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Bruchid species like Acanthoscelides obtectus (Coleoptera) and Zabrotes subfasciatus (Coleoptera) cause significant storage losses for African common bean producers. The value of storage protection to a market-oriented farmer is a function of price seasonality, value loss prevention, and their respective opportunity costs of capital. Evidence suggests that hermetic technologies like Purdue Improved Crop Storage (PICS) bags could be effective against key legume storage pests, but sustainable technology introduction requires that it be profitable for producers. While PICS bag effectiveness against these specific common bean bruchid species is still under investigation, this analysis references dry weight loss figures from life science articles and builds on previous value loss research to provide a model for potential competitiveness and technology adoption. PICS bag profitability with one and two years use are compared with estimated profitability of leading insecticide Actellic Super (permethrin (0.3%) + pirimiphos-methyl (1.6%)), weekly solar disinfestation and sieving, and the botanicals A.indica, T. minuta, C. lusitanica, and C. ambrosiodes. The Tanzanian market regions of Mbeya, Songea, Arusha, and Kigoma are analyzed. Results show competitive profitability of PICS bags with conservative loss estimates for alternative storage technologies, with high potential for adoption in Mbeya, Songea, and Kigoma.
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1
Profitability of Hermetic Purdue Improved Crop Storage (PICS) Bags
for African Common Bean Producers
by
Michael Jones, Corinne Alexander and James Lowenberg-DeBoer
Working Paper #11-6
November 2011
Dept. of Agricultural Economics
Purdue University
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services, activities, and facilities without regard to race, religion, color, sex, age, national origin or ancestry,
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Affirmative Action institution.
2
Profitability of Hermetic Purdue Improved Crop Storage (PICS) Bags
for African Common Bean Producers
by
Michael Jones1, Corinne Alexander2 and James Lowenberg-DeBoer3
Dept. of Agricultural Economics, Purdue University
West Lafayette, Indiana 47907-2056
1 jones491@purdue.edu
2 cealexan@purdue.edu
3 lowenbej@purdue.edu
Working Paper #11-6
November 2011
Abstract
Bruchid species like Acanthoscelides obtectus (Coleoptera) and Zabrotes subfasciatus
(Coleoptera) cause significant storage losses for African common bean producers. The value of
storage protection to a market-oriented farmer is a function of price seasonality, value loss
prevention, and their respective opportunity costs of capital. Evidence suggests that hermetic
technologies like Purdue Improved Crop Storage (PICS) bags could be effective against key
legume storage pests, but sustainable technology introduction requires that it be profitable for
producers. While PICS bag effectiveness against these specific common bean bruchid species is
still under investigation, this analysis references dry weight loss figures from life science articles
and builds on previous value loss research to provide a model for potential competitiveness and
technology adoption. PICS bag profitability with one and two years use are compared with
estimated profitability of leading insecticide Actellic Super (permethrin (0.3%) + pirimiphos-
methyl (1.6%)), weekly solar disinfestation and sieving, and the botanicals A.indica, T. minuta,
C. lusitanica, and C. ambrosiodes. The Tanzanian market regions of Mbeya, Songea, Arusha,
and Kigoma are analyzed. Results show competitive profitability of PICS bags with
conservative loss estimates for alternative storage technologies, with high potential for adoption
in Mbeya, Songea, and Kigoma.
Keywords: agricultural pests, technology adoption, Phaseolus vulgaris, hermetic storage, storage
economics
JEL Codes: Q16, Q13, O33
Copyright © by <Michael Jones, Corinne Alexander and James Lowenberg-DeBoer>. All rights
reserved. Readers may make verbatim copies of this document for non-commercial purposes by
any means, provided that this copyright notice appears on all such copies.
3
Problem Statement
The common bean (Phaseolus vulgaris) has significant nutritional and economic importance in
many regions of Eastern and Southern Africa (Giga et al., 1992; Wortmann et al., 1998; FAO
STAT, 2010). In this region, bean consumption alone comprises the third largest source of
calories and the second greatest source of dietary protein (Hillocks et al., 2006). In 1998,
researchers estimated almost 40% of total African bean production was marketed, with an
average annual value of $452 million USD (Wortmann et al., 1998). Production has since grown
from 1.96 million tons in 1999 to over 2.5 million tons in 2008 (FAOSTAT, 2010). Price
seasonality is also very pronounced in many regions, with ratios of average annual price
increases estimated between 17% 59% in Tanzania, 16% 34% in Kenya, and 31% 100% in
Uganda (FEWS NET, 2010b,c,d). Effective storage of this increasingly important crop could
therefore provide significant economic returns to producers.
On-farm storage is short term though, which is largely accredited to severe losses due to
pests A. obtectus and Z. subfaciatus in inadequately protected grain stores (Giga et al., 1992).
Average dry weight losses in unprotected stores range from 10-40% in less than six months, and
up to 70% grain damage rates are recorded in the same time period (Kiula and Karel, 1985;
Khamala, 1978; Paul et al., 2009). Grain damage, generally defined as insect emergence holes in
beans, results in significant price discounts, reaching up to a 2.3% decrease in price for every
hole per 100 beans (Mishili et al., 2011). To combat these storage pests, many extension offices
promote pest control strategies such as insecticide use and/or solar disinfection, though certain
botanicals show moderate potential as storage treatments (Songa and Rono, 1998; Paul et al.,
2009). However, the moderate effectiveness of botanicals as storage protectants, the possible
health concerns from insecticide use, and the labor intensity of solar disinfection practices
provide shortcomings in their efficacy for common bean storage (Songa and Rono, 1998; Paul et
al., 2009). A new technology, Purdue Improved Crop Storage (PICS) triple-layer hermetic
storage bags, may provide an improved alternative for insecticide-free, long-term storage of
common beans with minimal grain damage (Murdock et al., 2003; Hell et al., 2010; Ognakossan
et al., 2010). This analysis evaluates the cost-effectiveness of PICS bags against other storage
technologies available to small producers in Eastern and Southern Africa.
4
Introduction
Worldwide, the common dry bean (Phaseolus vulgaris L.) is the most economically and
nutritionally important legume for human consumption (Jones, 1999). A major staple crop in
Eastern and Southern Africa, the common bean is estimated as the third-largest source of calories
and the second-largestest source of dietary protein (Hillocks et al., 2006). Dry beans are
relatively inexpensive and complement the amino acids provided by maize and rice, making
them a key factor in fighting malnutrition (Pachico, 1993; WMO, 1992). Known as the “poor
man’s meat” in Eastern Africa, common beans are among several of protein-rich plant sources
commonly cultivated and consumed by low-income households across the region (Wortmann et
al., 1998). Figure 1 displays the relative nutritive importance of dry beans among common
protein-rich plants throughout the sub-continent.
Figure 1: Relative Importance of Protein Supply from Various Different Protein-Rich Plants
Source: FAOSTAT
East African production of common beans has grown from 1.96 million tons in 1999 to
over 2.5 million tons in 2008 (FAOSTAT, 2010). Over 96 bean production areas are defined in
the African sub-continent, though the sub-humid regions of East Africa encompass 39% of all
African production (Wortmann et al., 1998). Throughout the last decade in Eastern Africa,
producers in Uganda, Tanzania, and Kenya alone represented between 59.3% (2001) and 67.1%
(2006) of regional production, as displayed in Figure 2 (FAOSTAT, 2010). Rwanda has also
recently surpassed Kenya in production with 308,000 tons in 2008 (ibid).
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Eastern Africa Middle Africa Southern Africa Western Africa Total, SSA
Sub-Saharan African Protein Supply from Protein-Rich Plants (g/capita/day)
Groundnuts
Nuts
Pulses, Other
Peas
Common Beans
5
Figure 2: Common Bean Production in Select East African Countries
Source: FAOSTAT
Women generally dominate bean production and the crop is extremely important in
subsistence farming households (Wortmann et al., 1998). In 1998, researchers also estimated
that nearly 40% of total African bean production was marketed, with an average annual value of
$452 million USD (ibid). Marketing rates are known to vary greatly among growing regions,
with particularly high rates of marketing (≥ 60%) in Northern and Northwestern Tanzania as well
as Central and Western Kenya, and particularly low marketing rates (≤ 20%) in Rwanda and
Burundi (ibid). Giga et al. (1992) reported that among studied producers in Uganda, Tanzania,
and Zimbabwe, between 55-82% of beans are marketed, 9-38% kept for household use, and 9-
34% retained for seed. Marketing rates were highest across Uganda, at 66-84% (ibid).
Figure 3 illustrates notable bean trade routes in East Africa. Large flows of domestic
trade occur between the southern highlands of Tanzania to Dar es Salaam and from Western and
Eastern Kenya to Nairobi. While the vast majority of bean marketing occurs domestically,
exports from Ethiopia, Uganda, Kenya, Rwanda, and Tanzania totaled 123,265 tons in 2008,
with a value of over $79 million USD (Wortmann et al., 1998; FAO TradeSTAT, 2010).
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
(mT)
Common Bean Production in Select East African Countries
Malawi
Burundi
Ethiopia
Rwanda
Kenya
Uganda
Tanzania
6
Figure 3: Common Bean Production and Trading Patterns in Eastern Africa
Source: Wortmann et al. (1998)
Drivers of Common Bean Prices
Price Seasonality
Price seasonality is generally driven by regional harvesting periods, which are heavily dependent
on rainfall and climate patterns. Wortmann et al. (1998) designated fourteen African “bean-
growing environments depending on rainfall patterns, soil types, and altitude and latitude range.
Planting and harvest periods, as well as post-harvest marketing strategies, may vary considerably
among these growing environments. In the Ugandan and northern Tanzanian highlands, farmers
cultivate two bean crops annually due to bimodal rainfall patterns, meaning two annual rainy
7
seasons (Giga et al., 1992). In the lowland regions of northern Tanzania, farmers have also
reported growing a third bean crop to provide seed for planting, as bruchid damage prevents
reliable long-term storage of seed (ibid).
In all regions of Tanzania, beans are planted in the middle of major rainfall periods and
harvested in the middle of the following dry-cool period (Nchimi-Msolla and Misangu, 2002).
Farmers do not plant in the beginning of the rainy season to avoid early flowering during periods
of heavy rain, and thus prevent subsequent dropping of flowers (ibid). Table 1 presents an
estimation of planting and harvest schedules in Tanzania’s diverse rainfall zones, based on
planting strategies provided by Nchimi-Msolla and Misangu (2002) and rainfall forecast patterns
for 2010 and 2011 from FEWS NET (2010a).
Table 1: Estimated Bean Planting and Harvest Patterns in Tanzania based on Rainy and Dry
Seasons
Regions
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Unimodal
Zone
Msimu Rains
Dry
Spell
Msimu Rains
P
H
Bimodal
Zone
Vuli Rains
Masika Rains
Vuli
Rains
P
H
P
H
Source: Rainfall for 2010, 2011- FEWS (2010a); Planting and Harvest periods are based on
planting and harvest around rain patterns- Nichimba (2002)
Abbreviations: (P)- Planting; (H)- Harvesting
Two annual harvest periods may provide more steady market supply, contributing to less
pronounced annual price fluctuations. For example, Table 2 displays less pronounced (nominal)
high/low month price ratios in the bimodal zones of Arusha and Dar es Salaam, at 1.17 and 1.21
respectively (FEWSNET, 2010b). In contrast, other Tanzanian regions display high/low month
price ratios of 1.33 to 1.59, with the highest fluctuations in Kigoma, on the northwest border with
Burundi. In Kenya, bean price fluctuations are relatively low compared to neighboring
countries, which is characteristic of many Kenyan grain and pulse price patterns (FEWSNET,
2010b,c,d). The Ugandan capital, Kampala, has the highest seasonal price fluctuation in the
available data, followed by the northern Ugandan city of Gulu.
8
Table 2: Estimated ratio of high/low nominal price months
Tanzania
Kenya
Uganda
Arusha
1.174
Kitui
1.168
Lira
1.312
Dar es Salaam
1.211
Nairobi
1.201
Dodoma
1.333
El Doret
1.275
Gulu
1.684
Mbeya
1.391
Kisimu
1.335
Songea
1.461
-
-
Kampala
2.000
Kigoma
1.587
-
-
Source: FEWS (2010b,c,d)
Common Bean Hedonic Price Formation and Consumer Preferences
Consumer preferences have been documented throughout Africa regarding common bean size,
cooking time, grain damage, discoloring, variety, and degree of uniformity in a sample (Mishili
et al., 2011; Wortmann et al., 1998). The degree of preference for certain product attributes is
reflected in the premium consumers are willing to pay for these attributes. Likewise, the degree
of distaste for product attributes will determine the magnitude of the discount. In Eastern Africa,
large and medium sized seeds are preferred (Wortmann et al., 1998; Mishili et al., 2011).
However, these preferences vary in intensity across production areas and are less pronounced
among lower-income consumers (Wortmann et al., 1998). Samples with uniform varieties
samples are also preferred to mixtures, and beans are primarily marketed separately in Burundi,
Rwanda, Zaire, Kenya , and Tanzania (Mishili et al., 2011; Wortmann et al., 1998). Tanzanian
consumers also pay premiums for the variety Soya Kablanketi and demand discounts for any
discolored grain (Mishili et al., 2011). Evidence from Rwanda also suggests that consumers do
not place a premium on the chemical vs. non-chemical method in which are beans protected, but
instead focus more on the quality of dry beans after storage (Dunkel et al., 1995).
Information about hedonic price formation is very important for all actors in the common
bean value chain. Even where only 20% of common bean production is sold, farmers consider
market preferences before choosing varieties to plant (Giga et al., 1992). Evidence from Mishili
et al. (2011) demonstrates that bruchid-damaged beans are heavily discounted, at 2.3% per
emergence hole in 100 bean grains. Therefore, in a 100 grain sample, the presence of 10
emergence holes could decrease the value of that sample by 23%.
Principal Storage Constraints
Short storage periods are historically prevalent among small bean producers, the largest
component of the production chain (Giga et al., 1992). This is principally attributed to
prohibitive storage damage from post-harvest insect infestation or cash-flow constraints (ibid).
The most prominent and destructive of storage pests among common beans are the bruchid
beetles Acanthoscelides obtectus (Say) (Coleoptera: Bruchidae) and Zabrotes subfasciatus
(Boheman) (Coleoptera: Bruchidae), which cause average estimated dry weight losses of 10-40%
(Kiula and Karel, 1985; Khamala, 1978). Dry weight losses of 50% and 70% have even been
9
recorded where post-harvest management is especially poor (Lima, 1987; Khamala, 1978). Both
storage pests cause grain damage in their larval stage by boring into the bean, where they seal
themselves shut and feed until emerging as an adult (Songa and Rono, 1998). Holes resulting
from their subsequent emergence are generally understood as “grain damage” (Mulungu et al.,
2007; Songa and Rono, 1998). A farmer’s inability to prevent heavy storage losses from insects
may consistently force sales within 2-3 months, as they may incur “total crop loss” from insect
infestation within 4-5 months (Giga et al., 1992). However, if a farmer in the Dar es Salaam area
sold beans early after a May harvest to avoid insect damage, he would forfeit average potential
price increases of 14.1% by December or even 17.5% by March. Producers in the sourcing
regions for the Mbeya, Kigoma, and Songea markets may forfeit even higher seasonal price
increases.
If credit is not available or interest rates are prohibitively high, farmers may sell early to
pay post-harvest expenses. However, whole stores are rarely sold to meet immediate cash needs.
When necessary, farmers tend to sell a portion of stocks and store the remainder as long as
possible” as a highly liquid asset. This asset has the potential to appreciate in value after harvest,
peaking generally in the lean months before the following harvest, if maintained without
damage. By selling early, the forfeited potential gain from commodity price increases over the
marketing season may be interpreted as the “defacto” interest rate on liquidating these assets
after harvest (Stephens and Barrett, 2009).
Methods for Controlling Bean Storage Pests
A. obtectus and Z. subfasciatus are often present together in storage infestations (Abate and
Ampofo, 1996), but observations in Giga et al, (1992) indicate many circumstances of isolated
infestation. A. obtectus is able to bore into un-threshed pods before harvest, while Z.
subfasciatus is only able to infest once pods have been threshed for storage. In East Africa,
timely harvest must be assured to avoid heavy field infestation by A. obtectus (Giga et al., 1992).
If A.obtectus is present in the insect complex, bean stores are generally threshed “as soon as it is
practical” and treated with protectants (ibid). Alternatively, stored beans are protected from Z.
subfasciatus within un-threshed pods. Timing of threshing thus varies greatly on a regional
basis, ranging from 1-4 days after drying when A. obtectus is present to two months after drying
with isolated Z. subfasciatus infestations. Consequently, farmers must base storage strategies on
both rainfall (moisture) conditions as well as the regional insect complex.
Solar disinfection of seeds between weighted plastic sheets has been demonstrated as an
effective bruchid control technique in common bean (Songa and Rono, 1998) and cowpea
legumes (Murdock and Shade, 1991). The solar disinfection method is generally promoted by
extension agents, as well as the use of insecticides such as Actellic Super® (0.3% permethrin and
1.6% pirimiphos-methyl) (Songa and Rono, 1998). Results in Table 3 from Songa and Rono
(1998) in Kenya show that corn oil, the solar disinfection method, and Actellic Super®
performed comparably well in bruchid management during four months of storage. Solar
disinfection is determined the most effective method on the basis that corn oil discolored grain
and reduced market value (as verified by Mishili et al., 2011) and high insecticide residue may
10
prove harmful for human consumption. Germination of seeds was also highest when treating
with solar disinfection and Actellic Super®.
Table 3: Efficacy of Common Bean Storage Methods in Kenya after Four Months of Storage
Treatment
Percentage of
Damaged Seeds
Appearance of Seed
Percentage of Seeds
Germinated
Actellic Super®
0.9 ± 0.2
Unchanged
91.7 ± 4.2
Sunning & Sieving
0.7 ± 0.2
Unchanged
97.2 ± 2.8
Corn Oil
0.6 ± 0.1
Discolored
77.8 ± 6.5
Wood Ash
6.9 ± 3.0
Discolored
83.3 ± 7.2
Control
10.9 ± 4.6
Unchanged
77.8 ± 8.8
Source: Songa and Rono (1998)
Farmers may adopt a wide variety of traditional pest control methods, such as delaying
threshing and admixing with ash, soil, inert dusts, plants oils and other botanicals (Cork et al.,
2009). Botanical and plant material of varying protectant efficacy may include cypress,
marigold, tagetes, and neem, among many others (Paul et al., 2009). However, extension agents
generally discourage use of many botanical and “traditional” methods based on questionable
efficacy (Songa and Rono, 1998), though botanical alternatives for bean storage are the focus of
new scholarly attention (Paul et al., 2009; Mulungu et al., 2007; Paul, 2007). Paul et al. (2009)
reports in Figure 4 that A. indica (neem) as a seed powder applied at 1.5kg/100kg beans
maintains dry bean stores under 15% grain damage over a five month period, far surpassing other
botanical leaf powder treatments in on-farm trials. Conversely, neem leaf powder applied at
even 8.3 kg per 100kg of beans was unsuccessful as a protectant.
Figure 4: Percentage of Beans with Emergence Holes in Storage with Various Protectants
Source: Paul et al. (2009)
Other treatments receiving scholarly attention include utilization of diatomaceous earth
(DE) products such as KeepDry®, a silica dioxide inert dust from fossilized rock. Laboratory
experiments with DE products display a high Z. subfaciatus mortality rate at application rates of
0.75g/kg and 1.00g/kg (Lazzari and Ribeiro-Costa, 2006). Intertemporal dry weight loss and
bean damage estimates were unfortunately not presented in this study, making it impossible to
compare efficacy with storage treatments.
11
Researchers have also developed seeds with varietal resistance from areclin, a lectin, which
offers strong resistance to Z. subfasciatus but little protection from A. obtectus (Cork et al., 2009;
Velten et al., 2007; Kusolwa, 2007; Mamo, 2010). Results for this hybrid are considered
promising and beans with this genetic resistance have been manufactured, yet few farmers have
received improved varieties to date (Cork et al., 2009).
Effects on Germination
Farmers in Eastern Africa are generally aware of the need for clean, undamaged seed for
maximum germination (Giga et al., 1992). Baier and Webster (1992) and Songa and Rono
(1998) confirm general knowledge that bruchid damage from emergence holes negatively
impacts seed germination. Extension recommendations also caution against long sessions of
solar disinfection, as sessions lasting for one or more hours can result in 0% - 35% germination
rates (Agona and Nahdy, 1998).
Purdue Improved Cowpea Storage (PICS) bags
Triple-layer hermetic Purdue Improved Crop Storage (PICS) bags were developed under the
Bean/Cowpea CRSP project in the late 1980s through funding from USAID (Murdock et al.,
2003). Hermetic technology works by creating an airtight seal in which oxygen levels
dramatically decrease within days through insect, fungal, and/or seed respiration (Quezada et al.,
2006). The high density polyethylene PICS bags, with ultra-thick walls of 80 microns, are
produced in 50kg and 100kg capacity sizes and cost between $2 and $4, depending on the region
(Baributsa et al., 2010). This technology was originally created until the trademark “Purdue
Improved Cowpea Storage (PICS) for West and Central African cowpea farmers to protect
against extremely destructive cowpea bruchids, which prevented resource-constrained farmers
from long-term storage to capture price increases later in the marketing season. Moussa (2006)
conducted an impact assessment of the Bean/Cowpeas CRSP project and estimates that, due to
the introduction of hermetic technology in the region, over 500,000 additional tons of cowpea are
now conserved per year, resulting in $100 million USD in annual additional cowpea income.
The success of PICS bags with cowpeas has induced producers and researchers alike to
begin experimentation with storage of other commodities. To date, PICS bags have displayed
50% lower cassava chip storage losses compared to conventional polypropylene bags over a two
month period (Ognakossan et al. 2010). Research by Ognakossan et al. is still in progress at the
time of this analysis and will yield more long-term results soon. Hell et al. (2010) also displayed
that PICS bags can provide extremely high rates of protection for maize grain, remaining under
0.5% dry weight loss after a six month period. While no direct studies have thus far been
conducted with PICS bags for common bean storage, field experiences allow for estimations
(based on cowpea losses) of about 0.6% dry weight loss in long-term storage.
12
Key Literature Review Conclusions
1) Dry beans are of significant nutritional and economic importance in many regions of
Eastern and Southern Africa (Giga et al., 1992; Wortmann et al., 1998; FAO STAT,
2010).
2) Stored beans are consumed by the household, stored for seed, or marketed at a later date
(Wortmann et al., 1998; Giga et al., 1992).
3) Average seasonal price increases from post-harvest months to the annual high-price
month are estimated between 17.4% - 58.7% in Tanzania, 16.8% - 33.5% in Kenya, and
31.2% 100.0% in Uganda (FEWS NET, 2010b,c,d).
4) Among other consumer preferences, emergence holes from storage pests Z. subfaciatus
and A. obtectus result in significant quantified price discounts in bean grain samples
(Mishili et al., 2011).
5) Many extension offices promote pests control strategies as insecticide use and/or solar
disinfection (Songa and Rono, 1998), though certain botanicals show potential as storage
treatments (Paul et al., 2009).
6) PICS hermetic storage bags may provide a new alternative for long-term storage of
common beans with minimal grain damage or dry weight losses, based on results with
other commodities (Murdock et al., 2003; Hell et al., 2010; Ognakossan et al., 2010).
Data
In this meta-analysis, returns from storage will be calculated for bean storage utilizing PICS
bags, Actellic Super® insecticide treatments, solar disinfection, or the botanicals for which Paul
et al., (2009) conduct their extended period loss analysis. Conclusions are then drawn to
determine the cost-effectiveness of PICS bags within this range of current storage technology
options. As the United Republic of Tanzania represents the largest national common bean
producer in Africa, this country was selected for in-depth analysis in diverse market scenarios.
Price Data
Market price data for Tanzania was accessed through the recent Famine Early Warning System
(FEWS) price bulletins, which are recorded as charts of nominal five-year monthly wholesale
averages (September 2006 September 2010). Experience with maize price data shows that
five-year monthly averages can result in two months appearing as the global low and high price
periods, when actual individual annual high and low price months may be occur without a
distinct pattern (Chapoto and Jayne, 2010). In the case of Tanzanian common beans, the five-
year averaged low and high price months match other qualitative literature on the general peak of
13
the lean season (June) and the general major harvest month (October) (WFP 2010; WFP 2009).
Experience with richer data sets also shows that disparities between high and low price months
in five-year averaged data may be dramatically lower than actual annual disparities (Chapoto and
Jayne, 2010). Therefore, the nominal averages were determined to be a conservative measuring
tool to gauge the potential profitability for PICS bags, and thus appropriate in this analysis. The
data thus appear to be a smoothed trend with the actual high and low price months correctly
identified by the averages, serving as a conservative estimation of potential storage gains.
As numerical data could not be retrieved in the evaluated countries for the entire five-year
period, the FEWS NET data, with graphical representations of average monthly prices, provided
the best insight on price trends. To extract numerical data, the graphics were first copied from
the price bulletins into Microsoft Word®, then cropped and enlarged to focus on price intervals.
This image was then super-imposed on a respective table which was spaced evenly throughout
the intervals to replicate minor gridlines. Thus, prices could be estimated from the charts with
reasonable, yet imperfect accuracy (estimated range of error 1-2%).
Farm-gate prices are then assumed to conservatively represent 75% of wholesale prices,
based on data from a 2009 MSU/Tegemeo University maize market chain study in Kenya
including 534 households, 46 small traders, and 36 medium-scale wholesalers (Kirimi et al.,
2010). All marketing margins are assumed to remain constant throughout the year. Further,
farmers are assumed to be able to sell beans at any month desired.
Treatment Data
Losses from common bean bruchids in storage with PICS bags are still under active laboratory
and field investigation. The similarity of common bean and cowpea bruchids merited this
accelerated economic evaluation, and losses are assumed to be comparable with hermetic
cowpea storage (Boys et al., 2007). The only insecticide for which documented inter-temporal
damage estimates were provided was Actellic Super (permethrin (0.3%) + pirimiphos-methyl
(1.6%)) (Songa and Rono, 1998). Songa and Rono (1998) also provide the only common bean
research with inter-temporal damage estimates for the solar disinfection and sieving (S&S)
technique. Grain damage estimates are also documented in field studies utilizing cypress,
marigold, tagetes, and neem (Paul et al., 2009). Thus, these pest-control strategies are used for
economic comparison with PICS bags. However, grain damage data is only reported for four
months of storage by Songa and Rono (1998) and up to five months of storage by Paul et al.
(2009). Price maximum months in Tanzanian study markets occurred six or more months after
the assumed harvest month. To be conservative, damage levels with treatments from Songa and
Rono (1998) and Paul et al., (2009) are always considered at four month levels, even if the
optimal storage period is longer. As controls from each study showed remarkably varied rates
of grain damage at four months of storage, the damage levels from the northern Tanzanian study
(Paul et al., 2009) will be scaled to the more conservative Kenyan study zone (Songa and Rono,
1998) as a percentage of treatment vs. control losses. Grain damaged is also defined as the
percentage of beans with emergence holes. Mishili et al. (2009) describe quality discounts for
each emergence hole per 100 seeds, but, under constrained information, this analysis will
conservatively assume only one hole per seed is present in a “damaged” grain.
14
Both dry weight losses and the percentage of grains damage are important in calculating
revenues of stored beans. The field studies available, however, only documented the percentage
of grain damage at the noted time periods. A laboratory experiment, conducted by Mulungu et
al. (2007) provides a limited range of results documenting both dry weight losses and
corresponding grain damage levels. Figure 5 displays the relationship between these two
variables and resulting predictive linear equation. This linear relationship is utilized to
conservatively link the two variables and estimate corresponding levels of dry weight loss in
storage treatment data from Songa and Rono (1998) and Paul et al. (2009). Holst et al. (2000)
derived comprehensive equations relating dry weight losses and grain damage in maize grain,
showing the relationship to be exponential. Thus, the limited linear equation for beans in Figure
5 is only meant to provide a conservative estimate of losses beyond the data range of Mulungu et
al. (2007). It is important to note that all grain damage data from Songa and Rono (1998) and
Paul et al. (2009) at four months of storage fell within the documented range. Only loss
estimates for bean storage without treatment exceeded the data range from Mulungu et al.
(2007).
Figure 5: Relationship between damaged bean seeds to dry weight loss levels
Source: Mulungu et al. (2007)
Cost Data
Costs of insecticides and polypropylene bags for non-PICS storage are based on recent field
experience in Ghana. As price data for these items were not available from Tanzania, costs are
assumed to be equal to that in Ghana. Botanicals are assumed to be locally available, requiring
only labor as a search cost. This personal labor cost is conservatively assumed to be zero for this
analysis. Labor costs for the weekly solar disinfection and sieving of beans are also considered
zero, though Songa and Rono (1998) report that many producers complain of the laborious
difficulty of weekly treatments.
y = 1.4401x - 0.2301
0
5
10
15
20
25
0 2 4 6 8 10 12 14 16
% Damaged Bean Seeds
% Dry Weight Loss
15
Study Area
Previous nationwide bean bruchid studies in Tanzania have identified nine major bean growing
regions in Tanzania: Tanga, Kilimanjaro, Arusha, Bukoba, Mwanza, Morogoro, Mbeya, and
Ruvuma, and Kigoma (Nchimi-Msolla and Misangu, 2002). Figure 6 from FEWS NET verifies
current production and trade patterns dominated from these regions in 2010. Available price data
from FEWS bulletins, however, only reported data for markets in Dar es Salaam, Dodoma,
Mbeya, Arusha, Kigoma, and Songea [Ruvuma region]. Therefore, this producer-focused study
will report results only from the four major markets in production regions, excluding the Dar es
Salaam and Dodoma markets.
Figure 6: Bean Production Regions and Trade Patterns, 2010
Source: FEWS NET (2010)
Methodology
Calculating Returns on Storage
Returns for storage were evaluated in comparison to the benchmark of marketing immediately
after harvest vs. always selling six months after harvest and/or at the month with the maximum
price in the common bean marketing season. Harvest periods were determined by FEWS data
and verified by planting and harvesting planning descriptions in from CRSP workshop reports
16
(Nchimbi-Msolla and Misangu, 2002). Returns to storage in marketing regions throughout
Tanzania were calculated from the five-year nominal averages under varying opportunity costs to
represent a larger spectrum of the potential adopting producers.
From the small-producer’s benchmark option to sell directly after harvest, returns on
storage were calculated with the best estimation from the literature of expected losses with each
storage technology for each storage period. For sensitivity analysis, returns to storage are also
calculated for 5% above and below the expected losses from control samples (no storage
technology).
Thus,
      
[1]
     

[2]
  

[3]
This analysis also considers the ability of PICS bags to be used for a second season. The
cost of the PICS bag was straight-line depreciated over two years, and returns on storage
presented as an average of year one and two. As production costs vary greatly across the
country, these parameters were not included in the model. Caution should therefore be
exercised, as Nominal Crop Income refers to crop revenue, net storage costs.
Results
Tables 4 and 5 document the process by which returns on storage are derived for each
technology in the various market regions. This example is from the Mbeya region for producers
with an opportunity cost of capital (OCC) of 25%, the lowest possible OCC examined in this
analysis. Under these conditions, meant to rigorously test PICS bags against current treatments,
the hierarchy of treatments with respect to potential returns of storage is:
1) Solar disinfection and sieving (S&S),
2) PICS bags utilized for two years,
3) Actellic Super,
4) PICS bags utilized for only one year,
5) A. Indica,
6) C. Ambrosioides,
7) C. Lusitanica, and
8) T. Minuta
17
Based on fixed loss estimates and costs for each treatment, this order will remain constant
throughout all markets examined. Market regions vary in magnitude of price fluctuations and
this analysis will provide a method to measure the profitability of treatments. Further sensitivity
analysis follows the results section, which utilizes alternate loss estimates for non-PICS
technology based on control losses in Songa and Rono (1998).
Table 4: Derivation of Revenues for Producers in Mbeya (25% OCC)
Sell
Beans at
Harvest
Common Bean Storage Technology Options
PICS Bags
S&S
Actellic
Super
Botanicals1
One Year
Use
Two
Years of
Use (Avg)
A. Indica
C.
Ambrosioid
es
Selling
Period:
June
December
Sample
Production
(kg)
100
100
100
100
100
100
100
Dry
Weight
Loss (%)
-
0.60
0.60
0.65
0.78
1.87
3.04
Beans
Marketed
(kg)
100
99.40
99.40
99.35
99.22
98.13
96.96
Beans
Damaged2
(%)
-
0.63
0.63
0.70
0.90
2.46
4.15
Farm-gate
Price
(1000
TZS/kg)
0.43
0.60
0.60
0.60
0.60
0.60
0.60
Price
Received
with
Damage
Discount3
0.43
0.591
0.591
0.590
0.588
0.566
0.543
Total
Revenue
(1000
TZS)
43.13
58.77
58.77
58.65
58.30
55.55
55.62
1
The botanicals C. Lusitanica and T. Minuta were also analyzed in subsequent sections, but excluded in this
example
2
Interpreted as the percentage of beans with emergence holes present
3
Discount of 2.3% applied for each percentage of beans damaged (by definition in footnote 3)(Mishili et al., 2011).
Discounted Price = (FG Price) (0.023)(% Beans Damaged)(FG Price)
18
Table 5: Derivation of Storage Costs and Returns on Storage for Producers in Mbeya (25%
OCC)
Sell
Beans
at
Harvest
Common Bean Storage Technology Options
PICS Bags
S&S
Actellic
Super
Botanicals
One Year
Use
Two Years
of Use
(Avg)
A. Indica
C.
Ambrosioides
Selling
Period:
June
December
Total
Revenue
43.13
58.77
58.77
58.65
58.30
55.55
55.62
Storage
Costs
Sieve Cost4
(1000 TZS)
-
-
-
0.36
-
-
-
Insecticide
Cost
(1000 TZS)
-
-
-
-
0.99
-
-
Storage
Bag Costs
(1000 TZS)
-
2.86
1.43
0.49
0.49
0.49
0.49
Total
Storage
Costs
-
2.86
1.43
0.85
1.48
0.49
0.49
Nominal
Total Crop
Income
43.13
55.91
57.34
57.80
56.82
55.05
52.13
Opportunit
y Cost of
Capital
(25%)
(1000 TZS)
-
5.75
5.57
5.50
5.58
5.45
5.45
Gain from
Storage
-
7.04
8.65
9.18
8.12
6.47
3.55
Percent
Gain on
Investment
-
15.30%
19.40%
21.11%
18.40%
15.01%
8.24%
4
Derived from Songa and Rono (1998). Straight-line depreciated from stated 10-year lifespan.
19
Mbeya market region
Table 6 displays monthly wholesale data extracted from FEWS NET charts. Farm-gate prices in
Table 6 represent 75% of wholesale prices, following Kirimi et al. (2010). Figure 7 shows that
nominal prices display much less seasonality in 2009 and 2010 than in the 39.2% June-
December increase in the 2005-2008 period. This underscores the fact that storing beans will
inevitably vary in profitability from year to year.
Table 6: Extracted Wholesale and Farm-gate Bean Prices in Mbeya
Extracted Nominal Five-Year Average Wholesale Prices in Mbeya (TZS/kg)
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
575
631
638
663
700
731
800
710
730
695
640
650
Derived Farm-gate Prices (TZS/kg)
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
431
473
478
497
525
548
600
533
548
521
480
488
Source: Extracted from FEWS NET chart in Figure 7; Farm-gate discounting factor (75% of
wholesale price) from Kirimi et al. (2010)
Figure 7: FEWS NET Chart of Nominal Wholesale Bean Prices in Mbeya, Tanzania
Source: FEWS NET (2010)
Results in Table 7 conservatively estimate that all modeled treatments could provide
positive storage returns for producers when evaluated at a 25% OCC. Actellic Super, solar
disinfection and sieving (S&S), A. indica (neem), and PICS bags, in particular,could provide
economic returns to storage from 15.3 22.4%. Even producers with opportunity costs of
capital of 55% would attain some positive returns to storage, indicating storage protection could
be a beneficial investment for a wide range of potential adopters.
20
Table 7: Returns on Storage (%) in Mbeya under Various Opportunity Costs of Capital.
OCC
No Treatment
(DWL Levels)
Botanical Treatments
Extension
Promoted
Treatments
PICS Bags
30%
20%
10%
T.
Minuta
C.
Lusi-
tanica
C.
Ambro-
sioides
A.
Indica
Actellic
Super
S&S
One
Year
Use
Two
Years
(Avg)
25%
(112.7)
(75.6)
(29.4)
2.4
8.0
8.2
15.0
18.4
21.1
15.3
19.4
35%
(117.7)
(80.7)
(34.4)
(2.6)
2.9
3.2
10.0
13.3
16.1
10.3
14.4
45%
(122.8)
(85.7)
(39.5)
(7.7)
(2.2)
(1.9)
4.9
8.3
11.0
5.3
9.4
55%
(127.8)
(90.8)
(44.6)
(12.8)
(7.2)
(6.9)
(0.2)
3.2
5.9
0.3
4.4
Note: Losses from Paul et al. (2009) scaled to the four month control for Songa and Rono (1998)
DWL- Dry weight loss
Songea
Table 8 illustrates that the Songea market experiences the lowest average price in June and
highest peak in December. However, Figure 8 displays that prices in 2009 and 2010 peak in
January and February followed by troughs in March and April. This seasonality pattern is
logical in a unimodal zone (single rainfall period), but it is not known how annual patterns
behaved in previous years for comparison. The Songea market displays the second highest
average seasonal price increases in Tanzania, rising 46.1% from June to December.
Table 8: Extracted Wholesale and Farm-gate Bean Prices in Songea, Tanzania
Derived Nominal Five-Year Average Wholesale Prices in Songea (TZS/kg)
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
445
452
449
500
553
572
650
650
644
469
469
493
Derived Nominal Five-Year Average Farm-gate Prices in Songea (TZS/kg)
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
334
339
337
375
415
429
488
488
483
352
352
370
Source: Extracted from FEWS NET chart in Figure 8; Farm-gate discounting factor from Kirimi
et al. (2010)
21
Figure 8: FEWS NET Chart of Nominal Wholesale Bean Prices in Songea, Tanzania
Source: FEWS NET (2010)
Due to greater seasonal price fluctuations, higher returns to storage may be possible in
the Songea region. The botanicals C. Lusitanica and C. Ambrosioides now also show potential
for returns over 10% for producers with low opportunity costs of capital. Utilization of PICS
bags for two years, Actellic Super, A. indica, and the S&S technique provide potential returns
over 20%. For these treatments, even producers with the highest modeled opportunity costs
would attain positive returns to storage.
Table 9: Returns on Storage (%) in Songea under Various Opportunity Costs of Capital.
OCC
No Treatment
(DWL Levels)
Botanical Treatments
Extension
Promoted
Treatments
PICS Bags
30%
20%
10%
T.
Minuta
C.
Lusi-
tanica
C.
Ambro-
sioides
A.
Indica
Actellic
Super
S&S
One
Year
Use
Two
Years
(Avg)
25%
(116.6)
(74.1)
(25.6)
7.8
13.7
13.9
21.1
23.7
27.1
19.3
24.7
35%
(123.2)
(79.2)
(30.6)
2.8
8.6
8.9
16.0
18.7
22.1
14.3
19.7
45%
(129.7)
(84.2)
(35.7)
(2.3)
3.5
3.8
10.9
13.6
17.0
9.3
14.7
55%
(136.2)
(89.3)
(40.8)
(7.4)
(1.6)
(1.3)
5.8
8.5
11.9
4.3
9.7
Note: Losses from Paul et al. (2009) scaled to the four month control for Songa and Rono
(1998); DWL- Dry weight loss
22
Kigoma
Table 10 displays average monthly wholesale price data from Kigoma, similarly peaking in the
month of December. Figure 9 shows that nominal prices in 2009 display price seasonality that
closely matches the five-year averages, though 2010 prices demonstrate considerable volatility.
The Kigoma market experiences the highest average price increases of all Tanzanian markets
studied, rising 59% from June to December.
Table 10: Extracted Wholesale and Farm-gate Bean Prices in Kigoma, Tanzania
Extracted Nominal Five-Year Average Wholesale Prices in Kigoma (TZS/kg)
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
650
690
738
819
888
969
1031
914
827
763
750
750
Derived Farm-gate Prices in Kigoma (TZS/kg)
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
488
518
553
614
666
727
773
686
620
572
563
563
Source: Extracted from FEWS NET chart in Figure 9; Farm-gate discounting factor from Kirimi
et al. (2010)
Figure 9: Nominal Wholesale Bean Prices in Kigoma, Tanzania
Source: FEWS NET (2010)
Potential returns on storage in Kigoma are the highest of all examined Tanzanian
sourcing regions. PICS bags utilized for one or two years yield potential economic returns of
34.3% and 38.5%, respectively at 25% OCC. Botanical treatments all show positive returns on
storage, ranging from 18.9 33.2%. Continuing the assumption of zero labor costs, the solar
disinfection and sieving treatment could reach economic returns over 40%.
23
Table 11: Returns on Storage (%) in Kigoma under Various Opportunity Costs of Capital.
OCC
No Treatment
(DWL Levels)
Botanical Treatments
Extension
Promoted
Treatments
PICS Bags
30%
20%
10%
T.
Minuta
C.
Lusi-
tanica
C.
Ambro-
sioides
A.
Indica
Actellic
Super
S&S
One
Year
Use
Two
Years
(Avg)
25%
(110.9)
(70.1)
(17.4)
18.9
25.2
25.5
33.2
37.5
40.3
34.3
38.5
35%
(115.4)
(75.2)
(22.4)
13.8
20.1
20.5
28.2
32.4
35.3
29.3
33.5
45%
(119.9)
(80.2)
(27.5)
8.8
15.1
15.4
23.1
27.4
30.2
24.3
28.5
55%
(124.3)
(85.3)
(32.5)
3.7
10.0
10.4
18.1
22.3
25.2
19.3
23.5
Note: Losses from Paul et al. (2009) scaled to the four month control for Songa and Rono (1998)
Arusha
Arusha is located in the bimodal rainfall zone, contributing to the market region’s lower seasonal
price variation. This market zone has the lowest global high/low price increases in the
Tanzanian, rising only 17% from June to March. The first local price maximum in November is
only 7.2% higher than harvest month prices. Returns on storage were calculated using sale at
both local and global maximum price months.
Table 12: Extracted Wholesale and Farm-gate Bean Prices in Arusha, Tanzania
Derived Nominal Five-Year Average Wholesale Prices in Arusha (TZS/kg)
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
700
713
719
731
740
750
740
755
781
822
800
760
Derived Nominal Five-Year Average Farm-gate Prices in Arusha (TZS/kg)
June
July
Aug
Sept
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
525
534
539
548
555
563
555
566
586
617
600
570
Source: Extracted from FEWS NET chart in Figure 10
Figure 10: FEWS NET Chart of Nominal Wholesale Bean Prices in Arusha, Tanzania
Source: FEWS NET (2010)
24
Tables 13 and 14 display that positive returns to storage would not be realized by Arusha-region
producers targeting the first or annual price maximums. Even though the price appreciates an
additional 9.6% from November to March, the opportunity cost of holding this capital is
primarily responsible for the erosion of potential returns. This may help to explain why
producers sell early, as even perfect grain protection may not be beneficial for a market-oriented
producer. This model suggests that profit-maximizing producers in the Arusha region should
thus sell common bean stocks at harvest and invest the bean revenue in endeavors providing
higher returns.
Table 13: Returns on Storage (%) in Arusha for five months of storage under various
Opportunity Costs of Capital.
No Treatment
(DWL Levels)
Botanical Treatments
Extension
Promoted
Treatments
PICS Bags
OCC
30%
20%
10%
T.
Minuta
C.
Lusi-
tanica
C.
Ambro-
sioides
A.
Indica
Actellic
Super
S&S
One
Year
Use
Two
Years
(Avg)
25%
(109.6)
(81.3)
(46.0)
(21.8)
(17.5)
(17.3)
(12.2)
(9.2)
(7.4)
(10.9)
(8.3)
35%
(113.7)
(85.5)
(50.2)
(25.9)
(21.7)
(21.5)
(16.3)
(13.3)
(11.5)
(15.1)
(12.4)
45%
(117.9)
(89.6)
(54.4)
(30.1)
(25.9)
(25.7)
(20.5)
(17.5)
(15.7)
(19.2)
(16.6)
55%
(122.1)
(93.8)
(58.5)
(34.3)
(30.0)
(29.8)
(24.7)
(21.7)
(19.9)
(23.4)
(20.8)
Note: Losses from Paul et al. (2009) scaled to the four month control for Songa and Rono (1998)
DWL- Dry weight loss
Table 14: Returns on Storage (%) in Arusha for nine months of storage under various
Opportunity Costs of Capital.
No Treatment
(DWL Levels)
Botanical Treatments
Extension
Promoted
Treatments
PICS Bags
OCC
30%
20%
10%
T.
Minuta
C.
Lusi-
tanica
C.
Ambro-
sioides
A.
Indica
Actelli
c Super
S&S
One
Year
Use
Two
Years
(Avg)
25%
(117.8)
(86.8)
(48.2)
(21.6)
(17.0)
(16.7)
(11.1)
(7.8)
(5.8)
(9.7)
(6.8)
35%
(125.3)
(94.3)
(55.7)
(29.1)
(24.5)
(24.2)
(18.6)
(15.3)
(13.3)
(17.2)
(14.3)
45%
(132.8)
(101.8)
(63.2)
(36.6)
(32.0)
(31.7)
(26.1)
(22.8)
(20.8)
(24.7)
(21.8)
55%
(140.3)
(109.3)
(70.7)
(44.1)
(39.5)
(39.2)
(33.6)
(30.3)
(28.3)
(32.2)
(29.3)
Note: Losses from Paul et al. (2009) scaled to the four month control for Songa and Rono (1998)
DWL- Dry weight loss
25
Sensitivity Analysis
PICS bags were compared to other current storage treatments according to their most
conservative (i.e. lowest) inter-temporal loss figures in the literature. Further sensitivity analysis
is conducted to scale bean grain damage results for insecticide and solar disinfection treatments
from Songa and Rono (1998) to the much higher four-month control in Paul et al. (2009). In this
scenario, one and two year use of PICS bags become the most profitable options, and use of
botanicals for storage protection becomes almost universally unprofitable
5
. Continuing the
assumption of zero labor costs for solar disinfection and sieving, this storage option retains
higher returns on storage than Actellic Super. It is very important, therefore, to consider the
environment context in which analysis is conducted for the most appropriate assessment of the
benefit of technology transfer.
Table 15: Return on Storage Frontier when Scaling Loss Estimates to Paul et al. (2009)
OCC
No Treatment
(DWL Levels)
Botanical Treatments
Extension
Promoted
Treatments
PICS Bags
30%
20%
10%
T.
Minut
a
C.
Lusi-
tanica
C.
Ambro
-sioides
A.
Indica
Actellic
Super
S&S
One
Year
Use
Two
Years
(Avg)
Mbeya
25%
(112.7)
(75.6)
(29.4)
(49.2)
(32.3)
(31.4)
(9.6)
9.2
13.9
15.3
19.4
55%
(127.8)
(90.8)
(44.6)
(64.4)
(47.5)
(46.6)
(24.8)
(5.9)
(1.3)
0.3
4.4
Songea
25%
(116.6)
(74.1)
(25.6)
(46.4)
(28.6)
(27.7)
(4.8)
14.2
19.5
19.3
24.7
55%
(136.2)
(89.3)
(40.8)
(61.6)
(43.8)
(42.9)
(20.0)
(1.0)
4.3
4.3
9.7
Kigoma
25%
(110.9)
(70.1)
(17.4)
(40.0)
(20.7)
(19.7)
5.2
27.0
32.1
34.3
38.5
55%
(124.3)
(85.3)
(32.5)
(55.2)
(35.9)
(34.9)
(10.0)
11.9
16.9
19.3
23.5
Arusha
(5 mo)
25%
(109.6)
(81.3)
(46.0)
(61.2)
(48.2)
(47.6)
(30.9)
(16.2)
(12.9)
(10.2)
(8.3)
55%
(122.1)
(93.8)
(58.5)
(73.7)
(60.7)
(60.1)
(43.4)
(28.7)
(25.4)
(23.7)
(20.8)
Arusha
(9 mo)
25%
(117.8)
(86.8)
(48.2)
(64.8)
(50.6)
(49.9)
(31.6)
(15.5)
(11.9)
(9.7)
(6.8)
55%
(140.3)
(109.3)
(70.7)
(87.3)
(73.1)
(72.4)
(54.1)
(38.0)
(34.4)
(17.2)
(29.3)
5
Note: Data from botanicals as storage protectants taken originally from Paul et al. (2009).
26
Conclusions
Substantial pest damage is associated with common bean storage in Eastern Africa. Evidence
from market studies suggests that financial losses for producers occur not only in the form of dry
weight losses, but also compound with quality discounts for damaged beans. Consideration of
these compounding factors is crucial when evaluating total value loss and thus the benefit of
technologies preventing this damage in medium to long-term storage. For producers to capture
the greatest benefits from price seasonality in most Tanzanian market regions, long-term storage
of approximately six months is required. The market regions of Mbeya, Songea, and Kigoma
offer a price incentive for investment in long-term bean storage technology, while the Arusha
market offers substantially less incentive.
Under reasonable and conservative assumptions, this analysis demonstrates that PICS
bags have the potential to provide substantial returns to storage for marketing producers in most
marketing regions within Tanzania. With the most conservative (i.e. lowest) loss estimates in the
literature for alternative technologies (Songa and Rono, 1998), PICS bags do not provide the
highest returns to storage, but are competitive. Further, PICS bags do provide the highest return,
whether used for one or two years, when losses are scaled to higher estimates in Paul et al.
(2009).
The advantages of PICS storage technology will be most beneficial in regions where A.
obstectus and Z. subfasciatus bruchid infestation is high and seasonal market price fluctuations
are substantial. Investigations into regional common bean hedonic price formation,
incorporating quality discounts for damaged bean grains, will also provide additional insight into
the zones of highest potential benefit. Examination of the implications of regional producers’
marketing rates may also help identify zones of greatest potential impact.
Several key assumptions will need further investigation to test for robustness of results.
The assumption of zero labor costs for weekly solar disinfection contributes greatly to its
estimated high returns to storage. This should be a topic of further investigation, as producers
may be unwilling to spend the time necessary conducting the treatment. PICS technology
requires minimal labor only at the time of filling and emptying the triple-layer sacs, and could
provide a more enticing and competitive storage option for producers with higher personal labor
costs. The product’s nature as a durable good also provides an advantage over one-time use of
insecticides and botanical alternatives. Additionally, the absence of pesticide requirements with
PICS storage technology may add value for producers (and consumers) that is not adequately
captured in this model. Acquisition of more robust inter-temporal price data will also provide
considerably greater capacity for market analysis, including study of annual variances in returns
to storage and a subsequent risk analysis for investing producers.
27
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An alternative approach to traditional consumer behaviour and demand theory is characteristics theory, which assumes that a consumer’s utility function is generated by the characteristics, or attributes, that goods and services possess. Instead of a utility being a function of a product, it becomes a function of the attributes provided by these products. In this paper a hedonic pricing model is used to investigate the influence of sucrose level and cooking time on cowpea prices in Senegal. Cooking time has a significant impact on price only at Tilene market in Dakar, while the sucrose contents tend to provide a premium throughout. Further investigation shows that the local varieties, AW, Matam and Ndiassiw have higher sucrose contents than the other cowpea varieties.
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Purpose of review: This review focuses on the current state of postharvest losses and important tools available for use by farmers for protecting grain against insect pest infestations in sub-Saharan Africa with the view of identifying farmer perceptions, effective control practices, critical challenges and information gaps that need further research. Findings: Several beetle and moth pests attack stored grains in Africa causing significant losses. Currently, there is a lack of reliable and verifiable data on postharvest losses in most African countries. Annual grain losses of over 50% in cereals and up to 100% in pulses have been reported. Smallholder farmers have various forms of indigenous knowledge and complex cultural norms which they apply to grain storage practices and their potential effects need to be analysed. Tools available for managing insects associated with grains include contact insecticides and fumigants, botanicals, inert dusts, biological control agents as well as appropriate modified atmospheres through metal silo and hermetic storage technology. The uses of synthetic insecticides continue to be a major component of stored-product pest management strategies in Africa. However, for sustainable grain protection the combination of the various control options in an integrated and compatible manner and their uptake are imperative. Directions for future research: Assessments of the scale of losses for key stored commodities along the value chain are required. For practical utilisation of botanicals well designed on-farm trials are needed to validate their efficacy. Large-scale field assessment of the impact of the histerid predator, Teretrius nigrescens Lewis on the larger grain borer, Prostephanus truncatus (Horn) should be carried out to justify their continued release into the different agro-ecosystems. The current knowledge of triple-bagging technology, its availability and adoption is limited. Appropriate knowledge transfer techniques to encourage adoption of practical techniques needs to be developed.
Article
Cowpea is the most economically and nutritionally important indigenous African grain legume, grown by millions of resource-poor farmers. It is a key cash crop in areas too dry to grow cotton or other export crops. Most of the over 3 million t of cowpea grain produced annually in West and Central Africa is grown on small farms. Storage is often identified as the key challenge for small scale cowpea growers. Many farmers sell cowpea grain at low harvest time prices rather than risk losses by bruchids during storage. Some traditional methods are effective for small quantities (e.g., 10 kg), but are difficult to scale up. Some effective storage chemicals are available, but they are regularly misused by farmers and merchants. The Purdue Improved Cowpea Storage (PICS) Project is addressing these problems through promotion of hermetic storage in triple layer sacks which have an outer layer of woven polypropylene and two liners of 80 μ high-density polyethylene. Village demonstrations with more than 45, 000 PICS sacks have shown the technology to be effective. Good quality affordable sacks have been produced by manufacturers in Nigeria, Burkina Faso and Mali. Over the past three years more than one million sacks have been produced and sold. Despite the success with the outreach activities and the farmer adoption, the challenge remains to develop sustainable sack distribution networks. Issues identified include reluctance of wholesalers to order sacks due to risk associated with a new product, inability of wholesalers to develop effective distribution networks due to difficulties with enforcing contracts, and limited access to capital. The PICS project is exploring new ways to address some of these issues, including using non-traditional distribution systems for PICS sacks such as agro-dealers networks, and adapting distribution systems that have worked for cell phones and other products.