Post-harvest losses of crops and its determinants in Ethiopia: tobit model analysis

Abstract Background Reduction of post-harvest loses of crops are crucial tasks in ensuring food and nutrition security. However, a lack of knowledge on the extent of post-harvest losses and its associated impeding factors are posing major challenges to effectiveness of grain post-harvest loss manage...

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Main Author: Sisay Debebe
Format: Article
Language:English
Published: BMC 2022-02-01
Series:Agriculture & Food Security
Subjects:
Online Access:https://doi.org/10.1186/s40066-022-00357-6
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author Sisay Debebe
author_facet Sisay Debebe
author_sort Sisay Debebe
collection DOAJ
description Abstract Background Reduction of post-harvest loses of crops are crucial tasks in ensuring food and nutrition security. However, a lack of knowledge on the extent of post-harvest losses and its associated impeding factors are posing major challenges to effectiveness of grain post-harvest loss management strategy and to scale up for all other crop types in Ethiopia. The study estimates the magnitude of post-harvest losses of all crops and identifies its determinants. Methodology A national-level agriculture survey data were obtained from the Central Statistical Agency of Ethiopia. Data were analyzed using descriptive statistics and Tobit model analysis techniques. Results The analysis shows 25.81% perceived annual average post-harvest losses of crops were obtained with considerable variation across the crop types. The main factors impeding post-harvest losses of crops were households with larger adult family size, higher levels of education attendance, and wealth status, large landholding size and damage of stored crops by insect pests infestation and/or rodent feeding due to utilization of traditional storage equipments, access to extension support services, cooperative marketing membership, and being far away from both all weathered roads and near local market centers due to a higher transaction costs associated with a lack of market information, contamination, and mechanical injuries. Conclusion Minimization of post-harvest losses of crops could be achieved through a holistic approach by providing short and long-term training on post-harvest management practices, promoting the use of post-harvest technologies, paying special attention to the institutional support systems (agriculture extension and rural credit services), strengthening the support for post-harvest handling technologies, reinforcing the existing farmer cooperative marketing, and improvements of the local market and road networking infrastructures of rural areas should be undertaken by the government in collaboration with non-government organizations.
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spelling doaj.art-ca81b175b6ee41ea95355d9206f60a6e2022-12-22T02:48:04ZengBMCAgriculture & Food Security2048-70102022-02-011111810.1186/s40066-022-00357-6Post-harvest losses of crops and its determinants in Ethiopia: tobit model analysisSisay Debebe0Department of Economics, Addis Ababa UniversityAbstract Background Reduction of post-harvest loses of crops are crucial tasks in ensuring food and nutrition security. However, a lack of knowledge on the extent of post-harvest losses and its associated impeding factors are posing major challenges to effectiveness of grain post-harvest loss management strategy and to scale up for all other crop types in Ethiopia. The study estimates the magnitude of post-harvest losses of all crops and identifies its determinants. Methodology A national-level agriculture survey data were obtained from the Central Statistical Agency of Ethiopia. Data were analyzed using descriptive statistics and Tobit model analysis techniques. Results The analysis shows 25.81% perceived annual average post-harvest losses of crops were obtained with considerable variation across the crop types. The main factors impeding post-harvest losses of crops were households with larger adult family size, higher levels of education attendance, and wealth status, large landholding size and damage of stored crops by insect pests infestation and/or rodent feeding due to utilization of traditional storage equipments, access to extension support services, cooperative marketing membership, and being far away from both all weathered roads and near local market centers due to a higher transaction costs associated with a lack of market information, contamination, and mechanical injuries. Conclusion Minimization of post-harvest losses of crops could be achieved through a holistic approach by providing short and long-term training on post-harvest management practices, promoting the use of post-harvest technologies, paying special attention to the institutional support systems (agriculture extension and rural credit services), strengthening the support for post-harvest handling technologies, reinforcing the existing farmer cooperative marketing, and improvements of the local market and road networking infrastructures of rural areas should be undertaken by the government in collaboration with non-government organizations.https://doi.org/10.1186/s40066-022-00357-6Post-harvest losses of cropsDeterminantsTobit modelEthiopia
spellingShingle Sisay Debebe
Post-harvest losses of crops and its determinants in Ethiopia: tobit model analysis
Agriculture & Food Security
Post-harvest losses of crops
Determinants
Tobit model
Ethiopia
title Post-harvest losses of crops and its determinants in Ethiopia: tobit model analysis
title_full Post-harvest losses of crops and its determinants in Ethiopia: tobit model analysis
title_fullStr Post-harvest losses of crops and its determinants in Ethiopia: tobit model analysis
title_full_unstemmed Post-harvest losses of crops and its determinants in Ethiopia: tobit model analysis
title_short Post-harvest losses of crops and its determinants in Ethiopia: tobit model analysis
title_sort post harvest losses of crops and its determinants in ethiopia tobit model analysis
topic Post-harvest losses of crops
Determinants
Tobit model
Ethiopia
url https://doi.org/10.1186/s40066-022-00357-6
work_keys_str_mv AT sisaydebebe postharvestlossesofcropsanditsdeterminantsinethiopiatobitmodelanalysis