Post-harvest management and post-harvest losses of cereals in Ethiopia

H. Hengsdijk () and W. J. Boer
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H. Hengsdijk: Wageningen University & Research
W. J. Boer: Wageningen University & Research

Food Security: The Science, Sociology and Economics of Food Production and Access to Food, 2017, vol. 9, issue 5, No 5, 945-958

Abstract: Abstract Recent and systematic evidence on the magnitude of post-harvest losses in sub-Saharan Africa is scarce, hindering the identification of interventions to reduce losses. Here, we unlock standardized and systematically collected information on post-harvest management and farmer-reported post-harvest loss estimates from the Living Standards Measurement Study – Integrated Surveys in Agriculture. Using the data from Ethiopia, the objective is to disentangle factors that induce or relate to post-harvest losses in cereals. The data of approximately 2500 households and 5500 cereal records were analysed. Cereal post-harvest loss was reported by only 10% of these households. The average self-reported post-harvest loss was 24%. Rodents and other pests were most frequently reported to cause these losses. Adoption of improved storage methods was limited and most cereals were stored inside the house in bags. Random Forests (RF) was applied to gain insight into factors and conditions favouring post-harvest losses. Application of RF explained 31% of the variation in post-harvest losses reported by farmers. Three major factors associated with post-harvest losses were the distance of the household dwelling to the nearest market, the distance of the household dwelling to the main road, and average annual rainfall. Losses increased the further households were located from a market or main road, and losses also tended to decrease with higher rainfall. The standardized and nationally representative survey data from Ethiopia used were a good starting point for modelling post-harvest losses but the finally available information appeared to be partial. Therefore, this paper calls for better data collection, which could help to better target interventions needed to reduce post-harvest losses.

Keywords: Food loss; Random forests; Food storage; Maize; LSMS-ISA (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s12571-017-0714-y

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