1. Comparison of seven methods for stored cereal losses to insects for their
application in rural conditions
Miguel E. Alonso-Amelot*, Jorge Luis Avila-Núñez
Grupo de Química Ecológica, Facultad de Ciencias, Universidad de Los Andes, Mérida, 5101- Venezuela
a r t i c l e i n f o
Article history:
Accepted 24 January 2011
Keywords:
Wheat
Barley
Loss assessment
Insect damage
Sitophilus oryzae
One thousand grain mass method
a b s t r a c t
There are several methods for assessing harvest losses during storage with varying degrees of accuracy,
reliability and practical application, however, field conditions may limit their use among subsistence
farmers and traders in developing nations. We compared seven standard grain loss methods during
natural and controlled infestation by Sitophilus oryzae L. in wheat and barley to select the best procedures
for use in farm storage. Methods tested were: 1) visual inspection of infested lots, 2) uncorrected weight
loss, 3) modified standard volume/weight ratio, 4) grain count and weight, 5) percentage of damaged
grains converted to weight loss, 6) one thousand grain mass, and 7) one thousand grain mass including
dust. Previously disinfested cereal lots (wheat, barley, 500 g fresh w) were exposed to 20 newly emerged
adult S. oryzae for 90 d at 28
C and 70% r.h. Naturally- infested wheat lots were also monitored under the
same conditions. Before and after this period, fresh and dry weight, number, moisture content of
uninfested and damaged grains, weight of 1 L of seeds and dust produced by insect activity, fresh and dry
weight of 1000 kernels, and number of adult weevils was determined and applied to appropriate
equations of methods (1)e(7). Grain mass loss estimations varied by wide margins (9.3 Æ 1.3% to
25.8 Æ 2.3% in barley, 2.2 Æ 0.7% to 12.5 Æ 2.5% in wheat) depending on method employed, suggesting the
need for careful selection of the most appropriate procedure under field conditions and farmer/trader
interests. While accurate procedures such as method 7 provided dependable results, methods 3 and 5
appear most practical for wheat and barley.
Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction
Securing adequate sources of food is one of the most urgent
problems today in the great majority of developing nations. Many
of the cultivated areas in these countries are characterized by small
family-owned farms and ejidos (communal land holdings) which
must cope with unsophisticated techniques of cultivation, storage,
monitoring and control of harvest losses, and marketing. Despite
their fragility, a significant portion of food safety rests on their well
being and will continue to do so in the foreseeable future (Poulton
et al., 2010). However, these farmers face marketing abuse by
unscrupulous local traders (Vásquez-Arista et al., 1995) at the time
of selling their crop production. The quality of grain is of paramount
importance during this trading to establish a fair price for the
farmer (Compton et al., 1998a). It should be to the advantage of
growers to learn how to assess this quality and the extent of crop
losses knowledgeably before trade bargaining takes place.
Cereals continue to be the main source of alimentary calories and
proteins in most countries within the intertropical band (Alonso-
Amelot et al., 2009) but harvest losses due to pests continues to
be of great concern. Insects fare as one of the most damaging pests of
all. The classical work of Cramer (1967) on tropical rice estimated
losses at 34.4% due to all insects, whereas all other diseases reached
only 9.9%. Insects alone accounted for a 14% loss in rice yield in
Africa. This aging work has been referenced many times by recent
reviews thus endorsing its current status all over the world (Boxall,
2001; Oerke, 2006) which is compounded by more dramatic
occurrences found locally, as revealed for instance by up to 76% loss
in maize stored without insecticide protection in Zimbabwe farms
(Giga et al., 1991).
A large portion of tropical African, Asian and Latin American land
is under an unimodal and frequently highly variable rainfall pattern.
Without irrigation this limits the local production to one harvest per
year which may be highly volatile in many places leading to societal
instability (Dorosh et al., 2009). Frequently grains must be stored for
the rest of the year in low tech deposits in small farms while it is
* Corresponding author. Present address: Av. Joan Fuster 22-A, 2
, pta 4, Dénia
03700 Alicante, Spain. Tel.: þ34 965787578.
E-mail addresses: alonsome123@yahoo.com (M.E. Alonso-Amelot), jlavila@ula.ve
(J.L. Avila-Núñez).
Contents lists available at ScienceDirect
Journal of Stored Products Research
journal homepage: www.elsevier.com/locate/jspr
0022-474X/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jspr.2011.01.001
Journal of Stored Products Research 47 (2011) 82e87

2. either sold or consumed in the household or village (Golob et al.,
2004). For example, in normal years up to 32% of harvested maize
remained in stores for 12 months in Tanzania without industrial
insecticide treatment in the 1990 decade (Golob et al., 1999). Inad-
equate storing conditions or insect/mold contamination from the
field and increased susceptibility of hybrid strains may lead to
greater damage in proportion to storage time without pest
management counter-measures (Braga-Caneppele et al., 2003).
An imperative among the cultivation and harvesting strategies is
the assessment of damage caused by insects in cereal crops, either by
farmers themselves, or by traders, and technicians in animal farms in
which grain feeds remain stored (Adams and Schulten, 1976;
Rajendran and Parveen, 2005). Damage may be prevented by
shortening storage time or by monitoring and application at an early
stage of adequate treatments financially and practically accessible to
poor communities (e.g. Farrell et al., 1996; Stathers et al., 2002; Cox,
2004; Epidi and Odili, 2009).
Loss estimates vary greatly depending on the assessment
method. There are many popular procedures but some are not
sufficiently accurate. While grain batch weight loss or damaged vs
undamaged grain counts are popular estimates, variations in mois-
ture content or differences in individual appraisal derail valid
assessments and regional surveys. Others employ a variety of tech-
niques without universally accepted standardization. Hossain et al.
(2007) estimated susceptibility to rice weevil of selected quality
protein maize hybrids by weight loss. Demissie et al. (2008) assessed
damage by maize weevils by hand inspection of corn ears using
a 1e5 categorical scale from slight damage (10e20%) to extremely
heavy damage (90e100%), a trendy method among village farmers
which may be recalculated rather loosely into weight loss (Compton
and Sherington, 1999). Arannilewa et al. (2006) evaluated maize
weevil damaging activity in Aristolochia-treated grains by the
percentage of holed grains and the weevil perforation index of
Adedire and Ajayi (1996). Others deem ‘damaged grain’ as kernels in
which an insect has completed its life cycle inside it (Santos, 2007), or
total loss of germination capacity (Haile, 2006) while still others take
into consideration insect-born mold damage (Braga-Caneppele et al.,
2003). Within the variety of grain insect pests, some species cause
visible damage eholes, crevices, moldy cracks- but others remain
concealed within the kernels causing assessment difficulties and
dissatisfaction (e.g. Schulten,1975). At the cereal industry level much
more sophisticated laboratory methods (Neethirajan et al., 2005;
Singh et al., 2009) solve most of these problems but costs limit
their use to a lesser proportion of the grain harvested in developing
countries and are definitely not applicable at the farm level. More
research in this area to develop new grain loss methods has been
suggested (Boxall, 2002).
Under prevalent squalid conditions of many producers in
developing countries rapid and accessible grain loss methods are
required. There are several methods available for this purpose
(Harris and Lindblad, 1978) but it is not easy to establish which
method reflects the real loss more closely and reliably under small
farm conditions. In this context, a laboratory experiment was
designed in which kernels of wheat (Triticum sativum Lam.) and
barley (Hordeum vulgare L.) were subjected to artificial infestation
by adults of the rice weevil Sitophilus oryzae L. (Coleoptera: cur-
culionidae), the most common pest of these cereals in the tropics.
Seven popular grain loss methods were applied simultaneously to
the infested lots to compare results in search for the method with
the best dependability/labor ratio and more consistent results.
Equally important was the ease of application under field condi-
tions resembling a small cereal farm. Naturally infested wheat lots
were treated likewise. To our knowledge this has not been per-
formed for more than three different methods simultaneously (e.g.
Reed, 1987; Braga-Caneppele et al., 2003).
2. Materials and methods
2.1. Cereal grains
Dehulled wheat batches were obtained in threaded plastic sacs
from local producers in the region of Mucuchíes, Mérida State,
Venezuela, at 2900 m elevation where common grain beetles are
absent due to year round night-cold air temperatures. Therefore,
the use of insecticides on wheat plantations is unnecessary or
minimal. However, as infestation could have occurred in storage
(see next section) grains were frozen for several days to kill unde-
tected larvae. Broken kernels were assessed visually at 3% in all
batches, to neutralize the differential contribution of insect attack,
as a correlation between broken hulls content and progeny
production of certain grain insect pests such as Rhizopertha
dominica F. (Chanbang et al., 2008) or alteration of Sitophilus oryzae
feeding behavior (Trematerra et al., 1999) have been observed.
Dehulled, pearled barley was bought at the main produce market of
Mérida city, which was imported in hermetic plastic containers
from farmers in the Departamento Norte de Santander in Eastern
Colombia, showing 2% of broken seeds. Exposure of various grain
insect pests from our lab collection such as Oryzaephilus sur-
inamensis L., Sitophilus oryzae, and Tribolium castaneum (Herbst.) to
these wheat and barley lots did not result in increased adult
mortality after three months relative to controls on clean grain used
for insect stock maintenance, thus discarding pesticide residual
effects. The m.c. of all cereal lots employed was obtained by heating
at 80 C in a ventilated oven and until constant weight and
comparing initial and final weights. Wheat and barley bulk lots of
10 kg were cleansed of dust and plant residues and six 250 g sub
samples were visually examined in search of live insects or traces of
insect activity (holes, dead bodies or body parts), finding none. Six
untreated 500 g wheat samples were placed in glass jars capped
with cheese cloth tightened with a rubber band, and placed in the
growth chamber for 6 weeks at 28 C and 70% Æ 2% r.h. and a 12/12 h
photo regime to determine if occult colonization was present. All
samples of wheat were infested (Table 1). Insect production and
weight loss was determined in these batches. The experiment was
repeated with three 500 g replicates of a given lot under the same
conditions for 90 d to assess the natural impact of insects. For the
insect induced infestation experiments fresh wheat lots without
apparent insect activity were disinfested of possible hidden
arthropods by freezing at À20 C for five days, and m.c. was adjusted
to 10e11% by heating at 60 C in a ventilated oven until the desired
moisture level was reached. No insects could be observed in fresh
barley or after 6 weeks of exposure at 28 C, probably as a result of
the closed plastic containers used in market storage. Before use,
barley was cleansed of residual insecticides with running water and
dried in a ventilated oven at 60 C until 10e11% m.c. was obtained.
Table 1
Insect (Sitophilus oryzae) adult populations and loss of grain quality in wheat due
natural infestation of a commercial seed batches selected at random from a Mérida
city main market, after 90 days at 28 C, 70% RH and 12/12 photo regime. Results of
three replicates per sample: Means Æ SDa
Batch N
adult
insects/kg of kernels
% of damaged
kernels
% dry weight loss (DW)
1 2816 Æ 110a
10.7 Æ 0.6a
5.9 Æ 0.2a
2 2940 Æ 112a
11.6 Æ 0.5b
6.4 Æ 0.2a
3 3140 Æ 134a
14.6 Æ 0.9c
6.5 Æ 0.2a
4 3552 Æ 189b
15.4 Æ 1.2d,e
8.2 Æ 0.3b
5 4220 Æ 224c
16.4 Æ 1.3d,e
9.2 Æ 0.4c
6 5304 Æ 281d
18.2 Æ 2.1e
9.6 Æ 0.5c
a
Means in columns followed by the same letter are not statistically different
(KruskaleWallis, P 0.05).
M.E. Alonso-Amelot, J.L. Avila-Núñez / Journal of Stored Products Research 47 (2011) 82e87 83

3. Successful colonization by adding T. castaneum, S. oryzae and
O. surinamensis adults confirmed the absence of residual pesticides.
2.2. Insects and insect infestation
Newly emerged (3 d-old) adults of Sitophilus oryzae were
obtained from the collection of the Laboratory of Chemical Ecology
of this University which was established since 1991 from local
strains reared on wheat, barley and maize grains, without any
previous exposure to insecticides (Alonso-Amelot,1992). A one liter
sample of each cereal was measured using a graduated glass
cylinder and its weight determined (Æ0.1 g, 10 replicates). Five
hundred gram samples (¼ Wu, uninfested grain) of wheat and
barley (Æ0.1 g, three replicates) were prepared in clean plastic 1 L
pots. Parameters of Table 2 were measured. At time zero, 20 three
days-old (after emergence from hulls) unsexed rice weevils were
placed in each pot which was then capped with cheesecloth and
tightly closed with a rubber band. Pots were placed in a growth
chamber at 28 C, 70% Æ 2% r.h. and a 12 h/12 h photo regime, and
left undisturbed for 90 d. After opening the pots the parameters of
Table 3 were determined. In addition, three 100 g sub samples were
sifted through a dust screen to separate whole kernels from dust
stemming from insects activity and both were weighted (Wdust, and
Wdam, respectively) and corrected for the entire pot.
2.3. Grain loss methods
After induced infestation with S. oryzae adults grain losses in
wheat and barley were evaluated by application of seven methods.
First, nine 50 mL grain aliquots measured with the aid of a container,
e.g. a small drinking metal glass filled to the rim, were individually
spread over a table, preferably light-colored for better contrast.
Damaged (N50d) and undamaged kernels (N50u) were separated by
visual inspection, counted and their proportions determined by
equation (1) for each aliquot:
Xrel ð%Þ ¼ ½N50d=ðN50d þ N50uÞŠ Â 100 (1)
Second, nine representative 100 g (Æ0.1 g,) samples of kernels were
cleansed of dust and debris with the aid of a metal sieve and
weighted (fresh) before ðW1Þ and after ðW2Þ the storage period.
Dust from the last sampling was collected and weighted WðdustÞ.
Loss (%) was estimated as:(eq (2)).
Xrelð%Þ ¼ ½ðW1 À W2 À WdustÞ=W1Š  100 (2)
Third, a 1 L sample of grain was weighted (Æ0.1 g, fresh) in triplicate
at the beginning of the storage period (W1). Moisture content was
determined as described above also in triplicate. After the time of
storage ended, grain lots were sieved and dust collected and
weighted WðdustÞ. The grain body was homogenized by moderate
shaking. Nine 50 mL grain samples were drawn randomly and their
fresh (W2) and dry weights determined. Relative loss weight was
calculated by equation (3) (Reed, 1987):
Xrelð%Þ ¼ ½ðW1 À W2 À WdustÞ=W1Š  100 (3)
Next, all fresh weights were transformed into dry weight using
equation (4):
WiðdryÞ ¼ Wi  ð100 À %HÞ (4)
A fifth method compared the weight and number of undamaged
and damaged grains in the sample to determine their weighted
proportions (Compton et al.,1998b). Only one evaluation needs to be
performed at the time of selling or consuming the grain lot. At the
end of the insect infestation period (no previous evaluation at the
beginning of storage was required), grain lots were homogenized by
moderate shaking and nine 50 mL samples from each replicate were
drawn. Undamaged and damaged kernels were separated by visual
inspection. The number of grains and their weight in each group was
determined, filling in variables N50d; N50u; W50d and W50u in equa-
tion (5) for damaged and undamaged kernels, respectively.
Xrelð%Þ ¼ f½ðW50u  N50d À W50d  N50uÞŠ=½W50u  ðN50u
þ N50dÞŠg  100 (5)
Table 2
Wheat and barley condition before exposure to Sitophilus oryzae adults. Wheat A and
B are lots destined for induced and natural insect infestation, respectively. Fresh
Weights unless otherwise stated. means of N replicates Æ SDa
Parameter N Barley Wheat A Wheat B
Batch weight (g) Wi 3 500.2 Æ 0.5a
500.5 Æ 0.5a
499,9 Æ 0.5a
% moisture %H1 10 10.7 Æ 0.3a
11.9 Æ 0.3b
11.6 Æ 0.3b
Dry weight of
1000 kernels (g)
W1000k 9 20.9 Æ 1.7a
39.0 Æ 1.2b
38,88 Æ 1.90b
N
kernels in 50 mL N50u 9 1617 Æ 116a
861 Æ 38b
876 Æ 46b
N
kernels/1 L N1000L 9 32345 Æ 2320a
17212 Æ 764b
18222 Æ 752b
Weight of 1 L of
kernels
W1L 10 823.8 Æ 8.3a
762.3 Æ 48.1b
759.7 Æ 51.0b
a
Means in rows followed by the same letter are not statistically different
(KruskaleWallis, P 0.05).
Table 3
Data colleted from the experimental exposure of 500 g batches of barley and wheat to 20 recently emerged Sitophilus oryzae adults during 90 days at 28 C, 70% RH and 12h/12h
light/dark regime. Wheat A is the experimentally infested grain with 20 adults at time zero, and wheat B is the naturally infested grain maintained under the same conditions.
Weights are fresh unless otherwise stated. Values are means of N replicates Æ SDa
Parameter N Barley Wheat A Wheat B
At the end of the experiment:
Final batch weight (*) (g) Wf 3 407.0 Æ 7.0a
457.2 Æ 7.3b
465 Æ 5.1b
Final % moisture %H2 10 14.2 Æ 0.4a
15.1 Æ 0.3b
14.9 Æ 0.b
Dust weight (g) Wd 3 13.1 Æ 3.3a
2.2 Æ 0.2b
1.7 Æ 0.7b
Grain weight loss per batch (g) DW 3 93.0 Æ 7.0a
42.8 Æ 7.3b
35.2 Æ 5.1b
N
unaffected kernels in 50 mL N50u 9 1244 Æ 188a
751 Æ 34b
806 Æ 63b
N
affected kernels in 50 mL N50a 9 374 Æ 85a
108 Æ 23b
134 Æ 30b
Affected kernels (%) %a 3 20.4 Æ 6.7a
12.5 Æ 2.6b
14.5 Æ 2.5b
Weight of unaffected kernels in 50 mL W50u 9 26.9 Æ 2.4a
34.0 Æ 1.3b
35.2 Æ 2.5b
Weight of damaged kernels in 50 mL W50a 9 3.5 Æ 1.4a
3.9 Æ 0.8a
5.1 Æ 1.3b
Dry weight of 1000 unaffected kernels (g) TGM1 9 18.3 Æ 1.8a
39.9 Æ 0.9b
38.4 Æ 0.7b
Dry weight of 1000 kernels in damaged lot (g) TGM2 9 16.4 Æ 1.4a
37.6 Æ 0.9b
36.3 Æ 0.5b
Total adult insects found (per kg) 3 4394 Æ 390a
2056 Æ 623b
1605 Æ 156c
Live adults (%) 3 60.2 Æ 1.5a
62.4 Æ 1.1a
62.1 Æ 1.0a
(*) After sifting out dust.
a
Means in columns followed by the same letter are not statistically different (KruskaleWallis, P 0.05).
M.E. Alonso-Amelot, J.L. Avila-Núñez / Journal of Stored Products Research 47 (2011) 82e8784

4. The sixth method was done by converting the percentage of
damaged grain to weight loss. This is a variant of method 2. A
conversion factor (CF) to % of lost mass was multiplied by Xrelð%Þ in
equation (1). CF has been estimated for various cereal species
(Schulten, 1975). For barley, we estimated CF at 0.55. A seventh
method was done to correct some common sources of error by
considering the dry weight change of a grain biomass after a storage
period which may be infested by all kinds of damage, insect, mold,
microorganisms or other (Proctor and Rowley, 1983). Representa-
tive 1 L samples were drawn from sacs of grain (N ¼ 10). From each
sample three 50 mL sub samples were obtained; this volume carried
1500-1700 barley grains or 800e900 wheat kernels. The exact
number was counted (N1), weighted fresh (W1) and moisture
content of the grain lot determined (%H1) in ten replicates for each
lot by the procedure described above. Three 1 L samples were
selected randomly. Three 500 g subsamples were stored in 1 L
plastic pots and infested with rice weevils as described above. The
one thousand dry mass ðTGM1Þ of this grain was calculated by
equation (6),
TGM1 ¼ 1000 Â W1 Â ð100 À %H1Þ=ðN1 Â 100Þ (6)
TGM1represented M1 for the initial conditions.At the end of the
infestation experiment the procedure was repeated after sieving
and homogenizing the grain samples in 50 mL aliquots (9 repli-
cates) for each lot replicate. TGM2 was determined using equation
(6) again. Percentage of lost mass was calculated by equation (7),
Xrelð%ÞðTGMÞ ¼ ½ðTGM1 À TGM2Þ=TGM1Š  100 (7)
The final loss method was done to incorporate the dust fraction. The
principle was the same of the TGM method except that the dust
fraction of each 500 g lot was weighted (Wd) and from its moisture
content (Hd) its dry weight was obtained. The dust fraction of the
50 mL aliquots was estimated dividing Wd by 20 and inserted into
equation (8),
Xrelð%ÞðTGM þ dustÞ ¼ A þ B; where A ¼ Xrelð%ÞðTGMÞ; and B
¼ ½ðWd=20Þ Â ð100 À %HdÞ=ðTGM1  100ÞŠ
(8)
2.4. Statistical analysis
Thedatawere analyzedcomparatively by the KruskaleWallisone-
way non-parametric AOV test at p 0.05 for statistical differentiation
and performed with Statistix Analytical Software V 7.0 (Tallahase,
Florida, USA). Curve fitting was achieved using Microcal Origin V.5
(Microcal Software Inc., Northampton, Massachussets, USA).
3. Results and discussion
3.1. Natural infestation of local wheat
Despite the lack of Sitophilus spp. and other pests in the field
where wheat lots were cultivated, wheat destined to human
consumption was spontaneously infested with weevils from other
cereals sacks during market storage. All six 500 g lots taken
randomly from 50 kg plastic fiber sacks exposed for sale in the local
Mérida general produce market showed prolific infestation of
Sitophilus oryzae after 90 d at 28 C (Table 1). The adult population
continued to expand at an enormous rate, increasing by 50% after
eight additional days (d 98) and causing considerable damage. An
off-odor emanated from the lots which evidenced mold growth due
to increased moisture and spore spread by insect activity. Thus,
locally produced grain in small (2 Ha) high elevation farms mar-
keted in sacks at local markets in Mérida becomes contaminated
with stored product insects (weevils) from other grains when
brought to warmer places, mainly from maize in which S. oryzae
was a dominant species.
3.2. Insect and insect infestation
Clean and disinfested (À20 C) wheat and barley kernels (Table
2) were colonized successfully by implanted S. oryzae which
inflicted considerable damage after three months under growth
conditions (28 C, 70% r.h.) (Table 3). Spoilage was comparable to
wheat controls without previous thermal disinfection. Table 3
collects all parameters required for the application of the assess-
ment methods.
Differences in S. oryzae performance were observed in the two
cereals. Barley was a better medium than wheat for reproductive
success, because over twice the number of adults (Table 3) was
found in the former grain despite the smaller size of the kernels. At
the same time, no difference in adult size and weight between the
two cereal lots was recorded, suggesting nutritional sufficiency in
both (data not shown). The organoleptic quality and general aspect
of the grain lots was poor after 90 d exposure to weevil activity and
their selling value was probably null. It was of interest to compare
this preliminary judgment with the quantitative assessment
provided by established methods using the data of Table 3.
3.3. Grain loss
Data in Table 3 were applied to equation (1)e(8) for a quanti-
tative appraisal of grain lot loss after S. oryzae activity during the
three months of the experiment. Results of all methods are shown
in Table 4. Results varied widely from a low Xrelð%Þ ¼ 2:3 Æ 0:7% in
naturally infested wheat using the grain count and weight proce-
dure, to a high Xrel% ¼ 14:5 Æ 2:8%ðP ¼ 0:0003Þ provided by the
visual method. Artificially infested barley showed values of
Xrelð%Þ ¼ 9:4 Æ 1:3% and 25:8% Æ 2:3%ðP ¼ 0:0003Þ , respectively.
Similar discrepancies have been recorded in the past. For example,
Braga-Caneppele et al. (2003) reported Xrel(%) ¼ 2.3, 4.7, and 21.0%
following the assessment methods of Harris and Lindblad (1978),
Compton et al. (1998b) and simple weight difference, respec-
tively, in maize seeds infested with five maize weevils (Sitophilus
zeamais L.) for 90d at 25 C. In our case, visual appraisal and grain
count and weight procedures consistently furnished worst and best
scenarios, respectively, for the grain producer, and the opposite for
the trader. The fact that visual inspection is in general use in small
villages and does not require any other equipment than a small
50 mL cup gives the upper hand to the trader, thus keeping the
grain price artificially and unfairly low.
However, some of the tested procedures converged towards
comparable results: methods 3À7 (P ¼ 0.193) for barley and 3, 5À7
(P ¼ 0.068) for wheat, in both spontaneously and experimentally
infested grain (wheat A and B, Table 4). According to these methods
in artificially infested grain, barley sustained greater damage
(9.4 Æ 1.3 to 12.4 Æ 3.5%) than wheat (5.6 Æ 0.8 to 6.6 Æ 1.3%) under
similar conditions (P ¼ 0.0003) for TGM þ dust values). This result
is consistent with the larger number of adult individuals emerging
in the barley lots on day 90.
Conversion factors CF used in the calculation of % damaged
grains converted to weight loss (method 5), although easily appli-
cable in the field, may vary and require verification of published
values (Harris and Lindblad, 1978) with locally determined ones
because of the sensitivity of equation (5) to its product by CF.
However, the consistency of results of method 5 relative to TGM
(6e7) in all three grain lots, which is certainly more thorough but
difficult to apply in the small homestead, suggests that % damaged
grains converted by CF to mass loss becomes a practical and expe-
dite means to evaluate losses in surveys and individual farms. At any
M.E. Alonso-Amelot, J.L. Avila-Núñez / Journal of Stored Products Research 47 (2011) 82e87 85

5. rate, while the count and weight procedure (method 4) gave
consistent and comparable results with other methods in barley, it
grossly underestimated weight losses in wheat (e.g. 2.2 Æ 0.7% vs
6.0 Æ 0.9% from TGM, P ¼ 0.0004) and thus would not be as
generally dependable as other methods. However, it yielded a more
realistic value by consideration of moisture content as in the stan-
dard volume/dry-weight procedure (method 3). This could be
attributed to the increment in mass due to greater moisture as
a result of insect activity, respiration and more exposure to hygro-
scopic starch inside damaged kernels to atmospheric humidity,
which artificially reduced loss. Also, grains in open storage are
known to absorb and release moisture constantly to the point that,
at low infestation levels, negative Xrel(%) values may be observed
occasionally. This discrepancy was not recorded in barley and
reasons remain unknown.
The TGM method applied to barley and wheat under our
experimental conditions, although theoretically better supported,
does not offer advantages over the % damaged grains converted to
weight loss (method 5). However, when dust is accounted for in the
calculations (method 7) a more realistic loss is obtained in barley
although it seems to offer no advantages in wheat. Despite housing
different loads of weevils naturally and experimentally infested
wheat lots examined in this study sustained comparable damage
(Table 3). Although dispersed linear correlations between insect
infestation and weight loss (r2
¼ 0.6050) are on record (Braga-
Caneppele et al., 2003), our data (Table 1) showed a lower propor-
tional damage increase at higher insect densities (2000 adults/kg).
Grain weight loss was well correlated with weevil population (Table
1) through a second degree polynomial (r2
¼ 0.9823, P ¼ 0.0023).
Greater internal competition for available resources and canni-
balism, and the expected exponential growth of weevils population
may explain this observation.
While equipment required by these methods and calculations
remains simple, it may surpass the financial and educational
capacity of a large body of small farm holders in third world coun-
tries. Post-harvest mobile field technical services possessing such
facilities under government support or subsidized private operators
using the described methods, particularly method 5, could provide
adequate solutions for production, conservation of stored cereals,
a fair market price and an aid to escape subsistence farming poverty
traps. In addition, these services could become part of integrated
food security programs in farming communities and help design
integrated pest management policies.
4. Conclusions
1. Simple visual evaluation and classification of damaged and
undamaged kernels furnish a distorted and exaggerated esti-
mation of true mass loss.
2. Methods based on dry mass give a more realistic figure (e.g. vs.
uncorrected weight loss) as previously established.
3. The grain count and weight procedure (method 4) should not
be used in wheat loss assessments. However it furnishes
comparable results in barley. This disparity calls for further
studies and refinements when applied to other cereal grains
and pulse species.
4. Of the methods based on dry mass, the best dependability/
labor ratio under the particular conditions of the experiment
here presented is % damaged grains converted to weight loss
(method 5).
5. Inclusion of dust weight in the assessment of mass loss may be
of importance under large insect loads in barley and certain
insects species such as S. oryzae whose feeding behavior causes
large amounts of debris.
Acknowledgements
Authors acknowledge the financial support of Interamerican
Development Bank, grant QF-01, and Fondo Nacional de Ciencia,
Tecnología e Innovación, FONACIT, of Venezuela, grant CONICIT S1-
97001302. Authors are grateful to Dr. Luis Daniel Otero, of Labo-
ratorio de Ecología de Insectos, Departamento de Biología, Facultad
de Ciencias, Universidad de Los Andes, Mérida, for taxonomic
advice. The authors thank Dr. Frank Arthur of the Center of Grai-
nand Animal Health Research, Manhattan, Kansas, for his contri-
bution to the manuscript quality.
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a
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