Milling
Removal of the
outer coats from a grain may take place in one or more
stages. For paddy rice, red sorghum, and oats, considerable
mechanical effort
is needed to remove these layers. Any weakness in the
kernel, caused previously
or inherent, will manifest itself at this stage. Even with
grain in perfect
condition, only the best process with correctly set
machinery will yield an
out-turn of whole polished grains approaching 100%. In the
case of rice,
broken grains command lower prices and finely shattered
material ceases to be
human food. Some leaves the mill in the husk (fuel or
waste), but most with
the bran (feed). Bran removal may be considered a loss. With
the consumer
demanding rice with a high degree of polish, the loss at
that stage must be
measured and then changes made to keep the losses to a
minimum. It has been
noted that even a 1% increase in yield of whole grain rice
can result in huge
increases in national resources.
Grinding
In some processes
such as wheat milling, removal of an edible part of the
grain, eg, the germ, is deliberate and desired by the
consumer. Whether this is
a loss depends on the terms of any particular study.
However, mechanical
losses of desired ground products frequently occur, often
caused by maloperation
of the process or worn equipment. Common processes are
pounding in a
mortar, grinding between stones or toothed steel plates, and
the complex
Hungarian system for milling wheat into flour.
Separation
Whether the
separation of edible from less desired products is done in the
home (eg, winnowing hulls and bran from rice) or mill (eg,
sieving flour from
bran), complete separation is rarely achieved. With rice, it
is difficult to separate
the more finely broken grains from bran, and with wheat,
flour adheres to
bran and special equipment is used to remove most of this as
flour.
Nonuniformity
Processing of
mixtures that are nonuniform because of such factors as
hardness and softness of kernels, size (length, plumpness,
etc.), and moisture
content difference is itself a cause of losses.
CHAPTER V
B.
Guidelines for Performing Studies of
Farm Storage Losses(3)
J. M. Adams and G. W. Harman
1. An
inter-disciplinary team, comprising at least a storage technologist and
an economist, is necessary. The team should arrive in the
area early enough
before harvest to enable it to plan effectively, to select
fieldwork areas, to train
and brief enumerators, and to conduct necessary trial runs.
2. The sampling
frame for investigations on both technical and economic
aspects should be determined and stratified. Areas chosen
for fieldwork
should be as representative as possible of traditional
practices, both preharvest
and particularly postharvest. (See Chapter IV.)
Information on the
technical aspects of losses should be obtained by:
1. Collecting the
necessary baseline data on the moisture content, damage,
and bulk density (bushel weight) of the commodity
immediately prior to storage,
and recording any procedures involving selection or
treatment of the
product for storage.
2. Recording the
quantity of the commodity placed in storage.
3. Recording the
date on which some of the commodity is first removed
from the store. Thereafter samples of the commodity should
be taken at
monthly intervals. The sampling method used should be pre-tested,
prior to
large-scale use, for its acceptability to both the
investigator and the farmer.
4. Collecting
information on the rate of consumption of the stored commodity
over the storage period. This should be done on each
sampling visit.
5. Analyzing the
samples to obtain estimates of loss and applying these to
the consumption pattern to obtain an estimate of loss over
the complete storage
period. Weight of a standard volume of grain corrected for
moisture
content changes should be used to assess losses in samples
when regular sampling
is performed. If this is not possible the formula method may
be used to
estimate losses within individual samples, but with less
accuracy. (See Chapter
VI.)
6. Setting up
simulation stores, if necessary, which are under the control of
the investigator and simulate the farmers' pattern of
consumption. The commodity
should be accurately weighed in and out of the store. Care
should be
taken that the grain placed in these stores is of the same
quality and selected in
the same way as that placed in the farmers' stores.
Information on
economic aspects will be obtained:
1. By a
questionnaire survey on a once-only basis, conducted with a representative
sample of farmers.
2. On a regular
basis from farmers from whom grain samples are taken, if
this is part of the research, and from official sources.
The questionnaire
survey should be evolved in three stages:
1. A basic outline
following on-site discussions.
-----------------------
(3)Adapted from J.
M. Adams and G. W. Harman. The evaluation of losses in
maize stored on a selection of small farms in Zambia with
particular reference
to the development of methodology. Trop. Prod. Inst. Rep.
G109 (1977).
2. A trial run (see
below).
3. A final
revision. The questions to be asked will depend on the objective
of the survey, the potential ability of the interviewees to
respond, and the time
and staff resources available to the research team.
The questionnaire
should be sectionalized as required by the study. The
following is a guide to some but not all of the main subject
areas:
* General. Farmer's
status, household size, measurements of wealth (cattle
ownership,
alternative employment, size of farm), credit facilities and
usage of.
* Cropping. Crops
grown, area, and disposal/storage.
* Principal grain
crop(s) production. Varieties grown, seed source and
costs, use of
fertilizers and insecticides, drying and pre-storage activities.
* Storage. Quantity
stored, form in which stored, number and type and
structure of
stores, cost of stores and store materials, labor for building
and maintenance,
age of stores, potential life, pre-storage and in-store
treatments, dates
of first and last removals, frequency and quality of
grain removed, site
of removal from the store, usage of grain removed.
* Storage losses.
Cause, severity, usage of damaged grain.
* Marketing. Sales
of grain which is never stored, quantity, variety sold,
reasons for
sales, grade/price made, buyers, transportation.
* Buying.
Quantities bought, form (grain, meal, etc.), frequency, price,
source, usage.
It is important to
emphasize that the above are broad outlines only. Each
situation may require some addition or deletion and all
situations will require
precise framing of the questions to be asked. These six
criteria should be
observed:
1. do not ask
unnecessary questions; limit the number and complexity of
questions so that each interview is completed in 30 to 40
minutes maximum.
2. as far as
possible, frame the questions so that the answer is yes or no.
3. have a trial run
and revise or eliminate difficult questions.
4. avoid sensitive
questions if possible and seek local advice as to which
questions are sensitive. (It is, however, surprising how many
seemingly sensitive
questions can be asked and will be answered if correctly
phrased and
properly put, emphasizing the importance of enumerator
training.)
5. train
enumerators thoroughly, work with them through their initial field
operations, and spot-check their activities at intervals.
6. consider the
feasibility and advisability of moving enumerators between
areas and strata both as a check and as a stimulus on the
individuals' performance.
This questionnaire
survey will probably be asked of a larger sample of
farmers than the one from which samples of the grain are
drawn for analytical
purposes (assuming that the latter is part of the study
involved). Nevertheless,
all of the latter should be asked the questionnaire survey;
their actual activities
on grain removal can be observed in practice and comparisons
of observations
and statements will provide a valuable check on farmers who
are involved in
making statements in the questionnaire survey only.
Economic
information should be collected on a continuing basis from
farmers. If, as is likely, it is necessary to undertake a
program of regular
sampling of farmers' stored grain, regular visits should be
made to collect
economic information of usage patterns, quantities and
prices for sales and
purchases, time required for store building and maintenance
work, and cost of
materials used.
CHAPTER V
C.
Procedures for Measuring Losses Occurring During or
Caused by
Processing Including Threshing, Drying, and Milling
of Most
Grains, but not Maize or Pulses/Groundnuts
D.A.V. Dendy, with K. L. Harris
Processes may be
continuous or batch. In the former, samples of input and
output should be taken at regular and measured intervals.
The amount (1, 5,
or 10 min) of production taken from various lines in the
system can be weighed
to give the quantity of stock carried in that line in
proportion to other lines.
Samples may be taken in the usual way from the bags of grain
entering the
process and bags of product(s) leaving. Overall mass
balances must be
measured and converted to standard moisture content or to
dry weight.
Two fundamental
methods are used: measurement of total system (mass
balance), and comparison with a standard.
Measurement of
total system. The loss itself may be weighed. The optimum
process gives zero loss. Examples are threshing (loss on
stalk) and maize
shelling (loss on cob). In some cases the loss itself cannot
be measured, but the
input of grain and output of products can be weighed, the
difference being the
loss. In other cases, loss will be a comparison of the
traditional or commercial
system as against a perfect hand-stripping standard.
Comparison with
laboratory standard. Comparison is not against a perfect
(100% recovery) standard but with an optimum standard,
usually taking each
unit operation (stage) separately. Although this method is
not ideal, if the
standard of comparison is adequately described, the
comparison will produce
useful information.
It is important
also that unit operations (eg, hulling and polishing) subsequent
to that under consideration (eg, drying) be investigated or
that information
be obtained on the entire flow in the best possible and most
standardized
way.
Sampling (see also Chapter III)
Sampling procedures
are simple for batch processes such as are carried out
in small mills and homes. If a loss of material is looked
for, then a weigh-in
weigh-out procedure will be adopted. Where a lowering of
quality is suspected,
a sample should be taken before the process and put through
a parallel but
optimum process (eg, in a laboratory mill) to compare the
products. In continuous
systems, the unit operation (stage) can be scrutinized while
representative
samples of substrate are taken at regular intervals before
and after. The
condition of the inputs and outputs is determined by
laboratory examination.
The amount (weight) of the outputs is obtained by comparing
the total weight
of the streams over a fixed period of time so that the
comparative amounts of
grain going to food, feed, waste, etc., can be determined.
For example, in a
continuous flour-milling operation, weights taken over a
1-min period of
flour, bran, shorts, and dust will show what proportion goes
into each product.
If dust is 0.5% of the flour + bran + shorts, and dust is
used for fuel
while flour, bran, and shorts are all food, then the loss in
this stage is 0.5%.
Operators
Where losses depend
on operator efficiency, there will always be the problem
of deciding whether the operator is working normally or at
an enhanced
efficiency to impress the assessor. The tester must gain the
operator's confidence
and impress on him that it is not he who is under scrutiny.
The following
examples can be used as a guide for other unit operations.
THRESHING LOSS 1: Unstripped Grain (Loss With the Straw)
A suggested method
is as follows. Random samples of bundles of cut grain
are chosen and threshed by the customary method. The
threshed grain (sample
1) and straw are retained. Directly supervised labor
hand-strips every grain
(sample 2) from and out of the straw. The two grain samples
are then hand-winnowed
carefully to bring hand-stripped and mechanical material to
the
same quality. The good grain is weighed, moisture content
measured, and the
weights converted to a standard moisture content.
It is important to
examine the two samples and estimate as accurately as
possible (eg, by hand sorting of a representative subsample)
the proportion of
useful quality grain. Note and record unfilled, immature, or
green grains that
would be rejected during subsequent processing. Then the
total of these plus
extraneous matter should be determined and the estimated
total weight subtracted
respectively from the main threshed sample and the
hand-stripped
material. The good hand-stripped grain would normally be
lost, and the loss is
the percentage ratio of this to the total good grain,
hand-stripped plus normally
threshed.
Losses due to
scattering and spillage, which may occur with certain threshing
procedures, would be evaluated separately by recovering
scattered or
spilled grain from known or controlled amounts of threshed
grain or by weigh-ins
and weigh-outs if these are known or can be determined.
THRESHING LOSS 2: Damage to Grain
The method to be
followed for estimating grain damage during threshing is
basically the same as that for any other processing stage:
One must standardize
all other processing steps leading to the final product and
do the threshing by
the normal (local) method and by an optimal method which
will give maximum
yield of undamaged grain.
As with estimating
loss with the straw (threshing loss 1 above), the estimator
selects random bundles of cut grain. These are randomly
divided into two lots
of approximately equal weight. The methodology consists
essentially of
weighing initially and at the end to compare the traditional
(or any other
processing procedure) with a processing procedure that gives
100% recovery.
Lot 1 is threshed in the manner under evaluation. This may
include a final
hand-stripping, depending on local custom. The threshed
grain, including dry
hand-stripped, is bulked.
Lot 2 is
hand-stripped carefully and bulked. (Note: Subsamples of each lot
may be taken if laboratory equipment is available.) The
separate samples are
processed carefully to avoid loss or damage through the
locally used processing
system (cleaning, parboiling, drying, or milling) if this is
a batch system in
which the samples can retain their identity. The products
are then analyzed for
broken grains and damaged grains. This is especially
important for rice, which
is desired as a whole grain, and grains such as red sorghum
which undergo a
two-stage grinding system wherein bran or husk is first
removed from the
whole grain before grinding.
If local labor is
available, separation of whole from broken grain may be
performed by the local method (eg, hand-winnowing): The
out-turn of whole
grain is calculated and the results for threshing (by one or
more local methods)
compared with those for hand-stripping.
If the identity of
the samples would be lost by processing through the local
system (large dryers or large continuous mills), then
subsamples should be
taken and processed in the laboratory.
MAIZE SHELLING LOSS: Loss on Cob or Core
The method used is
basically the same as for threshing: Random samples of
cobs are taken and the grain is shelled by the method under
test. All the grain is
collected and weighed and a sample taken (sample 1). The
grains left on the
spent cobs are hand-stripped and weighed and a sample taken
(sample 2).
Moisture content of the two samples of grain is measured
with a moisture
meter and, if necessary, an adjustment made to the weights.
The percentage
ratio of the hand-stripped grains to the total is the
percent loss. The two
portions of grain must be kept separate for the next loss
assessment, grain
damage.
Losses of
insect-damaged, mold-damaged, or stored grain may be different
from the losses without such added factors. It is therefore
necessary to define
the situations being measured and the condition of the
grain. For example,
losses during the shelling of maize may actually be due to
the release of frass
(insect chewings, excreta, cast skins, insects and insect
fragments) at the time
of the shelling process, or the intentional removal of
weevils or musty grains
(see next section).
MAIZE SHELLING: Grain Damage
Many mechanical and
hand shellers cause damage to the maize kernels
which can result in a loss of food.
Shelled grain from
the previous loss assessment, but not the hand-stripped
material, is sampled and a representative subsample of at
least 200 grains
obtained. These grains are examined visually for cracks and
scratches, and the
number of damaged grains counted and the total expressed as
a percentage. It
is important not to count insect-damaged, mildewed, or
shrivelled grains, only
damage caused by the sheller. To check this, a parallel
sample of cobs should
be carefully stripped by hand and at least 200 grain samples
also examined. An
example of the use of these methods is given in Fig. 7.
pgl7x70.gif (600x600)
DRYING LOSS ASSESSMENT: Loss by Damage
In this section the
grain under consideration will be raw paddy rice, though
the methodology can be applied in principle if not in detail
to other grains and
to parboiled paddy. The method is based on that used by a
TPI team in
Malaysia and was used to compare three drying methods: 1)
yard (sun), 2)
batch (Lister), and 3) continuous.
1. Yard (Sun) Drying.
The method for
dryer-induced losses based on a laboratory milling operation
may be performed in a mill yard, on the highway, or in the
farmyard.
(a) Method for Use in a Rice Milling Laboratory on Small
Samples
As the bags of one
variety of paddy arrive at the yard, they are sampled (see
Chapter IV) and blended. The composite or bulked sample (of
about 1 to 1.5
kg) is then dried carefully. ((4)"Carefully" means
dried in a laboratory
dryer with forced air convection
at 1.5[degrees] to 2[degrees]C above ambient air so as to
bring the samples to
an equilibrium moisture constant (ie, about 14%) in not less
than 36 hr.)
Meanwhile the paddy will be dried in the usual way
and, when dry, rebagged for storage prior to milling; a
further sample of
about 1 to 1.5 kg is then taken. The two samples (before and
after drying) are
placed in cloth bags and, as soon as possible after
sampling, are dried carefully4
down to approximately the same level of moisture. A small
flatbed dryer
with a flow of air only slightly (1.5[degrees]C) above
ambient is suitable. Drying to
around 14% moisture content should take 6 to 12 hr. After a
further three to
five days to equilibrate (stabilize), the samples are
checked for the exact moisture
content and milled.
The best procedure
is to use a standard laboratory mill (huller plus cone).
Each process should be done in a standard way and in
accordance with
manufacturer's instructions. The rice will be separated from
husk and bran in
the laboratory mill. Whole and broken grain proportions are
then measured by
separating on a hand trier (indented tray) or a small rotary
trier (indented
cylinder) and weighing.
(b) Method for Use in Mills
If a laboratory
mill for small samples is not available or if the data are
required for mill use, the following procedures can be used:
Large samples (1
to 2 kg) are taken from representative bags being emptied
onto the drying
yard, so that the total bulked sample weighs at least 25 kg.
This sample is then
dried carefully(4) in a small batch dryer (as above). A
sizable sample of the dried
paddy from the yard is also obtained and the two samples
dried and equilibrated
as for small samples. If parboiling is customary, it should
now be
performed in a standard manner, suitable to the variety and
district. The
samples are then milled in a small commercial mill of local
type (Engleberg,
cone, "modern" )and the total product collected.
Many small mills that operate
on a toll basis are suitable for this purpose. The product
is separated into
whole and broken grains. If possible this should be done on
a separator (some
small mills have these and will provide the product
fractions already separated).
Alternatively, local labor may hand-winnow to separate. The
fractions
are weighed and the out-turn of whole grain calculated as
before (a).
Note: While it may be inconvenient to deal with large
samples, use of a
commercial rather than laboratory milling system ensures
that the results are
directly applicable to the local situation.
2. Batch Dryer.
Samples are taken
from at least four places near the top and four near the
bottom of the drying bin with good distribution across the
bin area. Samples
must be taken as the paddy is entering the bin (6 to 12 in.
from the bottom) and
just before the bin is fully charged.
Samples are taken
from approximately the same sites as the bin is emptied.
Each sample is kept separate in a cloth bag and is not
blended with the other
samples. There will thus be at least eight samples before
and eight after drying
for each batch. The samples are dried uniformly and
carefully(4) on a laboratory
dryer as for (a) above, stabilized three to five days,
milled on a laboratory mill
as in (a) above, and the results tabulated. It is important
to compare drying
damage on samples from each part of the bin; that at the
bottom is frequently
overdried and that at the top is frequently re-wetted by
transfer of moisture
from below, with consequent high breakage during subsequent
milling.
The mean figures
for brokens for input and for the batch-dried paddy
indicate the average damage caused by the drying process. As
a guide to
maloperation, the differences between brokens obtained from
samples of
dried paddy from different parts of the bin are important;
the mean figures for
a whole dryer are not.
3. Continuous Dryer.
With a continuous
dryer, sampling of input and output is performed periodically.
Samples (1 kg)(5) should be taken every 15 min over a period
of at least
1.5 hr. Larger dryer output may require larger samples. If
input is varying,
sample the same grain in and out of the dryer.
((5)Appropriately larger
samples must be taken if a small commercial-type mill rather
than a
laboratory unit is to be used, ie, sample size must be
matched to test
equipment.)
As with batch
dryers, it is better if the samples are kept separate. Samples in
cloth bags are placed, as soon as possible, in the
laboratory dryer (see 1.a).
When dried to 14-16% moisture, the samples are kept for
three to five days
before laboratory milling. The proportion of broken grains
should be constant
if the wet paddy is of constant quality and the dryer is
running consistently; the
difference between the mean figures for input and output
samples gives a
measure of the damage caused during drying.
GRINDING LOSS AS BRAN: Comparative Assessment by Weight
Grains such as
wheat, maize, and sorghum may be ground in stone mills, in
mortars, or in steel plate or steel roller mills. If the
objective is not only to
provide a flour or meal but to remove bran, the optimum
milling will remove
all the bran and leave all the endosperm (inner part) of the
grain as flour. The
separation of bran from flour is usually done periodically
during the grinding;
sieves of cloth are frequently used. Winnowing (air
classification or purification)
may also be used. The bran and other offals will usually be
used for
animal feed. The problem in assessing the yield of desired
product (flour) is
that of comparative weighing of various mill fractions over
measured time
periods. Quality of flour (eg, amount of bran) also may be a
factor.
Standard procedures have been evolved for
milling wheat on an experimental
mill, but this equipment is extremely expensive and of
little use for other
grains. The methods proposed below may be used to compare
the yields of
acceptable flour derived from different varieties of the
grain or to compare the
performance of different operators, and to obtain
information on other factors.
1. Comparative Measurement of Milling Yield by Variety
The method selected
for milling must be that which is used locally. The
ultimate test is milling yield; whatever losses occur must
be measured by a
standardized procedure.
A number of
different operators (eg, women if they are the traditional
operators) are required, each with a mill (querns or
hand-cranked plate-mills)
of the same type and size.
A portion (about 5
kg) of each variety is given to each operator. Each
sample is then milled by sieving or winnowing the product to
obtain a flour or
meal considered by the operator to be of the usual standard
desired in the
community. The total weights of grain, flour, and bran are
weighed, samples
are taken in sealed bottles for laboratory moisture content
measurement by
oven-drying; and the weights are converted to 15% moisture
content basis (or
dry weight basis).
Weight flour
(15%)
_________________ = extraction
rate (milling yield).
Weight grain
(15%)
The average of the
milling yield for any given variety obtained from different
operators is calculated. Provided that the operator yields
for each variety
are similar, the method will give an indication of
practically attainable milling
yield. This same procedure can be run on a commercial mill.
2. Comparison of Operators
With the above
procedure (1), a series of milling yields is obtained for a
given variety of the grain for a number of operators. If the
products obtained
were all acceptable to users, the operator attaining the
highest yield can be
employed to improve the communities' out-turns of edible
flour or meal.
3. Comparison of Mills
The procedure of
(1) is followed with any one variety to compare the milling
yields (extraction rates) for a series of mills.
4. Insect Damage
A constant volume
of each grain sample is weighed and milled by a standard
milling process and input-to-output of food and nonfood
product measured.
Insect-damaged grain will give a lower yield of flour than
undamaged grain.
RICE MILLING LOSSES
There are many
different milling systems in use, but these may be classified
as being either one- or two-stage, and either batch or
continuous. In the first,
the hulling and polishing are carried out in one machine; in
the second, separately.
One-Stage Batch Processing (eg, Engleberg Type Huller)
The bag of dried
paddy to be processed is sampled and the sample of about
0.5 kg placed in a sealed bottle or plastic bag. The bag of
grain is weighed and
the moisture content of the grain measured. The paddy is
then processed
through the huller and the product collected in the
customary way. A representative
sample of the product is taken. Subsamples (100 g) of the
input paddy
are then milled on a laboratory mill. The product is
separated into husk, bran,
and polished rice, and the rice is separated on a hand trier
(indented tray) or a
small rotary trier (indented cylinder) into wholes, halves,
and points. The
sample of mill product is separated likewise. The relative
proportions of whole
grains and total grain are compared; the efficiency of the
commercial mill can
then be related to that of the optimal laboratory mill and
the relative loss
calculated.
One-Stage Continuous Processing
As the paddy flows
from the hopper or storage bin into the hopper of the
huller, a sample (about 100 g) is taken every minute for 10
min. A sample of
the product flowing from the output side of the huller is
sampled, again a
sample of 100 g is taken every minute, beginning about 0.5
min after the first
input sample has been taken. The two bulked samples (labeled
"in" and
"out") are taken to a laboratory and there
analyzed by the same procedure as
for the batch process.
Two-Stage Continuous Processing
As typical of this
system, the "modern" rice mill consists of rubber roll
shellers and a series of cone polishers with, perhaps, a
finishing brush polisher.
Separations are carried out at each stage and after each
polishing (usually at
least two, frequently four). Skilled operators judge
visually the product quality
at each stage and also the effectiveness of the separation
of product from
by-product. Quantitative estimates of machine effectiveness
may be measured
by sampling on the input and output sides of any machine or
battery of
machines, processing the input sample by a standard
optimized laboratory
method, and comparing products for yield (out-turn) and
quality (percent of
whole grain).
Hulling (suggested basis for a method)
Many mills have two
hullers in parallel and some will have a "return huller"
for the 10% or so of paddy unhulled in the first pass. It
will not be possible to
sample the whole product of the huller system, as the
material passing back to
the return huller has already been through the first huller
unit and has been
separated from brown rice and husk. Samples must therefore
be taken at the
entry and exit to each individual machine; if the mill
possesses three hullers,
each must be sampled separately.
Representative
samples (250 g) are taken from the flow of paddy to the
huller on a regular basis (eg, every minute), and from the
product as it flows to
the first separator (likewise every minute) for about 10 min.
It is important to
obtain a truly representative sample of product; once it has
reached the chute
leading down to the separator some separation can occur. If
possible, the
sample should be taken immediately below the rolls.
The well-mixed
samples are subsampled for triplicate laboratory testing; the
paddy is milled in a laboratory sheller.
The products from
the plant and laboratory mills are then examined quantitatively.
The ratio of weights of total brown rice gives a measure of
the
effectiveness of the hulling attained in the plant compared
to that in the
laboratory. More important is the comparison of the ratio of
weights of broken
to total grains of brown rice. If the plant huller is giving
a higher proportion
of broken grains, then wear or a wrong setting on the
rollers should be
suspected.
Polishing (whitening)
Whether one is
endeavoring to measure losses over the whole polishing
system or for each machine, the method to be used will be
the same: As with
other unit operations, samples are taken of the feed to a
machine or series of
machines and of the product therefrom. The sample of brown
rice should be
milled carefully in the laboratory to the same degree of
milling as that of the
machine(s) in the mill. The out-turns of whole grain are measured
and compared
and the loss in the mill assessed.
Note: Whether it is, in fact, possible to set up such a loss
evaluation system
remains to be seen. The principal difficulty lies in using a
laboratory polisher
in one pass to give the same degree of milling as the
battery of polishers in the
plant and yet also give minimum breakage.
VI. STANDARD MEASUREMENT
TECHNIQUES
A. Preamble to the Methodology
K. L. Harris and C. J.
Lindblad
Definitions((6)See also Chapter II, Section A.)
There is a need to
define certain terms and concepts before proceeding to the
working methodology.
Losses
This effort deals
with removal of food grains from the direct human food
chain which, especially in developing countries, is the
fundamental energy
(calorie) basis of the human diet. The rice weevil consumes
rice when living in
the kernel. If the kernel is weighed before and after it is
bored, it will have lost
weight. If the larva or adult is still present when the
kernel is eaten, less weight
is lost. No consideration is given to a proportional change,
if any, in protein
accompanying the feeding. The relevance of the insect
presence depends on its
fate. If it is cleaned out it is loss; if it remains as
food, it is weighed as food.
Whether insects are eaten or whether the frass is sifted out
or falls from bagged
grain is sometimes fortuitous, sometimes purposeful. It
varies with the season,
with the culture, with hunger, or plenty. While the decision
to eat may be more
socioeconomic than scientific, use or nonuse as food in the
specific situation is
the controlling factor in these procedures.
Pilferage
In this manual
pilferage is not considered to be a loss. It is a transfer of
ownership as is spillage when it is used as sweepings in
lieu of, or in addition
to, wages.
Fungal Damage
It is anticipated
that the quantification of weight loss when the loss is due to
fungal damage will depend on local practices in the use of
the damaged material.
People accept or reject damaged kernels as local custom and
hunger
dictate. One purpose of this manual is to set forth
standardized procedures so
that measurements in one country can be compared with measurements
made
elsewhere. Therefore, in each situation acceptance-rejection
limits should be
defined in terms of a widely used language. Despite such
difficulty, judgment
limits based on information obtained from interviews must be
quantified.
Processing Losses
Grain removed from
the direct human food chain is a loss. Thus milling
losses that become animal feed would appear as a loss
although reentering
down the pipeline with a reduced calorie and, perhaps,
improved nutrition
input. This "feed" as against "food" use
needs to be recognized and
described in any situation where it is a factor.
Postharvest
This manual
generally accepts Bourne's (1) definition of postharvest as the
point at which grain, separated from the plant stalks or
root, is bundled for
field drying or placed in a container in which it is moved
or held, or both. It
can extend earlier, however, to include the time during
which the mature crop
is held in the field for storage or drying.
Household
This manual does
not cover losses in food after it reaches the point where it
is being prepared for cooking or for direct consumption,
even though there
can be serious losses in the hands of the ultimate user. In
the United States, for
example, this may be the most important site. However,
estimates and prevention
of these losses are so dominated by cultural habits and
preferences that
in-depth anthropological inputs are required which are not
usually within
grain loss reduction biology-technology.
Separation From Other Factors
This report
anticipates that grain losses will be considered in isolation from
other food-availability factors in the areas studied. It is
proposed that there is
no present need for guidelines that include such
sophisticated concepts as how
the availability of fish and meat influences the losses, and
need to control
losses, in staple grains.
Rapid Laboratory-type Procedures
None of the
shortcut tests such as presence of numbers of adult insects,
amount of frass, or insect emergence holes are sufficiently
accurate when used
alone for anything more than loose approximations.
"Loss" should be a measurement
of actual grain Substance removed from the food chain.
Techniques
for basic statistical concepts are covered in a separate
section.
How to quantify losses
has been the subject of detailed investigations by the
Tropical Stored Products Centre, England, and has been
assessed by the
Group for Assistance on Systems Relating to Grain After
Harvest.((7)The
acronym GASGA now stands for Group for Assistance on Storage
of Grain After
Harvest.) Papers
listed in the Bibliography at the end of this section give a
definitive appraisal of
these losses. From these review papers, from the original
published material,
from discussions with acknowledged experts, and from first-hand
field and
laboratory experience come the following conclusions on
techniques for
measuring losses:
All of the U.S.
Food and Drug Administration-generated procedures are too
time-consuming, require a laboratory setting, require
difficult-to-standardize
judgments, are on too small a sample size, or have too
variable a relation to
grain weight loss to warrant use in determining grain
losses. These are the exit
hole test, acid fuchsin egg-plug test, berberine sulfate
fluorescent stain egg
plug test, gelatinzation with sodium hydroxide, and
examination for internal
insects. Radiographic (X-ray) examinations require expensive
laboratory-based
apparatus, and are time-consuming and difficult to
standardize. The
Ashman-Simon Infestation Detector has similar liabilities.
Examinations for
insects on the surface of the grain, weighing insect frass
(dust from insect chewings and excrement), and various
procedures to visually
detect damaged grains and count and/or weigh them have been
given field
trials in developing countries. There is a positive
correlation between damage,
insects, and frass with some loss quantifications possible
and the 1970 IBRD
report suggests their use in making rapid assessments.
Some confusion
exists concerning the application of these procedures in
quantifying actual losses. Their use in actual test
situations and positive correlations
to weight losses have been taken by some to indicate a
practical degree
of precision to routinely determine weight losses. Such is
not the case. They
cannot be so used unless the biological and physical
characteristics of each
assessment situation are completely understood. If lots of
grain have the same
histories, then their frass-to-loss relations will be
similar and may be used to
survey them all on a comparative basis. However, if some
have been moved
(and frass is lost), or some have lesser grain borers
(produce much frass), or
some have weevils that make exit holes and some have moths
that hold their
frass in webbing, or the surface insects have been removed
from some lots and
not others, then any standardization between lots, regions,
grains, and countries
becomes a new scientific investigation, not subject to rapid
comparisons.
However, all of
these procedures are of value in a rapid visual and discussion
appraisal of a situation to come to a personal judgment.
Their precision
as indicators of actual losses depends on the expertise of
the user. This is
discussed in Chapter 11, Section D.
Rapid Judgment-Based Procedures]
"Guesstimates"
As these estimates
with some facts by knowledgeable persons have discovered
immediate and urgent needs that could not be met in any
other way, they
have served many purposes. However, as they have been simple
guesses or
preconceived opinions for special purposes, they have no
validity as determiners
of losses. True guesstimates have a valid role in reaching
rapid judgments
that may suffice for some purposes or precede more accurate
evaluations.
Biased Estimates
Although not
germane to the present effort, the practical effect of many of
the biased figures should not be underestimated. Many have
been used to draw
forth budgetary support for grain storage and marketing
research, build storage
structures of sometimes useful value, draw international
attention to
sometimes real and sometimes imaginary needs, and build
local and national
stockpiles that have both fed people and wasted grain to the
ravages of biological
and physical factors.
Traditional Local Estimates
These are
especially useful in getting one's bearings on local situations.
Interviews should not be passed over lightly. They need to
be done with care,
as discussed elsewhere in this manual, assessing the point
of view and biases of
the giver of information, what the figures are based on, and
local meanings of
such basic terms as "loss" and
"percent."
When reinforced by
on-site observations or measurements, such estimates
may be especially useful in obtaining a picture of local
conditions, extrapolating
to larger areas, and seeking out specific examples and
situations. There are
times when local people can make quite accurate comparisons
between conditions
found in grain as it goes into and is taken out of storage
and on actual
wastage to insects, birds, and rodents.
On-Site Expert Judgments
While this type of
rapid appraisal can be used only by experts to assess
percentage or weight losses, its use should not be
underestimated.
In making such
judgments, one needs to consider how local conditions
affect the physical and biological potential for losses. For
example, transport
in damaged bags or makeshift wagons with visible spillage
indicates an obvious
loss situation.
Dry conditions
spell trouble for insects. At 12% moisture or less, grain
insects have a more difficult time feeding and reproducing.
By 10% there are
serious living problems, and if there is evidence of an arid
6 or 8%, then grain
losses to insects are minimal.
Absence of visible
insects or damage after six or eight weeks of storage is a
good indication that there will be few insects for the next
few months also.
The habits of many
rodents are well known. Whether stores are open or
closed to them, and whether harborages or needed water are
available can be
readily ascertained.
Losses to rats can
be predicted from the nature of the local ecological
system. The problem may be more difficult with mice and
other small rodents.
Short-term storage,
good sound bagging, well-constructed transport vehicles,
strict weigh-in/weigh-out control with accompanying records,
the use of
insect, rodent, bird, and fungal control procedures, and low
temperatures all
point to minimal losses. Low or high temperature can be of
overriding importance.
Rice harvested in September in temperate climates may go
into natural
cold storage before insects make even a minimal start. Grain
held under metal
roofs or in bags in the sun at over 55[degrees]C will have
no active insect losses.
On the other hand,
while high moisture, active insect, rodent, and bird
depredations, and visible mold or heating from
microorganisms clearly indicates
trouble and potentially heavy losses, the extent of the
losses is determined
with difficulty by even an expert.
Production and Consumption Figures
Production and
consumption figures have often been suggested as a means
of assessing losses, the difference between what is produced
and what is consumed
being loss. Unfortunately, accurate figures at either end of
the system
are available only in the most sophisticated and developed
situations, and the
approach is of small practical value in many developing
nations and local
developing-country locations.
Standardization
Moisture
Changes in volume
and weight due to moisture need to be explained. Grain
harvested at 21% moisture dried to 15% by mechanical means
or aeration has
lost weight but not food value.
Measurement of
moisture changes requires the use of meters or drying
ovens. Weight changes need to be determined by sensitive
devices. Use of
moisture meters and scales or balances requires such devices
and a degree of
expertise in their use that may necessitate some basic
training. Moisture meters
are discussed in Appendix C.
Accuracy
Overall statistical
concepts are presented in Chapter IV. It seems reasonably
safe to anticipate that 75% confidence limits of [+ or -] 5%
would, for the present,
be as much, or perhaps more, than can be generally expected.
However, as yet,
there is no fixed gauge as to what constitutes reasonable
accuracy. The amount
of method variation that may be expected to occur in different
commodities,
ecological zones, parts of the harvest-to-consumer pipeline,
and types of damage
by different individual or mixed types of losses are
subjects that require
clarification in and before any survey appraisal. The first
field appraisal
should bear these and other factors in mind, particularly as
the desired confidence
limits influence the duration and expense of the assessment.
Literature Cited
1. BOURNE, M. C. Post harvest food losses -- the neglected dimension
in increasing the world
food supply.
Cornell International Agriculture Mimeograph 53 (1977).
Bibliography
ADAMS, J. M. Storage loss assessment techniques, a
biologist's view. Trop. Stored Prod. Centre
(1972).
ADAMS, J. M. Report on post harvest loss assessment in
durable produce, with particular
reference to
methology. Trop. Stored Prod. Centre (1976).
ADAMS, J. M. A guide to the objective and reliable
estimation of food losses in small scale
farmer storage.
Trop. Stored Prod. Inf. 32 (1976).
ANONYMOUS. GASGA Seminar on Methodology of Evaluating Grain
Storage Losses. Trop.
Stored. Prod.
Centre (1976).
HARRIS, K. L. Evaluation of grain storage losses. Report of
the International Bank for Reconstruction
and Development
(1970).
CHAPTER VI
B. Losses
Caused by Insects, Mites, and Microorganisms
J. M. Adams and G. G. M. Schulten
Insects are a major
cause of postharvest grain losses. By boring within the
kernels and feeding on the surfaces, they remove food,
selectively consume
nutritive components, encourage higher moisture in the
grain, and promote
the development of microorganisms.
Methods for
detection of internal insects have been summarized earlier in
this chapter. Methods given in this section are for
determination of losses to
the grain itself and are of three types:
1. Determination of
the weight of a measured volume of grain (see Methods
A and B1). In this case the loss in weight in samples taken
over a known time
period is a reflection of losses caused by insects or
microorganisms, or other
factors. Judgment as to cause of the loss is a second and
necessary step in the
process.
2. Separation of
damaged and sound kernels and determination of their
comparative weights calculated in terms of the whole sample
(see Method B2).
(In both 1 and 2
above, it is usually necessary to obtain a baseline sample of
the condition of the grain at the beginning of the test
period or to conduct tests
to estimate the baseline condition in order to determine the
real losses at that
point in the pipeline.
3. Determination of
the percentage insect-damaged grain and its conversion
into a weight loss using a multiplication factor (see Method
B3). (This method
also gives an approximate figure for use in preliminary
surveys.
Methodology
Sieving
In all of the
methods, prior to analysis, the grain sample should be sieved or
winnowed, or both, to remove dust and insects. Use the sieve
and sieving/
cleaning technique commonly used by the local
farm/merchant/consumer for
removal of such fractions that would be normally discarded
as inedible prior
to further processing.
Determination of the Original Condition of the Grain
Since the weight-to-volume
method is based on differing weights for different
levels of loss, it is necessary to obtain a baseline point,
by sample or
calculation, from which it is possible to compare all future
measurements.
This baseline needs to be in the form of a curve covering
all of the grain/
moisture conditions to be found in the particular grain
situation because some
grain volumes change significantly, and most often
regularly, at varying moisture
contents.
The curve is
obtained from analysis and calculation of a baseline sample.
Determination of the baseline condition is essential so as
to have a fixed
reference point with which to compare losses incurred during
storage. if it is
not possible to obtain this sample until after storage or
the process under study
has already begun, a visibly undamaged sample should be
taken and analyzed
as early as possible. This should be split into three
replicate subsamples and the
measurement required by the appropriate methods 1, 2, or 3
applied to each
subsample. Each subsample should then be placed in a jar
covered with
muslin, to prevent insects entering or leaving, and kept for
four weeks. At the
end of this period, the jars should be examined for insects
and damage. If
there is no damage in any jar, then all three replicates can
be used to calculate a
value. If there is damage in one, this must be discarded; if
two have damage,
both are discarded; and if there is damage in all three,
then take the sample(s)
with 5% or less damaged kernels. If the damage is above 5%, assistance
will be
needed from an expert in determining the appropriate
correction factor.
Method for Baseline Determination
A sample of
approximately 5 kg is either taken from every farmer's store if
they are being treated as individual case studies or, if
there are distinct grain
varieties under study, a representative sample of at least 5
kg is taken for each
variety, assuming that they are fairly homogeneous. If any
of the varieties is
not uniform (does not have a standard weight-to-volume
variation with
changes in moisture due to intravarietal variations of the
local grain(s)), then
either each lot of stored grain must be treated individually
or expert advice
must be sought.
This large sample
is sieved in the laboratory. The bulk sample is subdivided
into five replicate subsamples. The moisture content of a
representative subsample
is measured. The range of moisture content which might be
expected in
the field over the storage season is determined either from
locally available
data or by approximation (a normal range that fulfills most
purposes is
8-18%, depending on climatic conditions). The weight/volume
relationship is
taken over the range as follows: the range is broken down
into five equal steps,
eg, if it is 10-18%, this will be 10, 12, 14, 16, 18. If
small, perhaps 1%, steps
such as from 8-12%, this will be 8, 9, 10, 11, 12%. One
subsample will have a
moisture content near to one of these figures and the
moisture contents of the
other subsamples will have to be changed either by drying or
wetting, as
follows, to cover the range.
Drying down to a
moisture content. This should be done with the grain in a
shallow layer either in a warm, dry place with a current of
air passing over it
but protected from insect attack or, preferably, in a ventilated
oven in shallow
trays at a temperature not exceeding 35 [degrees]C. Its
moisture content should be
checked at regular intervals by allowing a sample to cool
and measuring its
approximate water content. When it has reached the required
moisture content,
it should be placed in a sealed container to cool and the
moisture content
should be measured accurately. As a rough guide, a small
sample of known
weight can be placed on a dish in the oven and its loss in
weight checked.
Wetting up to a
moisture content. This requires addition of a calculated
weight of water to the grain to bring it up to a required
moisture content. The
weight of water required is given by the formula:
Weight of
water to be added (g) = weight of grain
x Required %
moisture content - initial % moisture content
--------------------------------------------------------
100 - required % moisture content
For example, if we
have a subsample of 1,000 g of grain at 12% moisture
content and require it to be at 16% moisture content, the
calculation is:
Weight of water
= 1000 16 - 12 4
-------- = 1000 -- = 47.6 g.
100 - 16 84
This can be weighed
out or, since 1 g of water occupies 1 ml, it can be
measured out as a volume. Water is added to the grain in a
sealed container
with sufficient headspace for mixing, and mixed well. It is
left for two weeks to
condition, but vigorously shaken daily. For moisture
contents over 16%, the
container should be kept at 5 [degrees]-10 [degrees]C in a
refrigerator to discourage mold
growth. At the end of the conditioning period, an accurate
moisture content is
determined for each subsample.
There are now five
subsamples of grain at different moisture content for
each variety. For each subsample the weight that occupies
the volume measure
(test weight container) should be determined by filling the
container (see Fig. 8)
pgl8x86.gif (600x600)
according to the instructions provided with the apparatus
and then pouring
out the contents and weighing it to the nearest 0.1 g. This
should be done three
times for each subsample and a mean result obtained.
There will now be
five mean weights for each variety at five accurately
measured moisture contents. Each of these weights should
then be converted
to dry weight as follows:
Dry weight =
weight of grain x 100 - % moisture content
------------------------
100
For example, if the
volume of grain in the test weight container weighed 800
g and had a moisture content of 15%, then its dry weight is:
Dry weight = 800
x 100 - 15 85
-------- = 800 x --- = 680 g.
100 100
This is done for
all subsamples so as to obtain a set of dry weights for each
moisture content. A graph is now drawn of the dry weight
against the moisture
content, for example:
% m. c.
10.2
12 13.9
16
17.8
Dry wt.
700
680 650
620
600
From this a
reference line can be plotted of dry weights as determined by
measuring the actual moisture content and test weight at the
time a test is
made. This graph is then used throughout the rest of the
sampling period to
represent the dry weight of sample at any moisture content
as if it had not been
damaged in store.
A curve must be
made for each variety or area-cultural situation (see Fig. 9).
pgl9x87.gif (600x600)
Loss Measurement Procedures
METHOD A -- Standard Volume/Weight Method for Damage by
Insects and Microorganisms
After preliminary
laboratory work for the baseline figure, the measurements
can be made in the field or laboratory.
Equipment
1. Test weight apparatus for obtaining a standardized volume
of grain.
2. Balance, such as a triple beam balance, capable of
measuring 1.0-1.5 kg
accurate to 0.1 g.
3. A moisture meter capable of measuring to 0. 1 and
calibrated for the type
of grain being
measured.
4. A suitable size of grain sieve for the removal of
insects, dust, and any other
material that
would normally be removed prior to further processing.
5. Plastic sample bags and a liquid fumigant such as
[CCl.sub.4] to retain samples
for examination at
a later date.
Procedure
A well-mixed
sample, taken from the store, is first sieved by a locally appropriate
method and the weight of sievings are counted as a loss if
they are not
used locally or calculated back to the weight/volume if they
are used.
The moisture
content is measured.
The weight
occupying the volume container is measured. This is repeated
three times and a mean taken. This weight is converted to
dry weight using the
moisture content and formula for dry weight (see derivation
of Fig. 9).
The graph is used
to find the dry weight of a sample at the same moisture
content taken at the time of storage. For example, if the
moisture content of
the farmer's sample was 12%, then referring to the example,
Fig. 9, the dry
weight would be 680.
The weight loss in
the farmer's sample is then calculated as follows:
% of weight loss
- dry wt. from graph - dry wt. in sample
--------------------------------------------------------- x 100
dry wt. from graph
For example, if our farmer's sample at a moisture content of
12% had a dry
weight of 600 g, then as the dry weight on the graph for 12%
moisture is 680 g,
the loss would be:
% dry weight
loss = 680 - 600 x 100 80 x 100
--------------- = -------- = 11.8%.
680
680
This is the dry weight loss, which by definition excludes
moisture content
changes.
Sources of Error
The standardized
method of obtaining the volume attempts to eliminate
variations in packing, but with grain samples containing
very high levels of
damage, some of the grains may become crushed and lead to
inaccuracies
especially with small grains that may be sieved or winnowed
out or crushed so
that their insect- or microorganism-caused emptiness is not
detected. In this
case they may have to be picked out and losses otherwise
estimated. Conversion
factors change in the course of the storage period from high
to low, due to
increased severity of damage to the already-damaged grains.
The admixture of an
insecticidal dust to shelled grain increases friction
between grains and will reduce packing and hence the weight
per unit volume
will be less. Therefore, the weights for treated grain must not
be compared
with weights obtained for untreated grain.
For paddy, the
effect of moisture content on the dry weight occupying a
given volume is negligible, so within a range of 5% moisture
there is no
requirement for a predictive graph.
Rice (as distinct
from paddy) would best be measured by out-turn of the
mill.
Lumps of, or
otherwise webbed-together, grain can add weight. However, if
the lumps are picked or sieved out by local custom, they
should also be picked
out and the kernel loss estimated.
Since little is
known about methods for determining losses in insect-damaged
millet which, in effect, are hollowed shells, and since no
procedures
have been satisfactorily described for picking out and
weighing of insect-infested
millet, this grain presents a real problem not yet resolved
by this
current methodology.
METHOD B1 -- Modified Standard Volume/Weigh Method When a
Baseline Cannot be Determined
The standard
volume/weight method as described under METHOD A is
presently the most reliable method of loss determination.
There are, however,
situations where this method cannot be used without
modification. It may also
be difficult to obtain reliable moisture content
determinations in some cases.
It is often
necessary to make loss estimates in the middle of the storage
period when no baseline has been previously determined. It
also frequently
occurs that in a rural area different varieties of grain are
grown under different
conditions, such as with or without fertilizer, or on poor
or good soils. This
may affect the size of grains and, consequently, the
volume/weight ratio.
Application of
insecticide dusts may also affect the settling of the grains in
the standard volume and increase the volume occupied by the
grain.
Because of these
various conditions, a separate baseline may have to be
determined for each individual farm or storage situation.
This is often impossible
to achieve between harvest and storage.
Procedure
The standard
volume/weight method should be used but an artificial baseline
should be prepared by selecting undamaged samples from the
grain
present in the store at the time of loss determination. The
loss is the difference
in weight (expressed as a percentage) between the undamaged
and the damaged
sample. Conversion for moisture need not be used in this
case since the moisture
content will be approximately the same.
Experience with
this modification of the method is still limited. For maize
ears stored with husks, it is possible to select a number of
undamaged ears, to
shell these, and to use the grains to determine the
baseline. With other grains,
it may be more difficult to obtain an undamaged sample,
especially in cases of
heavy insect infestation.
Sources of Error
Unreliable results
may be produced if, during selection of undamaged grains
from the stored grains, there are hidden internal
infestation, preferential feeding
and egg deposition by insects in grains of different sizes,
and a difference
in moisture content.
To overcome the
problem caused by hidden infestation, the same procedure
for obtaining an undamaged sample as indicated for the
normal standard
volume/weight method can be followed.
Insects do not
often feed or oviposit on grains at random but, depending on
species, they may show a preference for smaller or larger
grains. There is then
the risk that in selecting undamaged grains, a particular
grain size may be
selected which is less liable to infestation than grains of
another size. Grain size
obviously affects the volume/weight ratio. When undamaged ears
are selected,
there is the possibility that smaller ears (with smaller
grains) may be unintentionally
selected, since smaller ears are less often infested than
larger ears due
to a better husk protection. The only way to reduce this
error is to take the
undamaged sample as much at random as possible. In addition,
a sample must
be taken which is larger than necessary and, after good
mixing, only a part of
the sample should be used for baseline determination.
When the baseline
and field sample are taken from the same part of the
storage structure, it is not usually necessary to determine
moisture content
since differences between the two samples are likely to be
small. The weight
difference between the two samples represents the actual
loss. If there is doubt
about the homogeneity of the moisture content of the grains
in store, the
method for baseline determination should be used.
Insects prefer
moist grains rather than dry ones. This behavior may cause
the baseline sample to be drier than the field sample. When
this is suspected to
be the case, the method for baseline determination should be
followed. When
this is impossible, the error can be reduced as much as
possible by taking large
random samples.
METHOD B2 -- Count and Weigh Method
There are many
situations in which a loss estimate is required but where
there is only minimal equipment available and the baseline
could not be determined
before the storage period. In addition, it is sometimes
impossible to
determine a baseline for the standard volume/weight method
because too
many grains have been damaged.
This is essentially
a method that takes a sample, separates it into undamaged
and damaged portions, counts and weighs each, and calculates
the percentage
weight loss. It assumes that the undamaged portion is
totally undamaged.
Used for unshelled
and mold-damaged grains, it provides a useful means of
estimating loss at moderate infestation levels with a
minimum of apparatus.
Equipment
1. Balance with a range of 0.5 g to 1.5 kg accurate to 0.1
g.
2. Tally counter.
3. Plastic bags and a liquid fumigant such as [CCl.sub.4] to
enable retention of
samples.
Procedure
The grains are
separated into undamaged and damaged categories, the latter
being separated according to cause. Grains in each category
are counted and
weighed. The resultant data may be substituted in the
formula below:
% weight loss =
(UNd) - (DNu)
------------- x 100
U(Nd + Nu)
where U = weight of undamaged grains,
Nu = number of
undamaged grains,
D = weight of
damaged grains,
Nd = number of
damaged grains.
Sample Size
Experience with
this method is still limited. A sample size is recommended
of 100-1,000 grains. Besides its simplicity, the method has
the advantage that
damage by different species of insects, such as Sitophilus,
Sitotroga, Ephestia
spp., and Rhizopertha, can be measured. The method may also
be used to
determine damage caused by termites, rodents, and birds.
Sources of Error
Hidden infestation
results in an underestimation of loss because grains that
have lost weight are included in the undamaged portion. When
the grain is
heavily damaged, it may become so broken as to lead to
counting errors.
At low levels of
infestation with the insects selecting larger or otherwise
nonrandom grains, the method is not dependable. At very high
levels of infestation,
kernels may be so destroyed as to be not measurable. For
example, in
maize ears at low infestation, often only the grains at the
top of the car are
damaged because they are incompletely protected by the
husks. These grains
are often the smallest of the ear. The only recommendation
to reduce this error
is to take large samples.
Since insects will
sometimes select and infest larger kernels, any procedure
that compares the individual weights of kernels may result
in a negative weight
loss finding. The selection of internally infested kernels
and their inclusion and
weighing as undamaged can also result in negative loss
findings unless care is
taken to recognize and account for these samples.
A preference of
insects for moist grains may confuse the relation between
weight loss and damaged grains as well. To reduce a possible
error arising
from this behavior, the grains could be dried to the same
moisture content.
METHOD B3 -- Converted Percentage Damage Method (For Use in
Field or Laboratory)
This method is
suitable for insect damage only and provides a useful estimate
for quick appraisal of losses without needing equipment. It
can be easily
used by unskilled but trained personnel.
When grains are
heavily infested, feeding by secondary pests and multiple
infestation may disturb the relation exit/weight loss and so
lead to an underestimate.
Therefore, when possible, it is preferable to determine the
conversion
factor instead of using those factors indicated below. It
will be obvious that
the conversion factor can be ascertained in a sample at any
time after the
sample has been taken as long as the sample is properly
stored.
When losses have to
be measured in a large number of samples, originating
from cereals which were stored for about the same period of
time and under
similar conditions (eg, regional surveys), at least some
samples should be kept
for determination of the conversion factor.
Although the
converted percentage damage method is liable to the same
sources of error as the modified standard volume/weight
method and the
count and weigh method, it has given very good results in
practice.
When
earlier-mentioned methods cannot be used, it is recommended to use
the converted percentage damage method rather than guessing.
With this
method, weight losses in cereal grains and pulses are
determined in a slightly
different way.
Equipment
1. Tally counter.
2. Plastic bags and a liquid fumigant such as [CCl.sub.4] to
fumigate samples when
determinations are
done at a later date.
Procedure
The number of
damaged grains is counted in the sample and expressed as a
percentage. This percentage damage is converted into weight
loss by means of
approximate conversion factors as indicated below. This
factor can be determined
separately for each individual situation or established
factors can be
used. This loss determination is only applicable when the
damage has been
largely done by insects which leave a clear exit hole in the
grain (Sitophilus,
Sitotroga, and Bruchidae).
CEREAL GRAINS
A random sample of
100-1,000 grains is taken and the number of bored
grains is counted. This can be done immediately or within a
few days after
sampling. When there are too many samples to be counted, it
is recommended
to store each sample in a sealed plastic bag to which some
liquid fumigant has
been added.
The percentage of
damaged grains is calculated with the following formula:
Number of bored
grains
------------------------------ x
100 = % bored grains in sample.
Total number of
grains counted
This percentage is
converted into a percent weight loss by dividing it by the
conversion factor (C) or multiplying it by 1/C.
To determine the
conversion factor, a random sample of 100-1,000 damaged
grains is taken which contains 10% or more damaged grains.
The percentage
weight loss is determined with the count and weigh method,
and the conversion
factor is calculated as follows:
Number of bored grains
---------------------- =
conversion factor.
Weight
difference in %
The following
conversion factors have been established in practice where the
larval stages develop within the grain, eg, Sitophilus
species, Sitotroga cerealella:
Maize (stored
as shelled maize
or as
ears without husks) % bored
grains x
1/8
Maize (stored
as ears with husks) % bored
grains x
2/9
Wheat
% bored
grains x
1/2
Sorghum
% bored
grains x
1/4
Paddy
% bored
grains x
1/2
Rice
% bored
grains x
1/2
PULSES
In pulses several
well-defined exit holes may be found in one bean or pea.
When infestation is not too heavy, it can be assumed that
each weevil consumes
about the same amount of food for its development.
Therefore, in the
case of pulses the number of exit holes is counted and not
the number of bored
beans (peas). For determination of the conversion factor in
pulses, the same
procedure is followed as for cereal grains but the damaged
sample must consist
of beans (peas) with one exit hole only. The conversion
factor indicates the
number of exit holes which equals a weight loss of 1%.
In the field
sample, the number of exit holes has to be counted in 100-1,000
beans. This number is divided by the conversion factor and
the percentage
weight loss obtained.
A known conversion
factor for cowpeas when bruchids are the cause of
damage is number of exit holes in 1,000 grains divided by
200.
CHAPTER VI
C. Losses in
Grain due to Respiration of Grain and Molds and
Other Microorganisms
R. A. Saul, with K. L. Harris
A mass of grain can
be considered as a living organism that feeds on itself. It
is made up of the individual seeds which are hosts to the
many microorganisms
of fungus, yeasts, and bacteria. It loses or gains moisture
depending on its
moisture content and the ability of the surrounding air to
absorb or release
moisture (relative humidity). For example, maize at 12%
moisture in air of
75% relative humidity will gain moisture until it reaches
15%. If the grain
moisture gets high enough the grain will sprout. At lower
moisture levels the
seed is essentially dormant and has a very low and rather
constant rate of
respiration.
Microorganisms can
grow under lower moisture levels than grain. They take
moisture from the air and use it for their metabolism.
Yeasts and bacteria
require an atmosphere of 95% relative humidity or higher,
while fungus grows
under conditions as low as 75% relative humidity.
The rate of growth
of the microorganisms is dependent on temperature as
well as moisture. Also, the extent of physical damage to the
kernel is a factor
which influences the rate of growth.
Growth of the
microorganisms and the seed is at the expense of the seed dry
matter. The rate of growth is reflected in the rate of dry
matter loss. When
quality is reduced to the degree that the grain is rejected,
there is an additional
loss of quantity.
Weight losses due
to respiration of the grain itself are unimportant until the
moisture is so high that serious deterioration by
microorganisms occurs. In
other words, when there are serious quantitative losses due
to respiration, the
quality has so deteriorated that total, or kernel by kernel,
rejection for food
use becomes the dominant factor, not losses in weight due to
respiration. At
this point, determination of losses involves an appraisal of
amounts of grain
rejected for food use.
The conclusion must
not be reached that if there are no changes in weight
that the grain is free of mold' toxins. Toxins are a separate
matter. When
suspected they must be determined by special tests.
Thus, there are two
types of losses. One is the loss due to grain being
converted by microorganisms to carbon dioxide and water. The
other loss
occurs when the grain (in its entirety or as individual
kernels) is rejected as
food. Such rejection can occur because of an obvious
discoloration or odor, or
because of the more technical knowledge or implication that
harmful substances
(mycotoxins) are present. In the latter situation, one must
determine
the amounts of grain rejected for food use.
Any visual survey
by locals or outsiders on what an individual rejects or
accepts becomes a difficult assessment. It needs an input of
all of the principles
of measuring subjective values, bearing in mind that bias is
eliminated with
difficulty and that all elements of bias are probably not
completely known.
Loss Measurement by Standard Table Based on Time,
Temperature, and
Moisture
It is the nature of
molds, yeast, and bacteria to reduce organic material to
simpler organic compounds or even to its inorganic form.
That is, molds decay
the grain and, if conditions are favorable for the growth of
mold, then they
will destroy the grain.
Long before the
grain is completely destroyed, it is made useless as food
because of the musty odor, discoloration, and possibly
formation of toxic
substances. In fact, this will occur by the time 1 or 2% of
the dry weight has
been destroyed.
The rate of loss of
dry matter due to mold growth depends on, in order of
importance, grain moisture content, temperature, and amount
of physical
damage to the grain.
Although, as stated
earlier, yeasts and bacteria grow at moisture levels lower
than those required by grain, a high moisture environment of
95% relative
humidity or higher is required for growth. Grain in
equilibrium with this
relative humidity will be about 22% moisture, depending on
the temperature.
Rice and maize are often harvested at this moisture content,
but most other
grains and seed crops are harvested at lower moistures.
Mold, however, can
grow under these and even somewhat drier conditions. Mold
growth stops
below conditions of 70% relative humidity. Safe storage
moisture content for
grain will be below that in equilibrium with 70% relative
humidity. Some
molds can grow very slowly in grain at temperatures below
freezing of water,
but at temperatures of 54.5[degrees]C their growth is
stopped. Table Ill shows the rate
of dry matter loss in relation to temperature and moisture,
and shows how
much weight loss may be expected to occur in undamaged grain
at given
moistures and temperatures. As seen in the Table, grain at
25% moisture and
15.5[degrees]C will lose 0.0312% of dry weight per day.
Thus, in 60 days the loss will
be: 0.0312 x 60 = 1.87%. By this time the grain will be
obviously out of good
condition.
TABLE III
Rate of Dry Matter Loss in Undamaged
Grain
as Related to Grain Moisture and Temperature
------------------------------------------------------------------------------
% Loss per Day
---------------------------------------------------------
Temperature
([degrees]C)
15% m.c.(a)
20% m.c. 25%
m.c. 30% m.c.
------------------------------------------------------------------------------
4.5
0.0003
0.0033
0.0098 0.0173
15.5
0.0010
0.0106
0.0312 0.0553
26.5
0.0034
0.0338 0.0994
0.1766
38.0
0.0101
0.1074
0.3165 0.5622
------------------------------------------------------------------------------
(a) m.c. = moisture content.
Notes: Oilseeds will not necessarily follow this table.
Mechanically field-shelled (combine-shelled)
maize will regularly contain approximately 30% damage and
Table IV will apply. Below 15%
moisture-caused losses will be inconsequential.
Damage to the seed
coat of a kernel creates a more favorable condition for
mold growth. Physical damage is defined as any break or
rupture in the seed
coat of the grain. Physical damage is associated with
shelling or threshing and
is also caused by insects and rodents. It can be pronounced
in corn mechanically
shelled at high moisture levels. Small grains such as wheat
and rice would
have very low levels of damage due to harvest but insect
damage should be
considered. Table IV shows the factor by which the rate of
loss for undamaged
grain in Table Ill is multiplied to estimate the rate of
loss for damaged grain.
Thus, if the loss were 1.87% as calculated above and the
grain had originally
had 10% damaged kernels, then 1.87% must be multiplied by
1.30 and the loss
would come to 2.43%.
Tables III and IV
apply to the first 1 or 2% loss of dry matter. The rate of
loss will increase with time as the molds grow and multiply;
however, the grain
will generally be rejected as food by the time 2% loss has
occurred.
Moldy grain may be
unevenly distributed in layers or pockets associated
with high moisture from leaks, condensation, and insects. In
such cases, it is
necessary to measure separately moisture and temperature in
these pockets and
in nonmoldy portions of the grain.
Loss Measurement by Weighing Damaged and Undamaged Kernels
and
Calculation of Loss
The sound and moldy
kernels should be counted and weighed and the average
weight determined.
% weight
loss = (UNd) - (DNu)
-------------- x 100
U(Nd + Nu)
where U = weight of undamaged grains,
Nu = number of
undamaged grains,
D = weight of
damaged grains,
Nd = number of
damaged grains.
Samples taken from
stored grain may contain kernels from portions significantly
stratified as to mold and moisture (insects also), and in
the calculation
of losses it may be necessary to allow the samples to reach
a moisture equilibrium
before weighing. Internal insect-damaged kernels may be
present in both
TABLE IV
Physical Damage Modifier on Rate
of Dry Matter Loss
------------------------------------------------------------------------------
Physical
Damage
Modifier
(% by
weight)
------------------------------------------------------------------------------
0
1.00
10
1.30
20
1.67
30
2.17
------------------------------------------------------------------------------
the sound and moldy portions and may need to be considered.
Experience has
shown that, if as much as 1% is insect infested, infestation
will be visible as
insect emergence holes when about 500 g of grain is rapidly
examined for
insects or insect damage. This examination is conducted by
passing a small
amount of grain at a time across a well-illuminated surface,
and rolling or
turning the kernels while searching for emergence holes. The
500 g can be
examined in about 5 to 10 min. Such an examination should
reveal some, but
not necessarily all, of the holes.
Loss Measurements by Comparison of Weigh-In and Weigh-Out
Losses will be
measured from start of storage until grain is removed from
storage. The method to use for measuring loss should be
based on changes in
unit weight (test weight). As mold destroys dry matter, it
will reduce the unit
weight of the grain.
To use this method,
a baseline for each storage unit needs to be established
by sampling the grain when it is put into storage and
measuring the unit weight
from this sample, which becomes the basis for estimating
loss from future
samples from that storage.
Respiration-Induced Losses That Result in Grain Being
Rejected as Inedible
Any measurement of
weight loss due to respiration of microorganisms
would be dominated by a quality loss which would make the
individual kernels
so bad they would be picked out and thrown away (or fed as
feed), or the lot
would be rejected.
Therefore, the
methodology is to determine what is locally not used for
food. This needs a survey technique. The survey will measure
a level that
depends on a subjective measurement that will vary with
time, place, and
hunger. In surveying, comparative or permanent use of the
data requires that a
sample or photographic record, or both, be kept of what the
rejection levels
were during the particular survey.
Experience has
shown that grain may be rejected as inedible when there is
about a 20% loss in weight due to mold damage. The level at
which this occurs
is highly variable and subjective. It varies by
socioeconomic levels, by local
beliefs and customs, by the degree of hunger, the season and
what is available,
by whether one is a seller or buyer, and by the difference
between common
practice and a demonstration for the outsider. There is,
however, no definitive
answer to the problem of how to obtain a realistic appraisal
of actual conditions
of use.
The appraisal must
fit the local use situation as set forth in the following
guidelines:
1. Consult with the
person regularly making the decision.
2. Take care that
the sex of the person interviewed is the same as that of the
person regularly making the decision.
3. Take care that
age and other social status situation is as practiced.
4. Take care that
outside pressures are not applied:
a. To be more
careful.
b. To be less
careful.
c. To
demonstrate special sight or odor skills.
d. To impress a
husband (wife), headman, outsider, etc.
5. Take care that
location, light, time of day, and utensils are normal.
6. Consider using
internal checks such as replicate samples or repeat samples
on other days.
7. If for home use,
buying, selling, or market grading, have the total situation
appropriate to that decision.
8. Recognize the
importance of interviewer-related bias.
a. Standardize
the approach.
b. Consider the
use of one interviewer throughout the survey.
c. Consider the
use of identical sex, age, and size of local individuals
throughout
the survey.
Additionally,
individual and/or local and/or seasonal or yearly standards
with national and international criteria suitable for
area-to-area, year-to-year,
and country-to-country understanding and standardization may
be compared
but require detailed expert consultation.
As stated earlier,
in any level-of-rejection evaluation, it is imperative that
the level be in a form that can be preserved in photographic
or other standards,
so that there will be a record of what the levels were and
what was rejected.
This transfer from
local decision to technical standard is one for an expert
grain grader. Such a person can transfer the subjective
criteria to an area-wide
survey of the frequency of occurrence.
The standardized
grading approach could be undertaken from the beginning
with an experienced grain grader who would use the
information obtained in
the field to establish a standard of grading which could
then be used to train
the laboratory technicians. If a sound field basis of
judgment were established,
it could be uniformly and accurately applied by the trained
technicians. This
would remove that bias which results when relying on a
farmer's judgment. It
would also reduce interview time and the time to sample the
farmer's store. It
would be necessary, however, to either have the experienced
grain grader
present in the field and laboratory during the entire time
of the first year's
sampling, or to maintain the samples as evaluated by the
farmer in a way that
the grain grader could use them to establish the rejection
standard. The second
approach would be preferred since the seasonal effect could
be observed and a
realistic average would be more easily obtained. From this,
then, would develop
a grain standard which would allow grading of any sample of
grain on
the basis of edible or unedible, and therefore an estimate
of the loss of grain as
food within the area.
CHAPTER VI
D. Rodents
Part 1.
General Considerations, Direct Measurement Techniques,
and
Biological Aspects of Survey Procedures
W. B. Jackson and M. Temme
Food losses to
rodents are acknowledged to be great, but quantification of
this diversion from human food supplies is less than
satisfactory. Literature on
rodent depredations to food (both pre- and postharvest)
recently has been
summarized by Jackson (1). Lack of adequate data and
appropriate survey or
sampling techniques was recognized as a prime deterrent in
obtaining adequate
estimates of loss.
Most data of local
or national postharvest losses result from bureaucratic
guesses. Studies are rarely undertaken, although
extrapolations are sometimes
attempted. (See Jackson [11 for detailed analysis of this
problem.) While many
of the figures quoted in government reports may be correct,
they usually
cannot be documented.
Most of the surveys
which have attempted to obtain data must be suspect,
such as a "felt loss" survey among Indian
stored-grain merchants who reported
that monthly losses (from all pests) ranged from 1.7 to
3.75% of their
stocks. Another report notes that 1.7% of sacks holding
cacao beans in a
Nigerian warehouse were opened by rats and
"estimated" that 10% of the
stored product was damaged. Estimates by different
investigators of postharvest
losses to rodents in India range from 2.5-5.9% to 25-30%,
and even
higher, and annual village losses in India were
"estimated" from 2.3 to 3.3
metric tons.
A few small-scale
studies have provided some statistics. A 1975 study in one
godown in India over 11 months showed losses of 1,400 kg of
food grains due
to 200 rats. Some rodents hoard food, 3 kg having been found
in a single
burrow; but the time required to amass such a volume is
generally not known.
Other estimates of burrow hoards have been as high as 15 kg.
Most efforts at
rodent-damage assessments have been focused on crops
under field conditions; however, even in the most recent
summary of methods
(2) only sugarcane is cited as having an acceptable survey
tool. Suitable techniques
for field assessment of damage to rice also have been
developed and
field tested in the Philippines.
It is evident that
one cannot turn to an existing body of knowledge for
obtaining an accurate measure of postharvest losses. It is
acknowledged that
"the usual method of estimation is to blame vertebrate
pests for all losses that
cannot be accounted for in any other way." FAO, in
assessing its role in
reducing food losses, indicated that no agreed methodology
existed for assessment
of losses from pests generally. Present resources available
for the necessary
engineering, biological, and statistical studies to develop
and evaluate
procedures in each country were deemed inadequate. However,
GASGA and
several FAO projects are now devoting effort to this
concern. The program at
the Vertebrate Pest Center, Karachi, is of particular
interest, but no working
reports are known to be available.
Field Losses
Postharvest losses
often are assumed to start with some manner of storage,
though it must be recognized that crops that are shocked or
windrowed in the
field for drying may well have rodent infestants and that
these rodents can
cause local damage and then be transported into storage
sites. Assessments
may be made in the field directly (usually involving a
sampling technique) or
with indirect procedures.
If comparable fields
without rats can be found, weight or volume differences
in the ultimate harvest would provide a good estimate of
rodent losses -- if
fungus, insect, bird, or large mammal depredations were not
involved or
were assessable. Techniques developed for assessing bird
damage to maize
utilize counts of individual kernels destroyed, the length
of kernel rows eaten,
or simply the proportion of the ear damaged. Separation of
primary from
secondary involvement also is necessary. For example,
insects or smut may be
able to invade the maize ear when the husk has been
penetrated by bird or
rodent activity.
If the crop is left
in sheaves or stacks in the field for a time, serious damage
may be caused by rodents. This damage can perhaps be
measured by comparing
grain losses and contamination in the damaged portions with
sheaves
and stacks that were protected from rodents.
Threshing yards are
known to be sites where considerable rodent damage
and loss can occur. Comparing pre-threshing harvest
estimates with grain
finally used may ascribe losses to the wrong operational
sector, however.
Storage Losses
Direct
determination of actual losses is one approach, although the total
volume of stored products usually cannot be examined due to
time, manpower,
or financial limitations, so a sampling technique must
frequently be
used. Obviously, moisture losses and damage from insects,
fungi, birds, or
other pests must be assessed separately.
Changes in quality
of stored food can be important. Loss of germ by selective
feeding markedly reduces the value of maize. Urine, fecal,
or hair contamination
of stores may provide a disease potential (eg,
Salmonellosis) and alter
the aesthetic valuation, and hence the market price, of the
product.
Unlike insects,
which often are distributed throughout the grain stores,
rodents will be at the periphery of bulk storage and often
nonrandomly distributed
through bagged or boxed products. This complicates any
statistical
approach to sampling and assessment. One approach would be
to examine all
susceptible products by inspecting each bag or container
incoming and outgoing
for rodent damage (and urine by ultraviolet light if this
form of contamination
is of concern). Contents of each damaged unit would require
detailed
examination to determine actual loss. The remaining portion
may be judged
satisfactory for use, convertible to animal food (at lower
market prices), or
unsuited for any use. Operationally, products stored in
certain structures or
sections of structures known to be without rodents could be
omitted from such
routines.
To ascertain rodent
damage and contamination in the total contents of bulk
storage units, such stores can be sampled around their
perimeter to determine
incidence of droppings and gnawed kernels, but this is
likely to be most difficult
because of inaccessibility of this layer.
Sampling schemes
extensively used for assessing grain quality, especially in
transit, will be satisfactory for determining rodent
infestation or contamination
only if the period of transit is relatively short, the load
is well mixed, and a
large active rodent population is not present. Allowing
loaded boxcars to stand
on a siding for several weeks permits invasion from local
populations, but
damage is likely to be peripheral and not detectable by
probe samplers.
Indirect
determinations of losses involve learning the sizes of infesting rodent
populations. If the rodent population can be censused or
estimated, their
daily food consumption (and contamination) could be
extrapolated as an estimate
of the loss. The techniques used to estimate population size
require
statistical assumptions that cannot always be met, although
some simple techniques
that can be utilized to determine population numbers in most
storage
facilities are described in Chapter VI, Section E.
The now classic
techniques used to census rat populations in New York and
Baltimore (3, 4) require calibration for each environmental
complex of concern.
Even so, this may represent the most practical approach.
Essentially the
rodent activity in evidence (droppings, runways and burrows,
gnawed food) is
evaluated by one team and the population size estimated on
the basis of these
signs. After this a second team determines the actual rodent
population by
intensive trapping. When the population estimates of the
first team are in
essential agreement with the capture determinations of the
second team, the
first team continues through the area with sight surveys and
consequent population
estimates. Unfortunately, this calibration process is lengthy
and must be
repeated whenever different species or different
environments are encountered.
Its adaptation to village or godown environments has not
been specifically
demonstrated, but as long as the areas of rodent activity
are discernible,
its application should be possible.
Some attempts occur
at popularizing estimation of rodent numbers by assuming
the rats seen during daylight hours represent a scientific
proportion of
the total population. Unfortunately, such procedures are
without experimental
backing. Furthermore, rats with a larger home range and
daily need for water
may be more rapidly observed than mice that remain hidden
within their food
supply.
On a limited basis,
direct and total counts of a population may be obtained
in a circumscribed area and losses estimated by calculating
the food eaten by
the population. This involves trapping, marking of
individual animals, and
direct observation. This tends to avoid difficulties with
widely varying movement
patterns and nonrandom distribution of animals but is very
demanding
of time. This requires some judgment as to migrations in and
out of the area,
amount of grain as against refuse eaten, etc.
One traditional
estimation technique employs census baiting. By ascribing a
given quantity of a placed bait eaten to a rat, the
population can be estimated.
However, where high quality food is stored and thus competes
with placed
baits, the competition and the neophobic responses (of rats)
are likely to result
in serious underestimates of the actual population. Mice,
with very limited
home ranges, often cannot be estimated with such a technique
when they are
infesting food-storage facilities.
If the population
has been satisfactorily assessed, an attempt can then be
made to estimate the corresponding losses, or at least the
losses caused by the
predominant species, for it is rare for only one species to
be involved.
A minimum estimate
can be made by multiplying the daily consumption of
an individual by the number of individuals in the
population. Consumption is
related to the liveweight of the animals. Mean daily
consumption varies with
the nature of the foodstuff and especially with its
nutritive value. For cereals,
the following amounts of grain can be used: For Rattus
norvegicus, 20-25 g,
Mus musculus, 2.5-3.5, Mastomys natalensis, 8-10, and
Bandicota bengalensis,
9-11.
If no experimental
data are available, daily consumption can be estimated at
1/10 of the mean liveweight of the species.
In addition to the
grain eaten by rodents, there are partially eaten grains
which are unfit for human consumption. Decisions on
discarding such grain
will vary with the season, with the abundance of any
particular harvest, with
local and national mores, etc. Thus, losses need to be on
the basis of actual
discards, not what should be discarded according to
aesthetic and health consideration
(see Chapter VI, Section C).
One very real
concern is for the process of obtaining accurate data. Catching
rats and then releasing them (for Lincoln Index estimates)
is difficult to explain
to a farmer suffering from rodent depredations. Probably
such an approach
should be reserved for government facilities where research
can be
conducted without intrusion into personal rights. Yet
studies ought to be done
in housing units, local godowns, and small shops or markets.
Residents and
owners must have confidence in the investigator and must be
able to see some
direct benefit to themselves for their cooperation, such as
removal of rats or
better storage conditions. Without the full support of local
peoples, the data
derived from study programs are likely to be another set of
"estimates" that
are not well grounded.
Pragmatically how
much damage or loss occurs from rodent infestations is
less important than getting to the sanitation, construction,
and control techniques
that will result in more stored foods being available to
people. But to
justify and evaluate rodent management programs,
cost/benefit ratios have to
be determined. Herein lies the reason that such
documentation needs to be
undertaken.
Summary of the Problems
Each component in
handling and transportation of foods following harvest
must be evaluated separately.
* In-field losses
lend themselves to direct appraisal (weight loss, kernels
damaged) and use
of sampling techniques.
* Transportation
from one site or field to another may enclose rodents
within a food
supply. Especially if the vehicle is relatively small and the
time great,
losses can be of real consequence. Determination of weight
loss, especially
after damaged or contaminated portions are removed,
can be made
directly.
* Local storage --
either in the home or in local godowns -- is the fate of
most grain, and
these sites are the most vulnerable to substantial losses.
Direct measurements
(weight/volume) of depredations are most readily
done, but
interpretations must be integrated with local environmental
conditions.
* Bulk storage,
because of larger volumes involved, is likely to have less
damage
proportionately. The ability either to determine numbers of
rodents or to
assess the damage itself is more limited, however. If the
grain is bagged
or containerized in some way, damage to specific containers
and their
contents can be determined. Contamination especially
is of concern in
bulk storage, since the mixing of a small quantity of
contaminated or
infested grain with a large quantity of clean product
results in a
total lot of contaminated product.
* Economic (and
aesthetic) thresholds for food damage and contamination
need to be
established (5). Efforts at sampling become increasingly
costly at lower
infestation and contamination rates.
Methods-Oriented Summary
The problem of
postharvest losses to rodents resolves itself into three aspects:
1) Losses due to the removal of corn, sorghum, and millet in
which grain
is eaten from cobs, heads, or spears; 2) losses to threshed
or shelled grain; and
3) losses caused by contamination in which the contaminated
grain is discarded.
(Losses due to rejection by the users is discussed in
Section C of this
Chapter.
1. Losses to Ears or Heads of Corn, Millet, and Sorghum
Measurements
consist of estimating the percentage of grain removed from
the heads, shelling, and weighing undamaged heads of the
same size, and
calculating losses by percent or actual weight loss.
Samples may be
taken so as to be representative of the lot as a whole if the
damage is distributed throughout the lot. When damage is
located in a particular
portion of the stack, pile, or windrow, sampling needs to be
representative
of that situation (see Appendix B) with an estimation of the
proportion of the
whole that is so affected.
2. Losses to Threshed or Shelled Grain
Problems of
sampling bagged or bulk grain are of three types: a) Those in
which before and after weights are available or may be
obtained; b) those in
which bagged grain with and without damage may be weighed
and compared;
or c) those in which no actual comparative weights may be
made of the grain
itself. These procedures are amplified below:
a. In many market,
transport, and warehousing situations, the grain has
been previously weighed. Reweighings will give the amount
lost to rodents, if
this is the only source of change. This can be a laborious
and costly task,
however, and usually an estimate must be made using one of
the procedures in
the following two paragraphs.
b. Comparison of
weights of undamaged and damaged bagged grain: Rodents
often concentrate their feeding and nesting in fairly
well-delineated areas
of bagged grain storage. When this is the case, damaged bags
may be weighed
and compared with the weight of undamaged bags taking
appropriate care to
obtain representative samples of the bags if weights before
loss are not available.
When the individual bags have already been weighed, direct
and actual
losses may be readily obtained.
c. Overall losses
to grain in storage: Most often serious rodent losses occur
in relatively long-term storage or in a long-established
marketing or warehousing
situation where grain is present under a stabilized pattern.
With long-term
storage, local rodents may be found out of the store, moving
in for feeding
and subsequent habitation. They will live in the stored
grain if undisturbed and
if water is nearby. Rodents in markets where there is a
permanent supply of
grain moving in and out of the storage will usually be
living nearby, in holes in
or under the floor, between walls, or in burrows, moving
into the grain for
food, and to nearby sewers, drains, or sinks for water. In
these cases, losses
involved are estimations of the rodent population, and the
food loss is calculated
on the basis of the number of rodents x time x food
consumption.
Some simple methods
suitable for general use of rodent population estimation
are given in Chapter VI, Section E. Rodents, however, are
known for
their diverse feeding habits and their food intake may not
be limited to the
grain supplies.
Recommendations
Specific field
studies, preferably integrated with insect-loss evaluations,
should be undertaken to quantify rodent losses in selected
environmental situations.
Typical sites might be small community or commercial
godowns, individual
farm storage structures, kitchen or household storage, and
field drying
or curing operations. Effects of different environmental
regimes and different
rodent species need to be considered. Whenever possible,
association with
existing FAO, EPPO, CARE, or binational programs would have
obvious
advantages.
At the village
household level, direct measurements of loss contamination
could be made on a daily or short-term basis. This requires
measurement of
foods purchased or taken from stores and analysis of amounts
actually available
for later consumption. Rodent populations could be evaluated
by estimating
sign or intensive removal trapping. Such an effort would
require exceedingly
good cooperation of village residents and merchants and
great honesty
on the part of all participants.
For small godowns
the most satisfactory measure is the comparison of input
stores to those taken out at a later date. This involves
measurement of the total
stores and evaluation of contamination. For larger godowns,
this requires use
of sampling techniques. Rat populations have to be
determined by trapping or
census feeding. Because of the inaccessibility of many
areas, use of sign probably
would not be satisfactory.
Considerations in
evaluative efforts (6, 7) should include: obtaining known,
estimated, or "felt" losses from owners,
occupants, or merchants; evaluating
structure for harborage and infestation potential;
quantifying the rodent sign;
evaluating daily/weekly/monthly/annual grain-handling
procedures and sanitation
practices; monitoring incoming and outgoing products to
determine
depredations; accounting for hoarding activities (eg, burrow
excavation); and
segregating losses from moisture decrease, insects, birds,
and fungi, and determination
of primary causes of loss.
Literature Cited
1. JACKSON, W. B. Evaluation of rodent depredations to crops
and stored products. EPPO
Bull. 7(2): 439
(1977).
2. FAO/CAB. Crop loss assessment methods. FAO Manual,
Commonwealth Agr. Bureaux,
Slough, England
(1971).
3. DAVIS, D. E. The rat population of New York, 1949. Am. J.
Hyg. 52(2): 147 (1950).
4. DAVIS, D. E., and FALES, W. T. The rat population of
Baltimore, 1949. Am. J. Hyg. 52(2):
143 (1950).
5. TAYLOR, T. A. Major problems affecting productivity of
cereals -- the pest problem. In:
Agr. Res.
Priorities for Economic Development in Africa, Abidjan Conf. 1968. NAS-NRC
Publ. 2: 175
(1968).
6. ANONYMOUS. Group for Assistance on Storage of Grain in
Africa Seminar on the Methodology
of Evaluation
Grain Storage Losses. Trop. Stored Prod. Inf. 24: 13 (1973).
7. ADAMS, J. M. A guide to the objective and reliable
estimation of food losses in small scale
farmer storage.
Trop. Stored Prod. Inf. 32: 5 (1976).
Bibliography
BROWN, R. Z. Biological factors in rodent control. U.S.
Public Health Service Training Guide
(1960).
EVERARD, C. 0. R. Some aspects of vertebrate damage to cocoa
in West Africa. Proc. Conf. on
Cocoa Pests
W.A.C.R.I. (Nigeria), p. 114 (1964).
FELLOWS, D. P., and SUGIHARA, R. T. Food habits of Norway
and Polynesian rats in
Hawaiian
sugarcane fields. Hawaii. Plant. Rec. 59(6): 67 (1977).
FERNANDO, H. E., KAWAMOTO, N., and PERERA, N. The biology
and control of the rice
field mole rat of
Ceylon Gunomys gracialis. FAO Plant Prot. Bull. 15: 32 (1967).
FOOD AND AGRICULTURE ORGANIZATION. Reducing post-harvest
food losses in developing
countries. ACPP:
Misc./21:15 pp + annexes (1975).
FRANTZ, S. G. The behavioral/ecological milieu of godown
bandicoot rats -- implications for
environmental
manipulation. All India Rodent Seminar, Siddhpur (1975).
HOPF, H. S., MORELEY, G. E. J., and HUMPHRIES, J. R. 0.
(eds.). Rodent damage to
growing crops and
to farm and village storage in tropical and subtropical regions. Centre
for Overseas Pest
Research, Trop. Prod. Inst. (1976).
KRISHNAMURTHY, K. Problems of food grain storage. Training
Manual. Asian Productivity
Organization, APO
Project TRC/IX/73, Tokyo, 81-84 (1974).
PRAKASH, I. Rodents and their control. Post-harvest
prevention of waste and loss of food
grains. Training
Manual. Asian Productivity Organization, APO Project TRC/IX/73,
Tokyo,
185-192 1974).
SANCHES, F. F. et al. Annual Report. Rodent Research Center,
College, Laguna, Philippines
(1971).
SPILLETT, J. J. the ecology of the lesser bandicoot rat in
Calcutta. Bombay Natural History
Society (1968).
CHAPTER VI
D. Rodents
Part 2. Loss Determinations by Population
Assessment and Estimation Procedures
J. H. Greaves
Direct measurement
of postharvest grain losses to rodents is difficult. As
explained in Part 1, the losses to rodents have to be
distinguished from losses
to birds, spillage, and pilferage, and, in the fields, from
shedding or preharvest
losses. Therefore, to determine the loss to rodents, all of
these other losses
must be identified and measured separately. Weight losses
due to other pests
and to changes in moisture content must also be measured and
considered. In
addition, specialized studies in the ecology of the rodents
may be required.
Thus, direct assessment of losses to rodents is complex, and
can rarely be
contemplated except as an aspect of a multidisciplinary
research study.
In contrast,
techniques for the estimation of rodent populations, developed
by specialists in the fields of rodent control and small
mammal ecology, are
well established. Clearly, the extent of grain loss to
rodents depends on the
distribution, size, and species composition of the rodent
populations involved.
Simple versions of established population assessment
techniques can therefore
enable the ordinary competent biologist with a little
specialized training to
derive loss estimates which, though indirect, will be based
on objective data
and, though approximate, will generally be of the correct
order of magnitude.
The methods
proposed here are intended primarily for use in grain stores.
They may also be considered for use, if intelligently
adapted, in fields during
the immediate postharvest period and in threshing yards.
They are unsuitable
for use where the grain, prior to threshing and still
attached to the straw or
haulm, is either stored in large compact stacks or on
vehicles during shipment.
The aim of the methods is to estimate the weight of grain
consumed by rodents;
related losses attributable, for example, to contamination,
health hazards,
and damage to sacks must be evaluated by other means.
Personnel and Training
The work, including
all practical operations such as placement, setting, and
checking of traps, should be performed by zoology graduates,
preferably with
some experience in the fields of rodent control, grain
storage, or small mammal
ecology. They must possess or first acquire various skills
in order to carry,
out the following operations competently:
a. Identify the
rodent species, and distinguish adults of the smaller species
from juveniles
of the larger species.
b. Identify and
evaluate signs of rodent infestation.
c. Set traps.
d. Handle live
rodents.
e. Keep field
records of the high standard required for investigative work.
These skills are best acquired on the job under the guidance
of an experienced
specialist. The basics may also be learned in a week or so
of laboratory
and field training at an institution specializing in rodent
control and ecology,
in which case it will be necessary to add a further
self-training period of 2-4
weeks in which to practice and improve the newly acquired
skills in an operational
setting.
Selection of Study Sites
The methods given
in Appendix B should be employed. Frequently it will be
found that appropriate government departments maintain
registers of farms,
premises of licensed grain traders, etc., which can greatly
facilitate selection of
a representative sample of study sites.
METHOD A -- Preliminary Survey of Infestation
A preliminary
survey of the study site must always be made in connection
with the two detailed techniques to be described
subsequently (METHODS B
and C). In addition, a systematic survey of a random sample
of sites can, by
determining the incidence of sites on which rodents are
present and have access
to grain, make a valuable contribution to an overall
assessment of the rodent
problem. It is emphasized, however, that the METHOD A survey
procedure
will lead to a valid estimate of the quantity of grain lost
to rodents only if it is
followed up with either METHOD B or C.
Equipment\N]
1. Electric flashlight/torch.
2. Tracking powder (talcum or finely powdered chalk). A
glass jar with a
perforated lid
provides a convenient means of dispensing the powder.
3. Clipboard and record sheets.
Procedure
Two visits will be
required. On the first visit record the following information
on a record form:
a. Date of survey
b. Address of store
c. Commodities
stored and quantities (by weight)
d. Nominal capacity
of the store (by weight)
e. Date of inward
shipment
f. Expected date of
outward shipment
g. Estimated annual
turnover (by weight)
h. Brief
description of the storage structure and conditions of storage
i. A sketch map of
the store (made on the back of a form) showing important
features and the
location of the stored grain.
Inspect the site
thoroughly for signs of rodent infestation, including burrows,
excreta, smears, footprints, damage to the commodity or
structure, and
places where rodents may enter the store. Record these signs
on the sketch map
as they are found. During the inspection, whether or not
signs of infestation
are found, lay tracking patches approximately 200 x 300 mm
at intervals
along the walls of the store and beside the stacked grain,
especially around
corners. The tracking patches should be laid at the rate of
approximately one
per 50 tons of grain, except that in stores of less than 250
tons, not less than
five patches should be laid. The tracking patches should be
entered in a numbered
sequence on the record sheet and their positions indicated
on the sketch
map.
The second visit
should be made the next day and the presence or absence of
rodent tracks on each tracking patch recorded. Usually it
will also be both
useful and possible to record whether any tracks found were
made by large or
small rodents (rats or mice) or by rodents of both sizes. It
will not normally be
permissible to conclude which species is present until
several trapped specimens
have been identified.
A simple estimate
of the incidence of infestation may be calculated when a
random sample of stores of a single type has been surveyed,
as follows:
Percent of stores
infested = No. of stores infested
---------------------- x 100
No. of stores surveyed
Percent standard
error = [square root](% stores infested x % stores not infested)
-------------------------------------------
No. of stores
surveyed
METHOD B - Trapping to Extinction
In principle, if a
complete census of the population is made by trapping all
the rodents that have access to the grain, then the feeding
capacity of the
population, and hence the current daily grain loss to
rodents, can be estimated
by multiplying the number of rodents by their daily food
requirement, since it
may reasonably be assumed that rodents with access to stored
grain will use it
as their primary food source. The method is suggested for
use in stores with
populations of up to 200 rodents; this would include a fairly
heavily infested
store holding up to 500 tons or larger, more lightly
infested stores. For larger
infestations an alternative technique for population
estimation (METHOD C)
is advocated.
Equipment
The following
equipment is needed in addition to that specified in
METHOD A.
1. 200 snap traps (rat size; striking bar 70-80 mm long).
2. 200 snap traps (mouse size; striking bar 40-50 mm long).
3. Spring balance (100 x 1 g).
4. Spring balance (500 x 5 g).
5. Blackboard chalk for marking trap locations.
6. Bait (see later).
Procedure
First make the
preliminary survey (METHOD A). The objective is next to
trap out the population as rapidly as possible and in a
period not exceeding 21
days; to achieve this, the bulk of the population should be
caught in the first
week. The correct siting of traps is helped by knowledge of
the movement
patterns of the rodents. Much will be known from the
preliminary survey, but
it is essential to increase and update this knowledge while
trapping is in
progress by the temporary placement of extra tracking
patches, which should
be renewed regularly. The tracking patches will also show,
by the absence of
tracks, when all of the rodents have been caught.
A large number of
traps must be used, at least equal to the supposed size of
the rodent population and preferably exceeding it by a
factor of 2 or more.
They should be distributed at intervals of 1 m or less in
all places where the
presence of rodents is suspected. Each investigator should
be able to deal with
about 100 traps daily. Place the traps in a systematic
sequence (called the "trap
round"), numbering and entering each placement on the
record sheet and
chalking up the trap number boldly nearby to make it easy to
locate on
subsequent visits. The bait should be of a sticky
consistency such as peanut
butter, crushed fruit (banana, oil palm pericarp, or melon),
or sweetened
dough, and should be pressed firmly into the bait hook so
that the rodents
cannot simply lift it off but are induced to exert some
lateral or downward
force on the release mechanism while getting the bait.
Succulent baits are often
particularly attractive to rodents in the dry environment of
a grain store and it
may be worth changing the type of bait used after a few
days. The traps should
be set as finely as possible.
Each day check the
trap round and record the species and body weight of
each rodent caught for each trap. Every trap, whether it
makes a capture or
not, must be freshly baited and reset each day and, if
judged to be advisable,
its position adjusted so as to increase the chance of making
a capture. Where
both large and small rodents are present, concentrate first
on trapping the
larger rodents and, as their numbers decrease, gradually
switch to using the
smaller traps.
It may sometimes happen
that though the vast majority of rodents are
trapped, a few recalcitrant individuals evade the efforts
made to capture them.
The size and species composition of this residual
population, provided it is
very small, can often be estimated from the frequency and
size of footprints on
the tracking patches. Such estimates and the evidence on
which they are based
should always be clearly stated.
Grain Loss Assessment
The primary data
which should be reported are the numbers and body
weights of each species of rodent trapped. The data for each
species should be
divided into two body-weight classes: 50 g or less, and more
than 50 g. The
biomass (sum of the body weights) of each weight class
should then be obtained
for each species. The estimate of the daily grain loss
attributable to each
species is obtained by multiplying the biomass of the
rodents in each weight
class by a factor representing the daily grain requirement
of a rodent in that
weight class, and then adding together the two products.
Preferably the
daily grain requirement of each species of rodent in the two
weight classes should be determined (as a proportion of body
weight) for the
commodity and country in question by measuring the actual
amounts consumed
by representative samples of captive rodents in cages. Where
facilities
for this are lacking, however, it will generally be adequate
to base the calculation
on an assumed grain consumption equivalent to 7% of body
weight for
rodents weighing more than 50 g and 15% of body weight for
rodents weighing
50 g or less. The estimated daily grain loss attributable to
species "A," for
example, would then be (0.07a + 0.15b) g, where a = biomass
(g) of rodents
of species A weighing more than 50 g, and b = biomass (g) of
rodents of
species A weighing 50 g or less.
The total estimated
daily grain loss is then readily determined by adding
together the estimates for the different species, and should
be expressed both
as an absolute amount and as percentages of the amount of
grain in the store
and of the nominal capacity of the store. If it can be
assumed that the rodent
population was reasonably stable, then the loss over a
period of time can easily
be calculated. Estimates of the annual loss expressed as
percentages of the
amount of grain actually stored, of the nominal capacity of
the store, and of
turnover are usually of particular interest.
METHOD C - The Lincoln-Petersen Method of Population
Estimation
This method (1) is
based on the following principle: First a sample of animals
is caught alive, marked, and returned to the original
population. When a
second sample is then taken, the number of marked animals in
the second
sample has the same ratio to the total number in the second
sample as the
number of marked animals originally released has to the
total population.
Since both the number of marked animals originally released
and the proportion
of marked animals in the second sample are known, the size
of the total
population can easily be calculated. The application of this
principle to estimating
rodent populations involves making several assumptions about
the
behavior of the populations. In practice the two most
important of these
assumptions are that 1) the duration of the study is
sufficiently short that no
significant change occurs in the population, and 2) the
chance of capturing a
rodent in the second sample is independent of whether or not
it is marked. In
the typical grain storage situation, the first assumption
may be satisfied by
completing the study in a period not exceeding 21 days. The
second assumption
may be satisfied by using live-capture traps for the first
sample and snap
traps to collect the second sample, since the behavioral
responses of rodents to
the two types of trap are relatively independent of one
another.
Equipment
The following equipment is required in
addition to that specified for
METHODS A and B.
1. 100 live-capture traps (rat size).
2. 100 live-capture traps (mouse size).
3. Simple restraining devices to hold live rodents for
marking (see later).
4. 2 pairs of dissecting scissors.
Two types of
live-capture trap are suitable. These are the funnel-type,
multiple-catch trap with a horizontal counter-poised door
operated by the
weight of the rodent as it approaches the holding
compartment, and the single-catch
trap with a door-closing mechanism operated by a treadle.
Live-capture
traps actuated by a bait hook are not recommended.
Live-capture traps for
mice should be made of sheet metal or of 7 mm or finer wire
mesh. Specialist
advice should be taken if there is any doubt about the
suitability of the trap
designs available.
Procedure
First complete the
preliminary survey (METHOD A). The operation is next
carried out in two stages.
Stage 1 lasts 10
days during which the aim should be to capture, mark, and
release as many rodents as possible. Distribute, bait, and
set the live-capture
traps, recording the trap round as in METHOD B. An average
density of one
rat-sized and one mouse-sized trap per 9 [m.sup.2] is
suggested. Fresh bait (eg, soaked
grain or fruit) must be provided daily. One investigator
should be able to
service 50-100 traps. Every morning, each newly caught
rodent must be
marked by clipping off the middle digit of the right hind
foot. To do this, the
rodent should be transferred from the trap to a cloth bag
where it is restrained
gently, while the mouth of the bag is opened to give access
to the foot.
Alternatively, larger rodents may be restrained in a
cylinder or cone made
from chicken wire, while mice may be grasped directly with
the forefinger and
thumb by the loose skin over the neck, either straight from
the trap or after
first transferring them from the trap to a box or bin 500 mm
deep. Newly
marked rodents should be released at the point of capture
and their numbers
and species recorded beside the trap entry on the record
sheet. Previously
marked rodents should be released at the point of capture
without making any
additional record.
Stage 2 also lasts
10 days during which the objective is to snap-trap as many
rodents as possible, using the procedure described under
METHOD B. The
body weight, species, and presence or absence of a mark
should be recorded
for each rodent trapped. In accordance with conditions, a
lower trap density
may be permissible; however, for the purpose of making
satisfactory population
estimates it is desirable to recover at least 20 marked
rodents of each
species in Stage 2.
Population Estimates and Grain Loss Assessment
The primary data
which should be reported are:
* The numbers of
each species marked in Stage 1.
* The numbers of
marked rodents of each species trapped in Stage 2.
* The numbers of
unmarked rodents of each species trapped in Stage 2.
* The species and
body weight of each rodent trapped in Stage 2.
* The population
estimate (P) for each species as P = an/r where a =
number marked in
Stage 1, n = total number caught in Stage 2, and r =
number of marked
rodents caught in Stage 2.
The estimate of
daily grain consumption is obtained as before, except that it
is necessary to determine the weights and relative sizes of
the two body-weight
classes by reference to the sample of rodents trapped in
Stage 2. Thus, where in
the absence of data from captive rodents it is assumed that
the daily grain
consumption figures for animals greater than 50 g and for
smaller rodents are
respectively 7 and 15% of body weight, the daily grain loss
attributable to
species A will be:
P [0.07ab + 0. 15 (1 - a) c] g
where P = the population estimate for species A,
a = the proportion
of rodents of species A of body weight greater
than 50 g,
b = the mean
body weight (g) of rodents of species A weighing
more than
50 g, and
c = the mean
body, weight (g) of rodents of species A weighing 50 g
or less.
(The parameters a, b, and c must be calculated from the
sample trapped in
Stage 2.
If the population
estimate, P, is unsatisfactory owing to fewer than 20
marked rodents of the species concerned having been trapped
in Stage 2, then
the data for two or more species may be pooled to give a
combined estimate.
The estimate of total daily grain loss should be expressed
in the various ways
suggested under METHOD B.
Literature Cited
1. LE CREN, E. D. A note on the history of mark-capture
population estimates. J. Anim. Ecol.
34: 453 (1965).
CHAPTER VI
E.
Measurement of Losses Caused by Birds (8)This
brief summary was excerpted and added to by K. L. Harris
from Estimates
of Bird Depredations to Agricultural Crops and Stored
Products by W. B. Jackson
and S. S. Jackson, first presented at the Colloquium on Crop
Protection Against
Starlings, Pigeons, and Sparrows, European and Mediterranean
Plant Protection
Organization, Jouy-en-Josas, France, Oct. 18-20, 1977.)
This section
recognizes that there is scarcely any line between grain held in
the field for maturing and drying and grain held for
maturing, drying, and
storage. The storage portion of the cycle is intertwined
with both the drying
and holding requirements. At times grain, chiefly maize,
sorghum, and millet,
may be held for extended periods in the field prior to
harvesting for storage or
direct to the table use. Some of the most serious grain
losses occur at this stage
when losses to Quelea spp., parakeets, and blackbirds have
assumed disastrous
proportions; however, losses are rarely quantified.
It is often
difficult to relate specific birds to designated damage or losses.
Feeding patterns may be irregular or overtap; insect
outbreaks, drought, or
flood may alter expected patterns; fungi may enter as a
secondary factor
related to bird damage; and the measurement techniques,
themselves, may be
tedious and exacting. Comparisons of damage to benefits,
whether off-season
removal of weed seeds compensates for food losses, effects
of intensive mono-culture,
the mutually destructive breakage or cutting of heads by
mammals
and birds, and other matters all complicate loss
assessments. Losses to piled
and bagged grain are often observed but rarely if ever
quantified, and birds are
usually more readily accepted than rodents as part of the
environment.
While losses are
real, satisfactory methods of determining losses have seldom
been available or used. The most intensive statistical
efforts have been on
blackbird damage in the United States. These have used the
detailed row-centimeter
measurement technique and visual-toss estimates as
summarized
below:
Row-Centimeter
Measurements (used on maize). The number of damaged
and undamaged ears in a row (15-100 ft) are counted. On
damaged ears, the
average lengths of damaged and undamaged kernel rows are
measured to the
nearest, approximately, 2 or 3 mm. These lengths are
converted to losses per
area, eg, tons/hectare. Less exacting are simple
measurements of the portion
of ear damaged, which may require some arbitrary averaging
if the damage
pattern is not symmetrical.
Visual-Loss
Estimates. This technique is usable on many different crops,
but observers must be trained and their procedures
calibrated for each crop.
This is a much more rapid technique, since counting is not
specifically required.
Damage-level criteria (5, 10, 20, 40%) are established and
workers
trained by repeated tests to distinguish visually between
these levels of
damage/loss.
Losses to stored
bagged or bulk grain can best be measured by before and
after weights over a period of time. The kinds and numbers
of birds and how
much time they spend on the grain should be noted. These
figures can then be
used in estimating losses in similar situations elsewhere.
CHAPTER VI
F. Moisture Measurement
T. A.
Granovsky, G. Martin, and J. L. Multon
Accurate
measurement of grain moisture and its variations is critical for
proper assessment of weight losses during storage. Changes
in moisture content
are accompanied by changes in weight and volume and need to
be recognized
as separate from actual grain losses. Frequently, the weight
of moisture
gained or lost by grain may exceed weight losses induced by
insects, rodents,
birds, or fungi. Moisture changes are merely the gain or
loss of water; the
others may alter food quantities or qualities. Therefore,
measuring the moisture
content of grain is an extremely important operation from
three standpoints:
1) Technology:
Knowledge of moisture content is needed to efficiently determine
and manage the harvesting, drying, stocking, and processing
operations.
it is also essential for assessing and controlling
postharvest losses insofar
as the action of water governs deterioration phenomena.
2) Analysis: To
compare the results of analysis with a fixed basis (dry
matter or standard moisture content). In particular,
assessing the weight of a
stock of grain and making loss determinations requires
accurate knowledge of
the moisture content.
3) Marketing:
Commercial purchasing and sales contracts often stipulate an
upper limit for the moisture content not to be exceeded.
Samples should be
analyzed as soon after being obtained as is practical.
Since grain can gain or lose moisture rapidly, all samples
not immediately
tested should be retained in air- and moisture-tight
containers and not exposed
to undue temperature variations.
It is necessary to
emphasize how important it is for all measurements to be
made with thoroughly standardized procedures. The
International Association
for Cereal Chemistry has called attention to various
procedures for measuring
moisture content.
Moisture
measurements depend on two fundamental baseline procedures.
These procedures determine what water shall be classified as
free moisture in
the grain and, hence, is the water that is dealt with in a
percentage moisture
determination and will be the basis of the reading given by
a moisture meter.
Table V summarizes international approval of the two types
of baseline
pgl4x120.gif (600x600)
methods.
An in-depth
discussion of the comparative values of the "fundamental reference
methods" versus the "practical reference
methods" is not within the
scope of this manual. They do, however, involve highly
specialized apparatus
and conditions (see ICC standards in Table V).
Use of Meters (See also Appendix C)
The amount of grain
necessary for determining moisture content will depend
on the testing method used. Some methods are portable and
enable
determinations in the field. Other methods are
laboratory-based and may
require a constant power supply and chemical agents.
Selection of a meter will
depend on where the determinations are to be made. In
general, use of a
moisture meter is encouraged, especially one which is both
portable, enabling
on-the-spot moisture determinations, and rugged enough to
withstand transport
from locale to locale. Aspects of proper adjustments and
sensitivities of
each meter should also be considered when making a
selection. The data in
Appendix C are pertinent in deciding what meter an
investigator will select,
amount of grain needed, speed of operation, and accuracy of
each. In any
case, manufacturer's directions in using the meter should be
followed.
Moisture meters
require periodic calibration, the frequency of which will
depend on the meter and conditions of its use. Often it can
be checked against
samples especially prepared and packaged for this purpose.
In other cases, it
may be taken to a central laboratory for comparisons with a
meter reserved for
this purpose, for comparison with control samples, or for
comparisons with
results by standard oven-dry methods. To re-set,
manufacturer's directions
should be followed.
As a general rule,
all field or laboratory determinations should include at
least three and preferably five replicates in an effort
toward greater validity.
Consistency in handling and preparation of samples for
moisture content
determinations is indispensable.
The percentage loss
or gain in weight by the grain may be derived from the
average initial and average final moisture contents. The
nomograph (Fig. 10) is
pglx121.gif (600x600)
employed as follows:
1. Lay a straight
edge so that the initial and final moisture content values lie
along this edge.
2. Read the
percentage gain or loss in weight off the right-hand bar.
For instance, if
the initial moisture content of a sample is 12.5% and the
final moisture content value obtained is 16.5%, then the
percentage weight
gain is about 4.8% (represented by dots). Conversely, if the
initial value is
20% and the final value only 150/o, then a 5.9% weight loss
has been realized
(represented by dashes).
VII. OPERATIONS
STANDARDIZATION AND CONTROL
A.
Handling of Samples in the Laboratory
T. A. Granovsky
When a sample
arrives in the laboratory from the field, it should be in a
sealed moisture-proof container and at ambient laboratory
temperature when
opened. This will require proper preparation and care of
samples in transport,
field to laboratory, in addition to prompt attention upon
arrival by the laboratory
staff.
During handling in
the laboratory, each sample must retain its identity as to
location, data collected in the field, grain type, variety,
and time in storage at
all times.
As each sample
enters the laboratory, it should be handled as per the sample
flow and by the procedures indicated below:
Sample Flow
If Moisture Content was Determined in the Field
1. Sample enters
laboratory.
2. Sample
collection data recorded on laboratory data sheet.
3. Whole sample
weighed (grain, dust, insects, dockage).
4. Grain sieved:
insects are recovered and placed in 70% alcohol; dust is
weighed, if necessary, and discarded.
5. Weight-to-volume
vessel properly filled and weighed.
6. Grain from
weight-to-volume vessel recombined with rest of original
field sample, repeated five times, and averaged.
7. Sample (1 kg) is
divided into a series of 8-32 subsamples.
8. Five subsamples
are randomly selected for tests on losses induced by
insects as per other instructions (see Section B, Chap. VI).
9. Other subsamples
may be used as needed in tests on losses induced by
microorganisms/respiration, aflatoxin, etc.
10. All data
derived during loss analysis should be recorded on the data
record sheet (Fig. 11).
pglx1240.gif (600x600)
If Moisture Content is to be Determined in the Laboratory
1. Steps 1 to 5 are
as above, but after weight of the weight-to-volume vessel
has been recorded, the moisture content is determined before
the sample is
recombined with the rest of the original field sample.
Weighings and moisure
content determinations are repeated three times each and
averaged separately.
Steps 7 to 9 are then finished.
2. The total weight
of grain, dust, insects, and dockage should be determined
for the whole sample as it arrives from the field. This
figure, and all
subsequent data, should be recorded on separate data record
sheets for each
sample. A suggested partial sample sheet for data derived in
the laboratory is
presented in Fig. 11.
3. The grain is
then sieved to separate off insects and dust (depending on the
characteristics of the debris, use No. 10 or No. 25 sieve
and solid botton pan).
Insects should be placed into bottles containing 70%
alcohol, labeled as to
origin, and identified as required.
4. The
weight-to-volume vessel, Fig. 8, should be properly loaded, filled,
pgl8x86.gif (600x600)
sliced, and weighed. This is repeated five times and a mean
is taken. After each
weighing, the grain should be recombined with the original
field sample and
remixed before another sample is removed (see Section B,
Chap. VI).
5. The 1-kg sample
is divided into 8-32 subsamples by using a recognized
method such as a sample divider or by coning and quartering
(Appendix A). It
is suggested that the subsamples be placed into individual
pre-marked containers
to facilitate their manipulation. As noted in Appendix A,
subsamples
may vary somewhat in size (number and weight of kernels)
depending on the
commodity and the conditions under which the grain was
produced.
6. Five subsamples
(replicates) are then selected at random for subsequent
tests on losses induced by insects. See Section B, Chap. VI,
for measurements
of losses caused by insects.
7. Other samples
may be used as needed in tests on losses induced by
microorganisms/respiration, aflatoxin, etc.
8. All data derived
during loss analysis induced by insects, microorganisms/
respiration, rodents, birds, and physical losses should be
recorded on the data
record sheet (Fig. 11).
CHAPTER VII
B.
Operations Manuals and Laboratory Records
T.
A. Granovsky and K. L. Harris
In the conduct of
any survey there is absolute need for an operations manual
that describes how the survey is to be managed to ensure
that the purposes of
the project will be performed. Operations manuals can be in
any useful format,
but should specify duties of each employee and operation. Such
a manual
is designed for internal use by operating personnel.
Depending on the
complexity of the operation, the manual may be divided
into subsections for on-the-spot use in specific operations.
If an operation is
large enough to involve a payroll, there should be a
division under corresponding
functional headings for the purchase of supplies, travel,
field observations
and sampling, laboratory analyses, and reporting and
tabulating results.
A complete
compendium of what to include in an operations manual is
beyond the scope of this work; however, guidance for a field
and laboratory
operations manual is given below:
It is imperative
that all procedures for information-gathering, sample collection
and transport, sample examination and reporting, and
collection and
tabulation of results be tested in dry runs before the
actual information gathering
gets under way. This period of preparation is used to give a
final assessment
of the quality of the written directions, on training or the
need for
additional training, and on the suitability of individual
people, procedures,
and forms for the job. Make changes as required.
Field Controls
1. Once the sample
collection and field observation sites, system, and criteria
are established, these same parameters need to be recorded
on paper in
terms suitable for the user.
2. Sample
collection should be explicitly set forth as to where, when, and
how -- with no room for deviation.
3. Use of
alternative procedures, when permitted or applicable, reporting of
inability to sample or make observations, reporting of
broken containers, lost
samples, and miscounts all need to be explicitly detailed.
4. There need to be
observation reporting forms, sample collection forms
and labels, packaging and shipping forms, and supplies where
required.
5. Triers (see
Appendix A) and other technical devices and supplies need to
be provided (bags, preservatives, clasps) and their use
completely described
(see below).
6. Where, when,
how, and how much sample is taken needs to be explicitly
set forth. How to operate triers, how much preservative is
to be added, how to
get samples to the laboratory, and speed and route of sample
shipments must
be established, set down on paper, and controlled.
7. Use of moisture
meters, scales, or balances and any special devices needs
to be explained stepwise in complete detail, as well as
their care and maintenance
and checking for malfunction.
8. All reports of
all observations and collections are to be on pre-numbered
forms or in numbered-page notebooks furnished by the
project. All entries
should be original and in ink or ballpoint pen with no
erasures or data-recording
on other slips of paper. All pre-numbered pages and forms
must be
accounted for with no forms discarded.
9. All entries are
to be made directly into the notebook as each measurement
is made. Supervisors should check on this immediately upon
arriving for
v a surveillance visit.
10. Any confusion,
or lost or broken sample, should be reported to the
immediate supervisor without fear of reprisal or penalty.
11. Suggested data
record forms are presented in the following figures: Fig. 12,
pglx130.gif (600x600)
a sample field observation form; Fig. 13, a sample
collection form; and
pglx131.gif (600x600)
Fig. 11, a sample field/laboratory data sheet for maize.
12. Supervisory
field controls require careful monitoring by several varied
techniques, such as scheduled and unscheduled supervisory
visits, discussions
with various employees and subjects being investigated, and
comparisons with
automobile logs and daily expense logs and diaries. These
techniques can be
part of the supervisory operations manual and can be kept as
checklists.
Laboratory Controls
1. Once the sample
analysis procedures are established, they need to be
recorded on paper in terms suitable for the user.
2. Analytical
techniques must be followed to the letter. No alternative procedures
are permitted unless expressly authorized in the operations
manual.
3. All needed
equipment must be provided and maintained in working order
using a recorded maintenance and calibration record.
4. All reports of
all tests are to be on numbered forms or in numbered-page
notebooks furnished by the project. All entries should be
original and in ink or
ballpoint pen with no erasures or data-recording on other
slips of paper. All
pre-numbered pages and forms must be accounted for with no
forms discarded.
5. All entries are
to be made on-the-spot as the results are obtained. Supervisors
should monitor this very carefully.
6. Any confusion,
mistake, mixup, lost sample, damaged container or sample,
or spoiled sample should be reported to the immediate
supervisor without
fear of reprisal or penalty.
7. Figure 11 is a
sample reporting form.
8. Analytical
controls require careful monitoring by several varied techniques,
such as scheduled and unscheduled supervisory visits,
generally observing
operations if the analyses are being done close to
headquarters, and
comparisons with daily logs and diaries. A supervisor should
know the analytical
procedures. By watching the operator, the supervisor will
form a dependable
judgment as to the analyst's expertise and working habits.
9. Analytical
operations require the use of internal controls, such as seeded,
or pre-set, standardized control samples sent through the
analytical procedures
with or without the analyst's knowledge, duplicate samples
analyzed at different
times by different analysts, and supervisors who can check
or repeat grain
separations and other analyses.
10. All instruments
require regular calibration, especially moisture meters
and balances for grain loss work.
(a) Moisture meters
usually can be calibrated against a standardized meter
in a national
or international institute. Standardized held-in-glass or
otherwise
sealed samples may be obtained from well-known institutions
for use in
calibration. For periodic use this is more practical than using
oven-drying
moisture determinations.
(b) Balances and
scales need to be checked against a special set of weights of
known value.
Frequency of checking depends on accuracy requirements
and the usage
to which the balance is subjected.
Reporting Results
1. All results
should be on numbered forms or in numbered-page bound
notebooks.
2. Results should
be submitted on a regular basis, and should be checked
and otherwise followed as the work proceeds. To allow them
to accumulate for
an end-of-project or delayed review is to lose an
opportunity to find and
contain sources of error.
3. Decisions on
interim reports and keeping the staff informed of the data
need to be resolved on an individual project and person
basis. In some cases,
being aware of what is happening and working toward overall
goals will maintain
and improve work equality, although it could introduce bias.
4. Standard
terminology of weight loss should be followed. This manual
recommends:
ow - cw/ow x
100 = % loss
where ow = original, weight on a dry weight basis,
cw = current or
final weight on a dry weight basis.
Other formulas,
such as those in Chapter VI, Section B, where direct differences
cannot be calculated, may have to be substituted.
VIII. APPLICATION AND
INTERPRETATION OF RESULTS
A. The Chronological Approach:
Losses as Reflected by Use Patterns
J. M. Adams
In making grain
loss estimations, it is important to relate losses to the
pattern of grain consumption. If grain is left untouched
throughout the storage
period, the total loss over the season can be obtained by
accurately
weighing all the grain in and out of the store and comparing
the totals. This
does not, however, indicate the relation between loss and
time, ie, when the
loss reached a peak or whether it was related to a
particular part of the season.
If at the time of removal the estimated loss is 10%, then
this represents the
total loss over the storage period. In most cases, however,
grain is removed at
intervals during the storage period and each quantity
removed will have been
exposed to deterioration for a different length of time and
will have suffered a
different degree of loss.
If a measurement of
the quantity removed is available, then estimates from
samples covering the removal period and pattern may serve to
cross check with
the total loss as well as showing the pattern of loss.
If, as often
happens on subsistence farms, the amount removed is quoted in
volume terms (eg, tins), then the volume removed will be the
same whether or
not the grain is damaged but the weight will be different.
In this case, the
weight of grain that occupies the farmer's measure should be
recorded carefully
at the beginning of the storage period. For each subsequent
removal of
grain, this weight can be reduced by the percentage of loss
estimated from the
appropriate sample. If samples are taken at monthly
intervals and the dates of
removals are known, an approximation can be made by applying
the estimated
loss to removals two weeks either side of the sampling date.
To obtain the total
loss, all individual losses can be summed.
Where removals are
roughly estimated, the loss may be obtained by calculating
the percentage of the total quantity stored which was
removed at each
sampling date and applying the percentage loss to this. The
resulting losses are
then summed to produce an overall percentage loss, as in
Table VI.
When stored grain
is regularly removed for household use, weight loss may
be measured by taking, or having the user set aside, a
sample from, or taken at
the same time as, the portion withdrawn for use. The
household may be
provided with an equivalent amount of grain in exchange for
the test samples.
TABLE VI
Relation Between Weight Loss and Consumption
Months in Store
1 2
3 4
5
6 7
8
Quantity
removed, %
10 10
10
10 10
10
15 25
Weight loss
in sample, %
1 2
3 5
8
12 18
25
Weight loss as %
of total stored
0.1 0.2
0.3
0.5 0.8
1.2
2.7 6.25
Cumulative weight
loss as % of
total
0.1 0.3
0.6
1.1 1.9
3.1
5.8 12.05
This is an actual
use-weighted loss of 12.05% compared with a loss of 25%
(as measured in month 8 of Table VI) if only a single, final
visit had been made
and there was no allowance made for consumption (see Fig.
14). Line A of the
pglx136.gif (600x600)
top of Fig. 14 represents a farmer who holds a quantity of
grain in store for
sale when the price is high and does not remove any until
the date of sale, when
the store is completely emptied. Line B represents a
subsistence farmer who
regularly removed grain from the store for family
consumption. The total loss
in weight suffered in case B is considerably reduced because
a decreasing
proportion of his total stored grain is exposed as the level
of loss increases with
time.
The same procedure
may be adopted in relation to nutritional loss, bearing
in mind that damage may cause greater losses in preparation
of food where
soaking of the grain is involved. It may also be used to
evaluate quality loss in
terms of money. For seed grain, the loss is the drop in
germination from the
time of storage to the date the seed is required and is
simply the difference
between the percentage germination recorded on the two
dates.
CHAPTER VIII
B. Losses and the Economist
M. Greeley and G. W. Harman
Definition
To the economist,
storage losses refer to changes in the value of grain which
occur as a result of any physical change while it is in
store. Alterations involving
biological changes normally reduce its value and thus
involve an economic
cost. Losses may also occur during marketing and, to the
extent that waste and
unintended physical alterations take place, during the
primary processing of
grain.
Setting Terms of Reference
The economist
evaluates loss by assessing the cost or sacrifice borne as a
result of its occurrence. Since losses can occur at various
points in the marketing
pipeline and will, if significant, have consequences for
individual stores-owners
and consumers, merchants, marketing boards, etc., and to the
country
as a whole, it is essential to define from whose viewpoint
the assessment is to
be made. In this guide, concentration is centered on the
consequences of losses
for stores-owners at farm level in developing countries.
An attempt should
be made to approximate the magnitude of the value of
losses before time is spent on trying to reduce them. If
this value proves to be
low, expenditure of appreciable resources on reducing losses
may not be justified.
Even when it is established that losses are sizable,
consideration should be
given to the relative desirability of their reduction
compared to alternative
investments. If the purpose is to increase the quantity and
quality of grain
available to users, there may be other more practical and
cost effective ways of
achieving this end. Examples of possible alternatives to
improving storage are
measures to stimulate the use of fertilizer to increase
production of grain and
changes in the marketing system to encourage stores-owners
to store less by
making grain/flour available for their purpose at a fixed
price throughout the
storage season. On the other hand, there are situations
where no alternatives
are available, and food lost equals people starved. These
situations are difficult
to resolve on an economic basis.
In assessing the
practicability of improving storage, it is essential to have the
improvement tested by stores-owners since this may reveal
unanticipated problems.
One important aspect of this testing will be to determine if
storage
owners are sufficiently motivated to undertake improvements
in their storage
methods. Factors affecting acceptability and utility of
storage improvements
are not all predictably quantifiable and require practical
testing before their
benefits can be accurately assessed. National priorities may
meet individual
needs and vice versa. Distribution of potential benefits
should also be taken
into account since these will vary appreciably according to
the type of improvement
proposed and the point in the marketing pipeline at which it
is
made.
Nature of Losses
The physical
alteration and diminution of grain in store will affect its weight
or quality. Both changes will alter its value and should be
assessed separately.
Change to the nutritional worth of grain may be regarded as
a particular type
of quality loss. Such losses are only relevant to the owner
if they affect the
price of grain that is sold or are of sufficient size to
reduce the value of grain in
other ways. An example is a reduction in an owner's capacity
to work which
may occur through eating grain which has suffered a
nutritional loss.
Losses may involve
other economic costs by necessitating expenditure to
reduce them and by affecting the timing and, therefore, the
price of grain that
is sold. Major factors influencing the economic consequences
of loss are:
scarcity of grain, the extent of seasonal price
fluctuations, the time at which
the impact of loss is felt, the proportion of a crop that is
stored, the extent of
the premium on better quality grain, and the opportunities
for using damaged
grain in other ways.
Collection of Data
The objectives of
data collection are to ascertain, by examining the behavior
of procurers, handlers, and stores-owners, the consequences
of losses incurred
by them; and, if the level of losses justifies changes in
the system of storage, to
assess the likely costs and benefits of such changes.
The exact nature
and amount of information to be collected will depend on
the circumstances in each situation and the time at the
researcher's disposal.
The basic minimum data necessary for reliable evaluation are
as follows:
1. Use of stored
grain, preferably throughout the whole storage season
* amount consumed
by stores-owner and his dependents
* amount sold;
price obtained
* amount used for
other purposes such as for seed, feedingstuffs, making
beer, payment of
wages
In obtaining these
data, attention should be given to the reasons for usage at
a particular time, interrelations between usage and type of
store, effects of a
stores-owner having more/less grain available, influence of
the variety/type of
grain on its use, and the effect of varying degrees of
physical damage on usage.
If regular visits are not being made to an owner, data will
need to be collected
on the time at which grain from the store was exhausted and
the consequences
of this for the owner. In examining usage, grain sales to
any marketing authority
should be distinguished from those at village level since
the price received
will probably be different.
In addition to the
amounts of grain used in various ways, the pattern of
usage should also be noted in relation to other stores which
the owner may
possess. For example, is grain taken out of one store until
empty or is it taken
out of more than one? Why?
2. The marketing
system
* method of
operation
* factors
determining prices received, particularly timing of sale and
quality of
grain (including any statutory regulations applicable)
* influence of
variety/type of grain
3. Behavior of
stores-owners
* motivation for
growing grain
* degree of
knowledge of losses
* measures (if
any) taken to eliminate loss
* capability and
motivation for adopting any suggested improvements
in storage
* work
undertaken off farm; its nature, timing, and remuneration, ie,
is the store
the major source of food grains?
4. Stores/storage
practices (existing and as would occur when suggested
improvements are included)
* materials used
in construction, quantity and price
* time taken to
collect materials and build or improve the store
* season at
which constructed and alternative work at that time (on and
off farm)
* expected life
of improved or traditional store
* insecticides used, quantity and price
5. General
* purchases of
grain, reason, timing, amounts, prices
* type/variety
of grain grown/stored
* cost of seed
Methods of Collecting Data
* published
reports and economic data
* discussions
with those having detailed knowledge of the behavior and
practices of
stores-owners
* questionnaire
surveys.
Training of field
staff who will be conducting, or assisting in conducting,
questionnaire surveys should receive close attention to
ensure that they thoroughly
understand the questions to be asked and the reasons for
them.((9) This matter
was debated at Slough and no real consensus obtained. Some
felt that information gatherers should not understand their
questions
and that the most reliable information was obtained when
information was
gathered in a fixed mechanical manner.) If at
all possible, all field staff should be accompanied on
initial visits, and periodically
thereafter, to ensure that questions are put without bias.
Questionnaires
should be tested experimentally on a sample of participants
before a complete
survey is made so that misunderstood questions can be
rephrased or removed.
Use of Data in Evaluating Losses
1. Weight Loss
The value is
obtained by pricing the weight loss according to the use to
which the lost grain would have been put and the effect of
its loss on the
stores-owner. For example, if the grain would have been
consumed by the
owner, its replacement cost as food would normally be used;
similarly, if sold,
its sale price, and, if used for seed, its cost of
replacement.
2. Quality Loss
This may be
assessed by adopting a standard of quality and measuring loss
as the difference between this standard and that of the
grain in the store. The
relevant standard will depend on the intended use of the
grain but often it will
be that set by a marketing authority. If no such authority
exists, an attempt
must be made to examine how the grain usage is affected (if
at all) by the
existence of differing qualities. The standard which affects
its usage should
then be adopted.
The economic cost
of the quality loss will be represented by:
Lq =
[V.sub.s] - [V.sub.a]
where Lq =
value of quality loss,
[V.sub.s] =
value of grain if it was all of a standard set,
[V.sub.a] =
value of the quality of the grain in store when used.
Quality loss of
grain intended to be used as seed is especially serious. If the
stores-owner does not realize that it is damaged, it may be
planted and result in
a lower rate of germination. This loss is assessed as the
difference between the
value of the crop expected from the undamaged seed and that
which would be
produced from the damaged seed.
3. Indirect Loss
This is the cost of
any insecticide or other treatment used by the stores-owner
to minimize his losses.
4. Nutritional Loss
This can be valued
in the same way as quality loss by adoption of a standard.
Since this method is liable to a high degree of
subjectivity, the reasons
for using a particular standard need to be clearly stated.
In some cases, nutritional
loss will not reduce the economic value of grain to an
owner; for
example, it may not, taken by itself, necessarily reduce its
sale price.
5. Other Losses
Stores-owners may
suffer other economic costs due to losses, but the valuation
of these will be specific to particular circumstances and it
is not possible to
provide more than the general principles of valuation
already outlined.
Further Points to Note on Evaluation
1. Valuation should
be based on the time when the impact of loss is felt by
the owner. This will not necessarily be at the time when the
loss occurs. This
factor will be of particular importance in cases when the
price of grain fluctuates
appreciably during a storage season.
2. In arriving at a
final loss figure, the value of damaged grain in any
alternative or secondary use should be considered. For
example, if grain intended
for human consumption was damaged and, therefore, used to
feed
cattle, the loss suffered by the stores-owner would be:
Ln = Lf
- Lc
where Ln = net loss,
Lf = value as
food,
Lc = value as
feedingstuff.
Summation of the
different types of economic costs occurring as a result of
physical loss will provide an estimate of the total economic
impact of losses.
Such estimates should be related to the "wealth"
of the stores-owners concerned
since losses of the same value will affect poorer
stores-owners to a
greater extent. In this respect, care should be taken in
quoting average values.
Use of Data in Assessing Improved Method(s) of Storage
The benefits of a
system of storage are assessed by a comparison of the costs
involved with its output as measured by a valuation of grain
leaving the store.
Improved storage may be reflected by a reduction both in
weight and in quality
losses per unit of storage cost. The value of any additional
amounts of grain
made available by a reduction in weight loss should be based
on the use to
which this extra grain would be put. The value of the
reduction in quality
losses is obtained by grading grain stored in both the
normal and improved
manner as it leaves the store using a common standard. The
amount of qualitative
benefit will be:
Qb =
Vi - Vu
where Qb = qualitative benefit,
Vi = total
value of grain leaving improved store,
Vu = total
value of grain leaving unimproved store.
In assessing the
reduction both in weight and in quality losses, it is necessary
to ascertain the level of these before improvements in
storage are made. Care
should be taken that the figures obtained are representative
since there may
exist appreciable variation between different seasons and
stores. The costs
involved in adopting a particular system of storage may be
divided into those
of materials and labor used in constructing the store and of
any treatments
applied to the grain. The cost of any purchased inputs,
including labor, will be
the actual amount paid. Any time spent by the stores-owner
or his family on
constructing the store or treating the grain should be
priced at a theoretical or
imputed wage rate. The rate used will normally reflect the
wage being offered
in a type of occupation similar to that in which the
stores-owner is engaged.
This rate should be taken only as a general guideline. The
objective in using
any particular one is to express the cost (if any) to the
owner of the time which
he and his family spends on storage by the value of the time
given up on its
alternative use. In some cases, materials used to build a
store will not be
purchased but gathered from fields or woods. The cost of
these free goods in
evaluation should be that of the time spent in obtaining
them.
In assessing the
cost of time, attention should be given to the seasonal
pattern of agricultural activity and also to the fact that
the value of time at a
particular period may differ between different stores-owners
according to the
amount of land and labor at their disposal.
The three main
methods of relating costs of benefits are by means of a ratio
(cost-benefit ratio), a rate of return, or by comparing the
additional benefits
from taking a particular action with the additional costs
incurred. The last of
these approaches is particularly suitable where the changes
to an existing system
of storage are relatively small. The rate of return concept
is more suited to
situations in which changes to the system of storage is
extensive and sizable
capital investments are involved. Where the rate of return
concept is used, the
value of grain removed from a store will be expressed as a
percentage of the
store's cost. Finally, but importantly, if benefits gained
over a period of years
are being compared with costs incurred at a point in time,
they must be
discounted using a suitable rate of interest. The spread of
benefits within the
total period is a significant factor in this procedure.
CHAPTER VIII
C. Conversion into Monetary Values
E. Reusse
After having been
physically and quantitatively assessed, food losses have to
be expressed in monetary terms. This is necessary to
establish a common
denominator for cost-benefit analysis, in which cost
(investment in potential
improvement measures) and benefits (expected reduction of
food losses) can
be weighed against one another.
Thus, if a farmer
can reduce his storage loss from 8 to 4% by means of
fumigation, and the fumigant plus amortization of plastic
sheetings amount to
$3 per 500 g, then 1 kg of grain must be worth more than 15
cents to warrant
the investment. If a rice miller can raise the extraction
rate of paddy rice from
63 to 66% by additional installations (including rubber
rollers) and additional
controls by qualified technicians, together increasing
milling cost from $2 to
$2.50 per 100 kg, then 1 kg of rice must be worth more than
17 cents to make
the improvement financially feasible. While the financial
value of the rice to
the miller might be only 15 cents per kg, the economic value
for the national
economy of the country concerned may be much higher, as it
is when the rice
gained through the advanced milling technique can serve the
substitution of
imports, thereby freeing valuable foreign exchange.
The question is how
to determine the value of a unit weight of grain. The
financial value can be one value for the individual
innovator (the farmer,
trader, or processor, whether private, cooperative, or state
enterprise) and a
differing economic value for the economy as a whole. The
viewpoint from the
individual enterprise sphere is also referred to as the
micro-economic consideration,
as opposed to the macro-economic one taken from the
viewpoint of the
national economy.
Food losses occur
principally at three different levels: farm, wholesale and
processing, and retail. These levels are linked by
transport. The gains in time-,
form-, and place-utility added to the food product at and
between the various
levels, carrying those essential inputs as storage,
transportation, processing,
packaging, financing, risk-bearing, and logistics decisions,
add value to it. The
cumulative value added in the postharvest system for
storable food crops in
developing countries generally amounts to between 50 and
100% of production
cost, depending on distribution radius and degree of
processing involved.
In a competitive
marketing system, the value added is reflected in the market
price received for the food product at the various levels of
the process. A
typical postharvest cost-price structure for rice might be
as shown on the chart
on the following page.
It follows that the
physical loss of 1 kg of rice in the form of paddy occurring
at the farm level in financial terms represents only 57% of
the loss of the
same quantity of rice, after milling, at urban retail level.
It is, therefore, vital
to value a food loss at the farm gate or market price
prevailing for that stage of
processing and for that geographical area where it occurs.
For transport-inflicted
losses, the market price at point of destination would apply;
for
milling losses, the price for the milled product would
apply.
Cost per kg
Cost per kg
paddy
milled rice
(at 66%
ext.
rate)
farm gate
value 10
+ transport
1
--
rural assembly
market value 11
+ bagging,
transportation, etc. 1.5
----
provincial market
value 12.5
+ milling
cost 1.5
----
milled rice (in
terms of paddy) (14.0)
21
+ bagging,
transportation, etc. ( 1.6)
2.4
----
----
urban wholesale
market value (15.6)
23.4
+ packing and
other retail cost ( 1.8)
2.7
----
----
urban retail market
value (17.4)
26.1
urban retail market
price ...
27
Since market and
farm gate prices are subject to seasonal fluctuations, when
working at a national level, annual average prices should be
used. To eliminate
abnormal annual crop situations, the average over the past
three years may
best be taken. An inflation factor, however, should be
added, if necessary,
since implementation of any remedial measures will usually
be delayed.
So far we have
discussed the financial valuation of food losses typical for
micro-economic consideration; let us now look at a few major
situations where
under macro-economic consideration the financial,
price-based valuation has
to be corrected or substituted by an economic valuation. As
the examples will
show, these situations typically arise because of government
intervention in the
price structure:
1. The situation of
subsidized producer or consumer prices
a. Subsidized
producer (farm gate) prices: for economic valuation the
subsidy
element has to be eliminated (downward correction of financial
values).
b. Subsidized
consumer prices: same applies, but upward correction of
financial
values.
2. Overstated
official foreign exchange rate of national currency: In such
situation domestic price development lacks close correlation
to world market
prices. This fact has little relevance in a closed food
economy, ie, where the
country is neither a regular exporter nor importer of the
staple food crops
(products) in question. In an open food economy, however,
where food losses
are affecting the foreign exchange intensive marginal area
of export surplus or
import substitution, those losses have to be valued at the
average annual FOB
export or CIF import price, respectively, under application
of a shadow rate of
the foreign exchange involved in converting to national
currency values,
shadow rate being understood as the rate expected to prevail
under conditions
of free floating exchange rates. The FOB or CIF value thus
established in
national currency has to be deflated by the transportation
cost between the
geographical area where the field losses are occurring and
the seaport. This
would include the simplifying assumption that, in most
developing countries,
consumption of imported staple foods is concentrated in
geographical areas
near ports of importation.
3. A shifting area
between financial and economic valuation is entered
when food losses in government reserve stock and price
stabilization schemes
have to be valued. Since the selling price of those stocks
in most cases is related
neither to market value nor internal cost price calculation,
the value applied to
stock losses should at minimum reflect the full unit cost of
operation, including
accumulated storage cost over the recycling period which may
extend over
two to three years.
APPENDIX A
SAMPLING GRAIN
1.
Comments on Probing Techniques and Probes
a. In this volume
the terms trier, probe, thief, and spear are used interchangeably.
b. A compartmented
grain trier should be used that will reach the bottom of
the container with each compartment 15 cm long (see Fig.
15). Noncompartmented
pglx150.gif (600x600)
grain triers should not be used to sample grain.
c. In
probe-sampling a bin from the top, the probe or trier should be
inserted in the grain at an angle of about 10 degrees from
the vertical, with the
slots closed. The probe should be opened while the slots are
facing upward.
While the slots remain open, the probe should be moved up
and down so that
all openings may be filled. The probings should be emptied
onto a sheet and
coned or quartered or mechanically divided to sample size.
d. In bag sampling,
the trier should be inserted from a corner diagonally
across to the farthest corner.
2.
Techniques for Sampling Bagged Produce (10) Adapted
from Trop. Stored Prod. Inf. 31: 37 (1976).)
P. Golob
The Importance of Sampling
Quality is an
important factor which dictates the value of a commodity. It is
judged by the overall appearance of the produce and will be
adversely affected
if there are holes in the grains caused by insect attack,
discolored grains from
mold damage, shrivelled grains, cracked and broken grains
from bad handling,
or rodent hairs and droppings.
Infestation by
stored product insect pests before harvest is common so that a
consignment may enter a store having a low-level
infestation. Depending on
climatic conditions, the pests can multiply rapidly and
greatly damage the
crop. Thus it is of vital importance that the infestation be
detected as early as
possible, preferably before storage begins. The crop must be
inspected and
sampled as it is unloaded from lorries or railway trucks
before it is stacked for
storage.
As a commodity
deteriorates during storage, it loses value. For the government
of an exporting country this can mean a loss of foreign
exchange. For the
subsistence farmer the losses result in less food to eat.
Poor storage conditions
can aid the increase of insect and mold populations and bad
storage structures
can allow the entry of rodents. It is, therefore, important
to continually check
stored produce in order to monitor changes.
For practical
reasons it is not physically possible to examine every grain in a
consignment. Thus the quality of the whole has to be judged
on the basis of a
sample. The sample must be representative of the individual
bag or stack from
which it is drawn. In this Appendix the various techniques
which may be used
to obtain representative samples from bagged commodities are
described and
their limitations are discussed.
Sampling From Stacks (See also Chapter IV)
The principles of
sampling from stacks apply to all types of stacking situations
whether in a large warehouse or godown, a ship, a train or
lorry, in a
trader's store, or a farmer's crib. In practice, however, it
may not be possible
to put all the principles to use due to the accessibility of
the stack.
Consignments of
produce can be divided into sectors on the basis of location.
For example, in a ship the commodities may be segregated in
different
holds, wherein each hold can be regarded as an individual
sector in terms of
climatic and other physical influences. Similarly each
boxcar of a train might
be regarded as a single sampling entity. Each sector must be
identified and
sampled individually.
As the conditions
within each sector may fluctuate as much as those affecting
the total consignment, it is important to obtain samples
which are representative
of the sector from which they have been drawn. Each sector
itself can
be stratified and samples must be drawn from all areas
within each sector, ie,
from the top, middle and bottom, left and right, center and
periphery. Removing
samples from these strata should be performed at random.
Twenty-four
sampling points from a cuboidal stack should provide an accurate
representation of the stack. However, taking samples from as
many points
as this for all but the largest stacks is uneconomical and
unwarranted, as fewer
sampling points will give as accurate a pattern. Five
sampling points are recommended
for wagons and lorries of up to 15 tonnes, eight points for
up to 30
tonnes, and eleven points for containers up to 50 tonnes, as
shown in Fig. 16.
pglx151.gif (486x486)
Number of Sacks From Sector (See also Chapter IV)
The above
recommendations are inappropriate for sampling stacked bags
because they regard the stack as a two-dimensional
structure. They take no
account of the difference between top layers in a container
and lower layers
where dust and insects would tend to accumulate. They
disregard any possible
changes that affect one side of the stack rather than the
other and they ignore
the fact that stacks are accumulations of individual units
that can be separately
sampled.
Practical
experience has shown that the optimum number of samples to be
obtained from a large consignment (over 100) of sacks is
given by the square
root of the total. Jelier (1) suggests that for sectors of
10-100 bags, 10 bags
should be taken at random and for up to 10 bags, each bag
should be sampled.
Thus, from a lorry having perhaps 100 sacks the sample would
consist of 10,
which would represent all areas of the stack.
Bags drawn from the
stack using the above rules constitute the initial sample
which should be taken randomly but at the same time should
be representative
of the whole stack. In practice, when obtaining the initial
sample from a small
stack as found on a lorry, it is not possible to sample
entirely at random. The
structure and size of the stack determine from which areas
bags must be
chosen, so that the number of bags from which the random
choice has to be
made is relatively restricted and may only be three or four
bags.
In many cases it is
not possible to sample randomly from all sectors of very
large stacks. Only by breaking the stack down would most
bags become available.
Thus only a relatively small area can be sampled. Effort
should be made
to get to bags in the middle. To do this, several layers of
bags at the top of the
stack should be removed and a bag in the sixth or seventh
layer obtained for
observation. This practice in no way utilizes randomized
searching for initial
samples.
The Bag as the Sample Unit
Sampling of the
commodity within the bag must be random so that every
grain has a chance of being picked. Many of the
sample-taking procedures are
not random but tend to be haphazard, resulting in having
human bias. With
haphazard sampling, such as using a spear or trier, every
grain does not have a
chance of being picked as just a portion and not the whole
bag is the sample
unit.
Methods of Obtaining Samples From Sacks
1. Spear Sampling
Bag sampling with a
spear or trier is practiced throughout the world. There
are many types and variations of sampling spears, the
commonest of which is
illustrated in Fig. 17. Bag spears are usually cylindrical
in shape and between
pglx152.gif (486x486)
40 and 45 cm in length with a diameter of 2.5 cm, except at
one end which is
drawn to a point.
The tube is open on
one side to allow grains to fall into a collecting channel,
which passes back along the length of the spear and opens
out through the
handle. This type of spear is used for collecting large
particled material, such
as maize grains or coffee berries. Other types of spears may
be of similar
design but narrower for collecting smaller grains such as
wheat and sorghum
(Fig. 17B) or simply open-grooved lengths of metal attached
to a handle (Fig. 17C).
The spear has
several good features; it is cheap, simple to use, and is a quick
way of obtaining grain from bagged produce. The tip of the
spear is pushed
into the bag, and the body with the open side face down is
inserted for the
required distance. Grain is collected in the channel by
twisting the spear so that
the open side is turned upwards. On withdrawing the spear
from the bag, the
grain is tipped out of it into a container. If the spear is
inserted into the sack at
an angle, with the point uppermost, grain entering it can
pass straight into a
container without the spear being removed, so that a large
sample can be
obtained (see Fig. 18). Generally six or more samples are
removed from each
pglx153.gif (486x486)
sack to make up a primary sample.
Because of its
widespread use, the faults of spear sampling are usually
disregarded. However, the disadvantage of the spear is so
fundamental that it
negates most of the results obtained upon analyzing samples
collected by this
method. When a spear is inserted into a sack either
horizontally or at an acute
angle, only a very small volume of the sack commodity is
sampled, ie, precisely
that material that actually falls into the spear cavity. The
sack is not sampled
randomly; the grains picked depend on the haphazard method
used to insert
the spear into the bag (see Fig 19).
pglx154.gif (600x600)
Many elements of
stored crops (such as protein and vitamin contents) are
generally constant throughout a single sackful of produce or
any variations
that do occur are insignificant. Produce moisture content
and insect numbers,
however, may not be constant throughout the bag. Insects, in
particular,
distribute themselves neither uniformly nor randomly. They
are often found in
pockets associated with the dust or meal material at the
bottom of the bag or in
areas of local heating and wetting.
Producing
information on insect numbers in a sack using a spear sample can
lead to erroneous conclusions and be totally misleading,
either overestimating
a population or more frequently underestimating it. Examples
of the way in
which this could occur are shown in Fig. 19. In Fig. 19A, a
large population of
insects crawling on the bottom of the bag could easily be
missed by spear
sampling; it is difficult to sample very close to the bag
fabric, top and bottom.
Observing or missing a population such as this could
influence the decision to
treat the commodity to eradicate the infestation, resulting
in heavy losses of
produce. In Fig. 19B, small pockets of two or three insects
could by chance be
picked up by a spear sample. Six insects in 100 kg of maize
may not require
eradicating if the produce is not going to be stored for
long periods. However,
six insects in a 500-kg sample is equivalent to 1,200
individuals in a 100-kg bag
if randomly distributed, whereas there may be less than ten
in the whole bag.
Thus spear sampling
can produce grossly misleading results and should be
avoided. A compartmented probe (Fig. 15) should be used
whenever a probe
pglx150.gif (600x600)
sample is taken. Compartmented probes are available in bag
size, as in Fig. 15,
or in larger sizes for probing deeper piles in bins, wagons,
etc.
2. Coning and Quartering
Sampling at farmer
and trader level requires a procedure that is simple,
cheap, and accurate. Coning and quartering is such a method.
When a bag of
commodity is opened and the produce is tipped onto the
floor, the contents naturally assume the shape of a cone. By
shovelling material
from the periphery of the cone to the apex, while circling
the periphery,
complete mixing and randomization of the produce will occur.
This mixing
needs to be done for 3 to 4 min at least five times round
the circumference.
Division of the bulk into halves and then quarters using a
flat piece of wood or
quartering irons produces four samples of very similar
properties. From a
100-kg bag, each sample would be 25 kg, too large to be
useful. By further
subdivision, using the same coning and dividing procedure,
each quarter can
be divided into 1/8th, 1/16th, 1/32nd, etc., subsamples.
Sampling error by
coning and quartering is about 10%, which is much more
accurate than spear sampling. This method is time-consuming,
however, and
can only be used when a small number of bags require
sampling. For continuous
sampling at marketing board or export level, the produce
flow sampler can
be used.
3. Sieving
The three
techniques described above comprise methods by which small
quantities of material can be removed from the bulk for
analyses or inspection.
An estimate of dust content or insect number in a sack can
best be
obtained by using a sieve. Unlike the methods discussed
above, a sample
representing the whole sack is not obtained. Instead the
commodity is divided
on the basis of particle size. Smaller particles, including
insects, pass through
the sieve mesh whereas large particles pass over it and are
returned to its bag.
A type of bag sieve
is shown in Fig. 20. The produce is tipped into a hopper
pglx156.gif (600x600)
located above the sieve mesh. On oscillating the mesh by a
simple handcranked
gear mechanism, the produce flows out of the hopper and over
the
mesh surface. The bulk of the produce passes back into the
sack, and dust and
insects are collected in a tray slung below the mesh. The
mesh size can be
altered as required depending on the particle size of the
produce being sieved.
Tests have shown that more than 90% of all dust and insects
is removed using
this apparatus, the recovery of insects being independent of
the population
density.
Apparatus for Sample Reduction
Sample reduction
can be performed by coning and quartering (see above) or
by using specific apparatus designed for this purpose.
Generally, this equipment
divides the sample into halves which then have to be passed
repeatedly
through the divider until a workable sample is obtained.
Such a divider is the
Boerner divider (Fig. 21).
pglx157.gif (540x540)
1. Boerner Divider (Conical Type)
This is a gravity
mechanical divider which works on the same principles as
the produce flow sampler (see below). The produce flows out
of a hopper and
around a cone but, unlike the PFS which takes a single
sample of up to 12% of
the total, the Boerner simply divides the total in half.
Instead of the four
sampling points of the PFS, the Boerner has a series of
channels around the
periphery of the cone. As the commodity flows into the
channels, it is directed
into one of two collecting points. The direction of flow of
the channels alternates
around the periphery so that every other one directs the
flow into the
same collecting pot. The Boerner is an accurate method of sample
division.
2. Box Divider
A simplified
version of the alternate-channel separation is the box divider
shown in Fig. 22. It is less expensive than the Boerner,
more easily transported,
pglx158.gif (437x437)
less subject to damage (and when damaged more easily repaired),
and does
almost as accurate a job as the Boerner. In using, care
should be taken that the
slot widths remain uniform and are not bent out of position.
3. Motorized Divider (Centrifugal Type)
In this divider the
seed falls into a shallow rotating cup from which it is
flung into a chamber divided into two or more outlets at the
bottom. An
example of this type is the Gamet divider (Fig. 23). In
dividers of similar
pglx159.gif (486x486)
design, the grain may be delivered from a rotating spout
over a number of
containers or over a cone with adjustable dividing blades at
the bottom which
may be arranged to separate off any desired fraction.
4. Produce Flow Sampler
The produce flow
sampler (PFS) (Fig. 24) is a device designed by the British
pglx160.gif (600x600)
Tropical Stored Products Centre for taking samples from
whole bags of grain.
The produce is tipped into an upper hopper which has an
opening at the
bottom. The opening is closed by a bung until sampling
commences. On
removing the bung, the produce flows down and around a cone
and, because
the apex of the cone is placed exactly under the center of
the hopper opening,
the flow of produce is equal all around the cone. Samples
are separated from
the main flow at four points at the base of the cone, the
points being spaced
equally around its periphery. The bulk of the produce is
recollected in a sack
attached by hooks to the bottom of the collecting funnel.
Sampling time is 20
sec for a 100-kg bag. Size of the samples can be altered by
changing the vent
that covers each sampling point.
The PFS was
originally designed for sampling bags as they were off-loaded
from lorries before the produce went into store. For this
purpose, the PFS is 8
ft high but the length of the legs can be lowered if
required. All flowable
commodities can be sampled using the device.
Tests on the
accuracy of this method have been performed using bags of
produce containing a small percentage of grains stained with
a dye strategically
placed at different parts of the bag to simulate pockets of
defective produce.
With groundnuts, for example, containing 5% dyed kernels,
the percentage of
stained nuts in the samples ranged between 3.4 and 6.0% in
15 tests, and for
maize and wheat which had 1% dyed grains, the recovery range
was 0.3-1.5%
in 30 tests. Thus accurate recoveries were obtained.
The PFS method of
sampling is accurate because, unlike spear sampling, the
whole bag is sample unit and the sample is obtained
randomly, each grain
having a chance of being picked.
Conclusions
Samples obtained
from bagged produce must be both representative and
random of that produce. Sampling using a spear is not random
and does not
result in a representative quantity of produce being taken.
At farmer or trader
level, coning and quartering do provide accurate results and
samples of similar
quality at marketing board or export level are best obtained
with the PFS.
Sieving, although not strictly a sampling procedure, can
give accurate estimation
of surface insect population. Subdivision of primary samples
must be
random and the Boerner, box, and Gamet dividers fill this
function. However,
the equipment for subdivision of samples is relatively
sophisticated and is not
always available. It may be more practical and almost as
reliable to reduce
samples by coning and quartering.
Literature Cited
1. JELIER, G. Sampling of grains, milled products, starch
products, and potato starch. Int.
Assoc. Cereal
Chem. ICC Standard 101 (1970).
APPENDIX B
TABLES OF RANDOM NUMBERS AND THEIR USE
B. Drew and T. Granovsky
Sample selection by
means of randomization is not an unorganized hit-or-miss
process. It is a rather formal protocol-dictated process to
assure that an
intentional or unintentional bias will not be introduced
during sample selection
and sampling.
A random sample
means that each and every unit (ears, plants, baskets,
row, farm) in a population has an equal chance of being
selected. It means that
the selection of "good looking," or
"typical," or "some of the good ones and
some of the bad ones," or those within a convenient
distance will be avoided.
To select on such bases neglects the principle that each
sample should have an
equal chance of being selected. Any such selection, therefore,
introduces bias.
Random selection usually means that randomization must be
done by the
project planners and supervisors although it may be
accomplished at the working
level and situations may be classified by the state of
knowledge into 1)
where information about the size of population to be sampled
is available
before field-workers are sent out, or where field-workers
are competent to
randomize, and 2) where information about population sizes
is not available in
advance and field-workers are not competent to randomize.
In either
situation, the only way to select at random is by a table of random
pglx164.gif (600x600)
numbers. Any other means simply will not give the total
randomization that is
provided by a table of random numbers.
A table of random
numbers (see Table VII) should be used by a fixed
procedure determined in advance. To do this, one should know
in advance
what units and how many are to be taken as the sample: ears
of corn, bags of
grain, farms lying on map coordinates, etc. The procedure
for taking the
sample also needs to be established in advance.
1. Plan the
selection of elements to be sampled in advance. Decide what is
to be selected: rows, bags in piles requiring
predetermination along a three-dimensional
grid, bags as they are moved for sampling, etc. Decide how
many
of these units are to be taken for the sample.
2. Number the units
in any convenient way starting with 1 and going as high
as necessary.
3. Use the table of
random digits. Start at any point in the table and proceed
to read off pairs of digits in any direction - up, down,
sideways, diagonally.
4. Write down the
pairs of digits as they occur. Skip any numbers that are
repetitions, or that are bigger than the total number of
units numbered in
step 1.
5. When you have
written down the number of units to be taken in the
sample, stop.
6. Sample those
units whose numbers have been listed.
7. Each time the
table is used indicate the starting pair of digits by circling.
Do not start at the same place again.
Cases Classified by Situation
1. Where units can
be numbered in advance:
Cribs on a farm
Baskets in a
building
Houses in a
village
Stacks in a
field
2. Where units are
encountered sequentially:
Bags being
unloaded from a truck or boat
Farmers coming
to market
Farms located
along a road
3. Where units can
be designated by coordinates:
Map coordinates
Three-dimensional (a pile in a warehouse)
Special Instructions for Map Coordinates
Map Coordinates Method 1 (Preferred Method)
Number every grid
point on the map. Leave out grid points that are inaccessible.
Choose pairs of random digits as given earlier. If there are
more than 100
grid points, follow the same procedure but use triples of
random digits.
Map Coordinates Method 2 (Alternative Method)
Consider the
vertical (north-south) coordinates to be units to be sampled.
Number them from 1 up and use random numbers to choose as
many coordinates
as are needed in the sample. In this case do not skip
repetitions.
Then consider the
east-west (horizontal) coordinates to be the units. Number
them from 1 up and use random numbers to choose as many
coordinates as
are needed. As each coordinate is chosen, pair it with the
next unused one of
the N-S coordinates from the first set. Repetitions are only
skipped if they are
paired with the same N-S coordinate.
APPENDIX C
MOISTURE METERS
Part 1
Guidance in the Selection of Moisture Meters
for Durable Agricultural Produce((11) Adapted from
Trop. Stored Prod. Inf. 21: 19 (1971).)
T. N. Okwelogu
The market for
moisture meters is both specialized and growing, and there is
a need for special attention to the selection of meters. The
manufacturer aims
to reach as many possible users as he can, while the
prospective buyer wants to
know about as many meters as he can before investing in any
model. Over the
years 1966-70 enquiries about moisture meters have been
received at The Tropical
Stored Products Centre at the rate of approximately 100 a
year. These
enquiries have varied from wanting to know if a particular
meter had a supply
address in the locality of the enquirer, to seeking advice
on what meter should
be used for a specified purpose.
This statement is
not a treatise on moisture meters, but an attempt to help
the prospective buyer dealing with durable agricultural
produce to determine
which moisture meter best meets his requirements.
Sources of Information
The three principal
sources of information available to the prospective users
are 1) newspapers, magazines, and journals, 2)
manufacturers' brochures, and
3) organizations in a position to give unbiased information
about moisture
meters.
Some newspapers,
magazines, and journals, which occasionally contain information
about meters, include the Financial Times, Electronic Age,
and
Power Farming. While manufacturers are always helpful in
supplying data
about their own range of meters, information about a wider
range of meters
will be more likely obtained from organizations having
unbiased interest in
these instruments. Examples of such organizations are 1)
Tropical Stored
Products Centre (Tropical Products Institute), Slough,
England, 2) Grain
Storage Department, Pest Infestation Control Laboratory,
Ministry of Agriculture,
Fisheries and Food, Slough, England, 3) National Institute
of Agricultural
Engineering, Wrest Park, Silsoe Beds, England, and 4) Grains
Division,
Agricultural Marketing Service, U.S. Department of
Agriculture, Agricultural
Research Center, Beltsville, MD 20705. Articles on moisture
meters sometimes
appear in the publications of these and similar
organizations.
Tables VIII and IX
give details of some available moisture meters, particularly
pgl81680.gif (600x600)
used. These details are based on information provided by the
manufacturers of
the meters.
With every piece of
information, it is important to ask the question: Is this
information sufficient for a decisive opinion to be formed
about the meter?
Where the answer is no, further enquiries should be made.
Factors to Consider in Making a Choice
It can be seen from
Tables VIII and IX and in Parts 2 and 3 of Appendix C
that there are several meters for any specific purpose. For
satisfactory selection,
the following factors should be carefully considered:
1. Meter types and
their implications.
2. Characteristics
of the commodity.
3. Requirements of
the work for which a meter is sought.
4. Business
considerations.
Principles and Implications of Meter Types
Most manufacturers
indicate the principles upon which the action of their
meters is based. An appreciation of the implications of such
principles will be
of considerable value in deciding which of several meters
will be the most
suitable. The meters commonly used with durable agricultural
products fall
into five groups, according to the principles of their action:
1. Those involving
chemical interaction between calcium carbide and the
product water,
with the evolution of acetylene gas, the pressure of which
is subsequently
measured.
2. Those involving
heat-drying of the product, the attendant loss ascribed
to evaporated
produce water (Fig. 25).
pglx174.gif (600x600)
3. Those involving
measurement of electrical conductivity (or resistance) of
the product,
since the value of this property is related to the moisture
content, within
a suitable range of moisture contents (Fig. 26).
pglx175.gif (600x600)
4. Those involving
measurement of the dielectric constant of the product
(or capacitance
of the electrical system of which the product is a component),
since the value
of this property changes with the moisture content,
within a
suitable range of moisture contents (Fig. 27).
pglx176.gif (600x600)
5. Those involving
measurement of that atmospheric relative humidity
which is in
equilibrium with the product moisture, since, under equilibrium
conditions,
there is a definite relation between the moisture content
of a product and
the ambient relative humidity (Fig. 28).
pglx177.gif (600x600)
Although it is
tempting to try to list the advantages and disadvantages of the
meter types, this approach is ineffective in providing
buyers with adequate
guidance. For example, although many resistance meters
require a ground
sample, use a small sample, or test products with a
relatively short range of
moisture content, there are others in the same group which
do not require the
sample to be ground, which can test large samples (by using
probes on whole
sacks), or have an extended range of operating moisture
contents. There are,
nevertheless, certain outstanding group features to be
noted: Heat-drying
methods require a suitable source of power supply or fuel, which
may not be
available. Methods based on the evolution of acetylene gas
require regular
supplies of fresh calcium carbide, which is not a safe
commodity to handle by
post, because of the risk of explosion. Meters measuring the
intergranular
relative humidity require, first, a knowledge of the
relation between the
produce moisture content and the relative humidity of the
intergranular air;
secondly, a periodic check on their calibrations; and
thirdly, in some cases,
large quantities of produce which must have remained
undisturbed for some
time prior to testing.
The electrical
meters are faster and, in the main, less demanding on calibration
checks, but require skilled servicing. Also, they give less
reliable readings
outside the middle region of the range of moisture contents
for which they are
calibrated. The accuracy of the probe-type electrical meters
is affected by
variations in the pressure exerted by the produce on the
electrodes, while the
consistency of the readings of those meters which measure the
dielectric constant
is affected by inconsistent packing of the sample in the
test chamber.
Attention has been
focused above on the less favorable features of the meter
groups mainly because they are more likely to be overlooked.
Information on
the merits of any meter will not normally be difficult to
obtain, and Tables
VIII and IX show the relative merits of the meters discussed
in the present
article.
Characteristics of the Commodity
The commodity to be
tested imposes a number of limitations, and these
must be taken into account when considering the use of any
meter. Perhaps the
best way to do this is to answer questions such as the
following:
First, is the
chemical nature or any normal pre-treatment of the produce
likely to interfere with the use of the meter? For instance,
meters measuring
electrical conductivity may not be suitable for produce,
like salt-fish, which
will become highly conductive when damp. Again, for
commodities like dried
egg or milk, a heat-drying meter may not be suitable.
Second, is the
moisture content to be measured outside the range for which
the meter is calibrated? For example, very few electrical
meters are known to
be suitable for a product such as tea whose moisture content
is normally
required to be below 5%, that is, outside the range of
moisture contents for
which most electrical meters are calibrated.
Third, is the
milling property of the produce incompatible with the effective
use of the meter? For example, commodities such as macadamia
nuts, palm
kernels, copra, and cashew nuts are not amenable to
grinding.
Fourth, are the
unit size and shape of the produce likely to affect the
efficient use of the meter? Construction of the meter may be
such that it
cannot be pushed into floury or powdery produce without
hampering the
measurement of moisture. Again, larger products like cocoa
beans, unshelled
groundnuts, cashew nuts, and pieces of illipe nuts (Shorea
spp.) will present
packing problems with some meters.
If the answer to
each of the above questions is an unqualified no, then the
meter may be considered suitable for the product. But a yes
answer can make
all the difference between a meter being chosen or rejected.
In such a case,
steps should be taken to see what, if anything, has been
done to solve the
problem, either by the manufacturer or by someone else.
Nature of the Situation Needing a Moisture Meter
In a summary of
this kind, it is not easy, even if it is possible, to cover all the
situations where the use of a moisture meter may be desired.
However, such
situations are likely to fall into one or the other of the
following categories:
1. Knowing whether
grain is at the right stage for harvesting.
2. The processing
(eg, drying, milling, or storage) of foodstuffs.
3. Bulking or
packaging for storage.
4. Commercial
transaction, where moisture content is part of the basis for
payments.
5. Produce
inspection including loss estimates.
All the above
situations require moisture meters which are not fragile, which
are consistently accurate within limits acceptable for the
particular purpose,
and whose performance is little affected by the operating
conditions of space,
temperature, pressure, light, dust, or wind. They also
require, to a certain
extent, meters that are simple to operate, portable, and
capable of taking
remote measurements, as with probe-electrodes, or stem
hygrometers, or that
samples be taken of the material for laboratory testing.
Operational Considerations
The purpose for
which the use of a meter is usually contemplated is twofold:
to increase or improve productivity (that is, the flow of
goods and services),
and to ensure economical operations. The usefulness of the
meter can be
improved by employing one which can give results rapidly;
for which spares
and facilities for servicing or calibration are easily
available; and which does
not depend on sources of operating power that run out, break
down, or
become short in supply (eg, battery, mains supplies, gas,
paraffin, and other
fuel).
Economy of
operation implies keeping to a minimum both capital and
operating costs or increasing the return to unit cost.
Additionally, even though
it may have been purchased for a specific grain, the wider
the range of commodities
that a meter can test, the more flexible and economical may
be its
total use. Likewise, the less destructive a test is, the
less will be the incidental
loss of material caused by the use of a meter. Although this
kind of loss may
appear small, it must be realized that its magnitude will
depend on how much
produce is damaged at each test, and how many times such
tests are performed
on a given product.
Conclusions
Few meters, if any,
can win the top position in every conceivable area of
consideration, and there is no magic formula for choosing a
meter. Where a
choice has to be made, however, all known factors need to be
considered. This
implies having adequate information about as many meters as
possible, and
then carefully checking the meter descriptions against the
requirements.
The buyer must have
a knowledge of the commodity to be tested and the
accuracy required of a determination of its moisture
content; the availability
of the meter, and the cost of operating it; the conditions
under which the meter
will be operated; the ease of obtaining spares and
facilities for servicing or
calibrating the meter; and the type of power supply required
and available.
When a provisional choice has been made, it is often
advisable to obtain the
meter on loan for trial before buying. This will make it
possible to verify
certain claims which may not be possible otherwise. For
example, the buyer
may discover that the meter does not give as "precise,
error-free, and effortless
moisture measurement" as he was made to expect. He may
discover, too,
that although the meter is calibrated for rice, it in fact
needs a different
calibration for his own type of rice.
Choosing a moisture
meter must be approached from both commercial and
technical aspects, and requires a critical appraisal of many
variables.
APPENDIX C
Part 2
Table of U.S.
Department of Agriculture, Federal Grain Inspection
Service List
of Moisture Meters Used in the United States and
Their Manufacturers, April 1978(a)
Principle of
Name of Device
Operation
Manufacturer or Distributor
American Moisture
Infrared heat- American Farm
Equipment Co.
Tester -- Model
ing -- direct 340 E. Main
St.
M-20
reading Lake Zurich,
IL 60047
Apollo Microwave
Loss on drying Apollo
Microwave Products
Laboratory
using microwave 6204 Official
Road
energy Crystal Lake,
IL 60014
Auto-aquatrator
Karl Fischer Precision
Scientific Group
Method 3737 West
Cortland St.
Chicago, IL 60647
Brabender, C.W.
Thermobalance C.W. Brabender
Instruments, Inc.
Rapid Moisture
50 East Wesley St.
Tester
South Hackensack, NJ 07606
Brown-Duvel
Distillation Burrows
Equipment Co.
Moisture Tester
1316 Sherman Ave.
Evanston, IL 60204
Gerber Industries
P.O. Box 1387
Minneapolis, MN 55440
Seedburo Equipment Co.
1022 West Jackson Blvd.
Chicago, IL 60607
Burrows DMC-700
Dielectric Burrows Equipment
Co.
1316 Sherman Ave.
Evanston, IL 60204
Dickey-john, Inc.
P.O. Box 10
Auburn, IL
62615
Burrows Moisture
Capacitance Burrows
Equipment Company
Recorder
1316 Sherman Ave.
Evanston, IL 60204
Burrows Safe
Capacitance Burrows
Equipment Company
Crop III Moisture
1316 Sherman Ave.
Tester
Evanston, IL 60204
Burrows Model 400
Capacitance Burrows
Equipment Company
(Radson) Moisture
1316 Sherman Ave.
Meter
Evanston, IL 60204
Buhler MIAG Rapid
Thermobalance The Buhler
Corporation
Moisture Tester,
P.O. Box 9497
Type MLI-400
1100 Xenium Lane
Minneapolis, MN 55440
Cera-Tester
Capacitance A/S N. Foss
Electric
Slangerupgade 69
DK 3400 Hiller[phi]d, Denmark
Principle of
Name of Device
Operation Manufacturer
or Distributor
Delmhorst
Conductance Delmhorst
Instrument Co.
Moisture Detector
607
Cedar St.
Boonton, NJ 07005
Dickey-john DJ1S
Dielectric Dickey-john,
Inc.
P.O. Box 10
Auburn, IL 62615
Dickey-john
Dielectric Dickey-john,
Inc.
Forage Moisture
P.O. Box 10
Tester
Auburn, IL 62615
Dickey-john
Dielectric Dickey-john,
Inc.
GAC-II
P.O. Box 10
Auburn, IL 62615
Dickey-john
Dielectric Dickey-john,
Inc.
GAC-III
P.O. Box 10
Auburn, IL 62615
Digital Moisture
R.F. Capacitive Diversified
Engineering, Inc.
Meter Model DM/6
Measurement 2022 Sledd
St.
Richmond, VA 23220
Grain Quality
Near IR Neotec Instruments,
Inc.
Analyzer
2431 Linden Lane
Silver Spring, MD 20910
Higropant
Conductance National
Instrument Co., Inc.
Moisture Meter
4119 Fordleigh Road
Baltimore, MD 21215
Humidimetre
Dielectric Cedem,
Division Instrumentation
Digital HD. 2000
Fully Automatic Agricole Et
Alimentaire
33-5 rue Jean Baptiste Charcot
92400 Courbevoie, France
Insto-I Moisture
Dielectric Dickey-john,
Inc.
Tester
P.O. Box 10
Auburn, IL 62615
Insto-II Moisture
Dielectric Dickey-john,
Inc.
Tester
P.O. Box 10
Auburn, IL 62615
KF-4B Aquameter
Karl Fischer Beckman Instruments,
Inc.
System
Method Scientific
Instruments Div.
P.O. Box C-19600
Campus Dr. at Jamboree
Blvd.
Irvine, CA 92713
KPM Aqua Boy
Conductance Chatham
International Corp.
MS-I
P.O. Box 377
Larchmont, NY 10538
Koster Crop
Heating Koster Crop
Tester, Inc.
Tester
4716 Warrensville Ctr. Rd.
North Randall, OH 44128
Marconi Moisture
Conductance Marconi
Instruments
Meter Type
100 Stonehurst Court
TF-933C
Northvale, NJ 07647
Mettler LP 11
Infrared Mettler
Instruments Corp.
thermobalance 20 Nassau St.
Princeton, NJ 08540
Principle of
Name of Device
Operation Manufacturer
or Distributor
Model G8R or
Radio frequency Moisture
Register Company
Model G9
dielectric power 6934 Tujunga
Ave.
loss factor No.
Hollywood, CA 91605
Moisture Teller
Heating Harry W.
Dietert Company
Model 276
9820 Roselawn Ave.
Detroit, MI 48204
Motomco Moisture
Capacitance Motomco, Inc.
Meter -- Models
267 Vreeland Ave.
919, 840, and 430
P.O. Box 300
Patterson, NJ 07513
Ohaus Moisture
Infrared heating
Ohaus Scale Corporation
Determination
and balance 1050 Commerce
Ave.
Balance
Union, NJ 07083
Optical Moisture
Infrared Anacon, Inc.
Analyzer
absorption P.O. Box 416
Burlington, MA 01803
Pier Moisture
Infrared Neotec
Instruments, Inc.
Analyzer
Reflectance 2431 Linden
Lane
Silver Spring, MD 20910
Protimeter Grain
Conductance Cosa
Corporation
Moisture Meters
17 Philips Parkway
Montvale, NJ 07645
Quik-Test
Dielectric Dickey-john,
Inc.
Moisture Tester
P.O. Box 10
Auburn, IL 62615
Schenk Moisture
Capacitance Schenk
Moisture Engineering
Monitor
and/or R.R. 7, Box
78
Conductance Vincennes, IN
47591
Semi-Automatic
Thermobalance Haake, Inc.
Moisture Tester
244 Saddle River Road
Saddle Brook, NJ 07662
Skuttle Moisture
Conductance Skuttle
Manufacturing Co.
Meter
Electronic Division
Canfield, OH 44406
Steinlite
Electronic Seedburo
Equipment Co.
Moisture Tester
Impedance 1022 West
Jackson Blvd.
Chicago, IL 60607
Super-Conti
Capacitance A/S N. Foss
Electric
Automatic Slangerupgade
69, DK 3400
Recording
Hiller[phi]d, Denmark
Super-Matic I
Capacitance A/S N. Foss
Electric
Print-out Slangerupgade
69, DK 3400
Hiller[phi]d, Denmark
T & M Vacuum
Infrared vacuum Townson &
Mercer, Ltd.
Moisture Tester
thermobalance Scientific
Equipment
Beddington Lane
Croydon, England
Technicon
Near Infrared Technicon
Industrial Systems
InfraAlyzer
511 Benedict Ave.
Tarrytown, NY 10591
Principle of
Name of Device
Operation Manufacturer
or Distributor
Dickey-john, Inc.
P.O. Box 10
Auburn, IL 62615
Universal Moisture
Conductance
Burrows Equipment Company
Tester
1316 Sherman Avenue
Evanston, IL 60201
902 Moisture
Phosphorous E.I. DuPont
Co.
Evolution
Pentozide Instrument
Products Div.
Analyzer
Quillen Bldg.
Concord Plaza
Wilmington, DE 19898
No. 1210 Froment
Mechanical N.J. Froment
Moisture Tester
Plunger -- 9-volt P.O. Box 758
Battery Trenton,
Ontario
Canada
------------------------------------------------------------------------------
(a) This list was compiled from manufacturers responding to
a USDA inquiry. Inclusion does not imply U.S.
Government endorsement; omission does not imply disapproval.
APPENDIX D
ASSESSMENT OF PROFITABILITY OF ALTERNATIVE
FARM-LEVEL STORAGES((12) This appendix is
abstracted from a paper given in Coimbatore, Tamil Nadu,
India, 1976, to a national meeting of engineers working on
postharvest technology.
The final report referred to is the IDS/IGSI Crop Storage
Project report
submitted to the Government of India in 1978.)
M. Greeley
There have been
relatively few attempts to assess the private profitability of
alternative farm-level storage improvements. Yet without
this evaluation there
is no basis for choosing between alternative technologies.
The exercise below
illustrates an approach to evaluating three important
methods of storage improvement for Andhra Pradesh, India. In
each case, we
ascertain a benefit-cost ratio for each rupee invested by
determining how many
rupees are gained through grain saved by improving storage
methods.
It must be
emphasized that we are concerned here mainly with explaining the
approach and that, for example, the levels of losses due to
different causes
given here are rough and are presented only as examples.
The three storage
improvements, all designed by a local grain storage institute,
are:
1. The domestic
metal bin, manufactured by Andhra Pradesh State Agro-Industries
Corporation;
2. the improved
platform for the outdoor gade (bamboo basket); and
3. the improved
base for the puri (large circular paddy-straw rope structure).
Improvements to the
gade and puri are both designed to prevent access to
rodents and groundwater migration. The puri is not fumigable
but the gade
can be fumigated successfully once a mud and dung coat is
applied. The
project has built over 30 gade improvements and 10 puri
improvements. To
make comparisons easy, all calculations are based on storage
of one 75-kg bag
of paddy. We are using loss-levels by cause((13) Comparison
between the gade
and the metal bin is unaffected by the relative
importance of different causes because all three types of
losses can be prevented
in both. This is not true for the puri where fumigation is
not possible. It may
also be true that the importance of different causes of loss
varies significantly
between unimproved gades and unimproved puris as well as
there being variation
in the total percentage of losses, but the purpose here is
to describe the method.
The actual results are secondary, though it could be said
that the improved
gade-metal bin comparison is more realistic than comparing
either one of these
with the puri.) in the traditional stores of:
rodents, 2%; insects, 2%; and molds, 1%, assuming that the
maximum saving
possible through storage improvement is 5%.
In addition, other
values required are:
1. Initial
construction costs both of the structure and the improved base/
platform.
2. Annually recurring
costs.
3. The price of
paddy.
4. The effective
life of the structures.
5. A discount
factor.((14) A discount factor is a simple concept. It gives
the relation between
future cash flows and their present value. Asked to choose
between a gift of
Rs 100 now and Rs 100 in ten years' time, we would all
choose Rs 100 now. To
be willing to give up Rs 100 now, how much money would I
require to be given
in ten years' time? This depends on how much extra money I
could earn in ten
years with the Rs 100 invested, which in turn depends on the
rate of return.
This depends on the rate of interest. The discount factor
works like a
compound rate of interest. The value now of a Rs 100 in ten
years' time is the
amount of money I would have to invest now in order to have
Rs 100 in ten
years' time at a compound rate of interest. If I invest Rs
32 at a 12% rate of
compound interest, its value in ten years' time is just
under Rs 100; so the
discounted present value of Rs 100 in ten years' time in
this case is Rs 32. In
valuing future costs or benefits to obtain their present
value, we divide by a
discount factor (the inverse of multiplying by a rate of
interest). After one
year an investment is worth P (1 + i), that is, the
principal sum (P) plus the
principal times the rate of interest. This sum which we call
[P.sub.1] divided by
(1 + i) equals P. Looking at the change after one year helps
to understand the
role of the discount factor. Rs 100 now at a 12% rate of
interest equals $100 +
Rs 12 after one year (100 + 100 x 0. 12 = (P + P x i) =
112). We write this
formula as P (1 + i). To find the original (present) value
of that Rs 112 which
we can call [P.sub.1], we simply reverse the process.
Instead of multiplying
by (1 + i) we divide by (1 + i). The present value is
112
[P.sub.1]
-------- = 100,
ie, P = ---------
1 + 0.12
(1 + i)
Similarly, to reach the present value, after two years, we
divide
by [(1+i).sup.2] and after three years by [(1+i).sup.3]. The
value now of Rs 100 in 10 years' time is
100
------- = Rs 32
[(1 + i).sup.10]
(where i = the proportionate rate of discount. In this case,
the rate of
discount is 12%, i = 12/ 100 = 0.12). We have assumed a
discount rate of
12% simply because it is one used in some national planning
exercises and it
may reflect not too misleadingly the rate of return in
alternative forms of
investment.)
These values are
given below:
Metal Bin. Currently
priced at Rs 341 excluding transport and with a capacity
of 10.5 bags, the cost per bag is Rs 32.5. Excepting
fumigation there are no
annually recurring costs and no platform costs. All three
causes of loss are
prevented.
The gade is a
basket-type structure usually made from bamboo. Its cost
depends on its capacity. Payments from the farmer to the
basketmaker is in
kind (not cash) at the rate of 2 kg of paddy for every 40 kg
of capacity. To
calculate the money value of a kind payment, we assume a
price of Re 1 per kg
of paddy. The cost of a 75-kg capacity structure, that is,
one-bag capacity, is
then equal to Rs 3.75. The cost of the improved platform is
Rs 5.1 per bag.
Total initial cost is therefore Rs 8.85.
The cost of the new
mud coat each year is given as Rs 0.5 (based on an actual
amount of Rs 8 for a 16-bag structure which is about
average). The other
annual recurring cost is fumigation. Total annual recurring
cost is therefore Rs
1.25.
Improved Puri. The
cost each year of the structure construction is approximately
Rs 0.80 per bag after allowing for reuse of the straw. The
structure is
rebuilt each year. The cost of the improved base is Rs 4.2
per bag. Insect losses
are not preventable because fumigation is not possible.
The life span of all
permanent structure/platforms is conservatively estimated
as 15 years.
The cost of
fumigation (1 EDB ampule) is assumed to be Rs 0.75; one
fumigation only is given at the time of initial storage.
Loading/unloading
and cleaning costs are excluded since the puri is completely
rebuilt each year and is loaded in the actual process of
construction, but
the estimated labor costs of loading (inseparable from
construction) are
roughly the same as for the other structures.
The price of paddy
is assumed to be 1 Re per kg. The discount rate is
assumed to be 120%. It is assumed also that no credit has
been taken to
purchase any of the structures so no loan or interest
payments are due.
The costs are as
above and the benefits over the 15 years' life of the structures
are measured by the grain saved:
Rodents
2% = Rs 1.5 undiscounted
Insects
2% = Rs 1.5 undiscounted
Molds 1%
= Rs 0.75 undiscounted
From the totals at
the bottom of Table X the discounted benefits/cost are
pglxtabx.gif (600x600)
the money benefits/costs divided by the discount factor over
a 15-year period.
The discounted
benefit-cost ratios are as follows:
Metal
bin 25.58:38.23 = 0.67:1
Improved
gade 25.58:18.40 = 1.39:1
Improved
puri 15.35:10.49 = 1.46:1
The importance of
discounting is shown in the case of the metal bin. Without
discounting the benefit-cost ratio is 1.29:1 (51.25:43.75),
which implies
that for every rupee invested, a return of Rs 1 29 paise can
be expected,
whereas after discounting we obtain a return of only 67
paise, for a loss of 33
paise. We must emphasize again that the loss-levels given
are assumed only for
convenience in illustrating the approach.
The same approach
can be easily adapted to include additional factors such
as risks of fire, flood, and theft or the use of different
prices for (a) different
uses of stored grain, or (b) different removal patterns. An
important additional
factor very relevant in some states now for the metal bin is
the cost of
credit. Further refinements can be introduced by examining
how sensitive the
results are to changes in the parameters (eg, different
price levels). Indeed, this
is an important exercise if the values used are at all
uncertain. Some subjective
factors such as the preference for a modern metal bin or
contrarily the reluctance
to switch from a traditionally used structure are more
difficult to incorporate.
In this exercise we
have ignored the question of actual storage requirements
based on production and disposal patterns. If a farmer
wishes to store 100
bags of paddy, then the theoretical choice would be between
1 puri, 4 gades
(average size of our improved gades is 25 bags though
individual gades up to
160 bags exist) or 10 metal bins. Space constraints and
possible scale economics
(which have been ignored by using average costs) then become
relevant;
both factors work in favor of larger unit capacity
structures. However, it is
also likely that, all things being equal, the percentage of
losses is inversely
related to size. In other words, the potential gross
benefits from improvements
to small structures are greater. The list of additional
factors is by no means
exhaustive; particular regions, particular crops, particular
use patterns, etc.,
will require giving different emphasis to one or another
factor but these can be
incorporated as needed and still allow meaningful
comparisons through the
benefit-cost ratio.
Finally, we should
note that a parallel approach can be used to estimate
"social" benefit cost ratios from an extension program
for storage improvement
though this involves including (a) additional costs of the
extension program
and the associated administrative overheads, and (b) a set
of prices that
reflects real social values rather than using direct market
prices.
SELECTED REFERENCES
ADAMS, J. M. A bibliography on post-harvest losses in
cereals and pulses with particular reference
to tropical and
subtropical countries. Trop. Prod. Inst. G 110 (1977).
ADAMS, J. M., and HARMAN, G. W. The evaluation of losses in
maize stored on a selection of
small farms in
Zambia with particular reference to the development of methodology. Trop.
Prod. Inst. G 109
(1977).
ASIAN PRODUCTIVITY ORGANIZATION. Training manual:
Post-harvest prevention of
waste and loss of
food grains. APO Project TRC/1X/73, Asian Productivity Organization,
UNIPUB (1974).
van BRONSWIJK, J. E. M. H., and SINHA, R. N. Interrelations
among physical, biological,
and chemical
variates in stored-grain ecosystems; a descriptive and multivariate study.
Ann. Entomol.
Soc. Am. 64(4): 789 (1971).
BROWN, R. Z. Biological factors in rodent control. U.S.
Public Health Service, Communicable
Disease Center
Training Guide - Rodent Control Series (1960).
CHRISTENSEN, C. M. Storage of cereal grains and their
products. Am. Assoc. Cereal Chem.: St.
Paul, MN (1974).
CHRISTENSEN, C. M., and KAUFMANN, H. H. Grain storage: The
role of fungi in quality
loss. Univ. Minn.
Press: Minneapolis, MN (1969).
COTTON, R. T. Insect pests of stored grain and grain
products. Identification, habits and
methods of
control (out of print). Burgess Pub. Co., Minneapolis, MN
1963).
FOOD AND FEED GRAIN INSTITUTE, KANSAS STATE UNIVERSITY.
Grain storage and
marketing short
course outlines (in English-Spanish-French). A. Fundamentals. B. Grain
inspection and
grading. C. Handling, conditioning and storage. D. Sanitation. E. Marketing,
operations and
management. Mimeo. Dep. Grain Sci. and Ind., KSU, Manhattan
(1976).
GREIFFENSTEIN, A. C., and PFOST, H. B. Moisture absorption
of bulk stored grain under
tropical
conditions. Res. Rep. No. 6. Food and Feed Grain Inst., Kansas State Univ.,
Manhattan (1974).
HALL, D. W. Handling and storage of food grains in tropical
and subtropical areas. FAO Agric.
Devel. Paper No.
90 (1970).
IDRC. Rice postharvest technology, ed. by E. V. Araullo, D.
B. De Padua, and M. Graham.
International
Development Research Centre, Ottawa, Canada (1976).
LINDBLAD, C., and DRUBEN, L. Small farm grain storage.
Action/Peace Corps, Program and
Training Journal,
Manual Series No. 2, Washington, DC, or Volunteers in Technical
Assistance, Vita
Publications, Manual Series No. 35E (1976).
MONRO, H. A. U. Manual of fumigation for insect control (2nd
ed.). (In English-French-Spanish.)
FAO Agric. Devel.
Paper No. 79 (1969).
MUNRO, J. W. Pests of stored products. Hutchinson & Co.,
Ltd.: London (1966).
PEDERSEN, J. R., MILLS, R. B., PARTIDA, G. J., and WILBUR,
D. A. 1974. Manual of
grain and cereal
product insects and their control. Dep. Grain Sci. and Ind., Kansas State
Univ., Manhattan
(1974).
PHILLIPS, R., and UNGER, S. G. Building viable food chains
in the developing countries.
Special Report
No. 1. Food and Feed Grain Inst., Kansas State Univ., Manhattan (1973).
PINGALE, S. V., KRISHNAMURTHY, K., and RAMASIVAN, T. Rats.
Food Grain Technologists'
Research
Association of India, Hapur (U.P.), India. Kapoor Art Press, Karol Bagh,
New Delhi, India
(1967).
RAMIREZ, G. M. Almacenamiento y conservacion de granos y
semillas, 2a impresion. Compania
Editorial
Continental, S. A. Mexico, Espana, Argentina, Chile, Venezuela (1974).
SINHA, R. N. Uses of multivariate methods in the study of
stored-grain ecosystems. Environ.
Entomol. 6(2):
185 (1977).
SINHA, R. N., and MUIR, W. E. Grain storage: Part of a
system. Avi Pub. Co.: Westport, CN
(1973).
WORLD FOOD PROGRAM. Food storage manual. Part I, Storage
theory. Part II, Food and
commodities. Part
III, Storage practice. Commodity and Technical Index. Prepared by
Tropical Stored
Products Centre, Ministry of Overseas Development, Slough, England
(1970).
WYE, A. J. Selected bibliography on improving farm storage.
Trop. Stored Prod. Inf. 21: 13
(1971).
INDEX
Accuracy, 45, 77
Baseline procedures, 83, 119
Bias, 1, 7, 39, 45
Boerner divider, 149
Bourne, 11
Confidence limits, 45
Consumption, relation to loss, 135
Cost/benefit analysis, 1, 145
Cowpeas, 83
Culture, 29, 39
Damage assessment, 101, 109
Data-record sheet, field and laboratory, 123
Domestic organization, 39
Drying losses, 59, 67
Dust, effect on volume, 83
Emergence holes, 77, 83
Estimations, 1, 77
Expert judgments, 77
Food defined, 11
Frass, 77
Fungal damage defined, 77
Grain pipeline, 15
Grain storage, 109, 187
Grinding losses, 67
Guesstimates, 1, 77
Household losses, 77, 101
Interventions/intervention points, 1
Leaks, 19
Loss-causing factors, 25
Loss defined, 11, 77, 139
Loss measurements, 67
Loss points, 19
Loss reduction, 7
Losses (cleaning and winnowing, drying, par-
boiling, hulling,
polishing), 59, 67
Losses due to microorganism growth, 95
Maize losses, 59, 67, 83
Map sampling coordinates, 163
Market price/market value, 145
Meters, moisture, 119, 129, 167
Moisture measurements, 119
Moisture meters, 119, 129, 167
Moisture-proof container, 123
Moisture reference tests, 119
Mold toxins, 7
Mycotoxins, 7
Paddy losses, 59, 67, 83
Pattern of loss, 135
Pilferage defined, 77
Pipeline concept, 7, 19
Postharvest defined, 11, 77
Postharvest price structure, 145
Post production, 11
Preharvest, 11
Probes, 149
Probing techniques, 149
Processing losses defined, 77
Pulses, 83
Questionnaire, 63
Random numbers, 163
Random samples, 45, 163
Rapid loss appraisal, 25
Rate of microbial growth, 95
Representative samples, 45
Resource allocation, 19
Rice, 83, 187
Rodents, 101, 109
Row-centimeter measurements, 117
Sample dividers, 149
Sample reduction, 149
Sample selection, 163
Sample sieving, 149
Sampling, bag, 149
Sampling, stack, 149
Sampling methods, 49, 149
Sampling stratification, 49
Sampling survey design, 49
Social factors, 39
Sorghum, 83
Storage, 187
Threshing losses, 59, 67
Time, effect on loss, 135
Tradition, 29
Triers, 149
Unit weight changes due to mold, 95
United Nations General Assembly, 1
Visual loss estimates, 117
Volume/weight determination, 83
Weight loss determination, 83, 95, 119
Wheat losses, 59, 83
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