Introduction: Maize is the most important staple in sub-Saharan Africa (SSA), with highly seasonal production. High storage losses affect food security, but good estimations are lacking. Methods: A new method using focus group discussions (FGDs) was tested with 121 communities (1439 farmers, 52% women) in Kenya’s six maize-growing zones, to estimate the maize losses to storage pests and analyze farmer practices. Results: As control strategies, half of the farmers used chemical pesticides (49%), while hermetic bags (16%) and botanicals (15%) were also popular. Relative loss from weevils in the long rains was estimated at 23%, in the short rains 18%, and annually 21%. Fewer farmers were affected by the larger grain borer (LGB) than by maize weevils: 42% in the long rainy season and 32% in the short rainy season; losses from LGB were also smaller: 19% in the long season, 17% in the short season, and 18% over the year. Total storage loss, from both species combined, was estimated at 36%, or 671,000 tonnes per year. The greatest losses occur in the humid areas, especially the moist mid-altitudes (56%), and with smaller loss in the drylands (20–23%). Extrapolating the point data and overlaying with the maize production map shows the geographic distribution of the losses, with the most important area found around Lake Victoria. FGDs provide convenient and cheap tools to estimate storage losses in representative communities, but a total loss estimate of 36% is higher than is found in other studies, so its accuracy and framing effects need to be assessed. Conclusion: We conclude that storage pests remain a major problem, especially in western Kenya, and that the use of environmentally friendly technologies such as hermetic storage and botanicals needs more attention, both by the public extension service and private agrodealers.

1. Estimating on-farm storage losses in maize
using community surveys in Kenya
Hugo De Groote1, Francisca Muteti
1International Maize and Wheat Improvement Center (CIMMYT),
(h.degroote@cgiar.org, hugo.degroote@gmail.com)
31st Conference of International Agricultural Economics (ICAE)
17th – 31st August, 2021
De Groote, H., Francisca Mutheti, Anani Bruce. 2023. On-farm storage loss estimates of maize in Kenya using community
survey methods. Journal of Stored Products Research. 102: 102107. https://doi.org/10.1016/j.jspr.2023.102107.

2. Introduction
 Maize is the major food crop in
Africa
 Storage losses remain high,
especially weevil and LGB, .
 National studies on the economic
impact of storage pests are rare,
and none in Kenya.
 Scientific and systematic
observations on a national scale
would be expensive; but surveys
with individual farmers easier.
 LSM surveys have been used in
Ethiopia, Malawi, Uganda and
Tanzania.
 An alternative: systematic and
representative FGDs

3. Methodology
• Sampling
 121 communities randomly
selected from six agro ecological
zones;
• Data collection
 In each community, group
discussion conducted with 10-15
maize farmers.
 In total, 1439 farmers
participated, xx women;
 printed pictures of maize weevils
and LGB were shown to the
participants.
 Participants were asked
 Do they know the insects?
 How many farmers were affected?
 What loss do they cause?

4. Results
• Identification
– Maize weevils:
• correctly identified by > 90%
– LGB was less known (XX), esp. high tropics (38%)
• Observation
– Weevils: everywhere in LR, less in SR
– LGB: less both in LR and SR
• Relative losses (%): 24% for both weevil and LGB
Storage
pest
Coastal
Lowlands
Dry mid
altitudes
Dry
transitional
Moist
transitional
High
tropics
Moist mid
altitudes
Total
Maize
weevil
25.4 13.0 14.4 25.2 17.3 36.1 23.9
LGB 22.8 13.0 7.1 24.4 15.1 47.5 23.9

5. Losses by Maize Weevil(%)
• Farmers more
affected in
moist mid
altitudes, less
in high tropics,
both seaons.
• Maize losses
were lower in
the SR

6. Losses by LGB(%)
• Highest
proportion
of affected
farms in
moist mid
altitudes,
lowest in
high tropics.
• More
damage LR
than in SR

7. Species Zone
Production
(1000 tonnes) Storage losses (%) Losses (tonnes)
Long
rains Short rains
Long
rains
Short
rains Annual Long rains Short rains Annual
Weevils Coastal lowlands 25.9 15.8 25.0 26.0 25.4 6.5 4.1 10.6
Dry mid-altitudes 17.2 24.3 12.6 13.3 13.0 2.2 3.2 5.4
Dry transitional 110.6 106.4 12.8 16.1 14.4 14.2 17.1 31.3
Moist transitional 1,081.2 383.4 28.3 16.4 25.2 305.6 63.1 368.7
High tropics 898.2 9.4 17.5 3.3 17.3 156.9 0.3 157.2
Moist mid-altitudes 278.8 179.7 37.9 33.3 36.1 105.8 59.8 165.5
Total 2,411.9 719.0 24.51 20.53 23.6 591.1 147.6 738.8
LGB Coastal lowlands 25.9 15.8 19.8 27.6 19.9 5.1 3.2 8.3
Dry mid-altitudes 17.2 24.3 11.1 14.3 9.7 1.9 2.1 4.0
Dry transitional 110.6 106.4 7.0 7.2 7.0 7.7 7.4 15.2
Moist transitional 1,081.2 383.4 26.9 17.5 26.0 290.7 89.7 380.4
High tropics 898.2 9.4 15.3 3.3 15.2 137.0 1.3 138.3
Moist mid-altitudes 278.8 179.7 53.3 38.4 46.8 148.6 66.0 214.6
Total 2,411.9 719.0 24.51 23.61 24.3 591.1 169.7 760.9

8. Geographical extrapolation of absolute
losses, maize weevils and LG

9. Conclusion
• Maize weevil and the larger grain borer cause significant
storage losses, which vary across the six maize growing
regions in Kenya.
• Statistics on storage losses in different zones are key to
comparing the costs and benefits of postharvest loss
reducing technologies.
• Technologies developed for reducing PHL should be
tailored to suit different agro-ecological zones.

10. Thank you
for your
interest!