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Is labour a major determinant of yield gaps in sub-Saharan Africa? a study of cereal-based production systems in Southern Ethiopia

Author: Silva, J.V.
Author: Baudron, F.
Author: Reidsma, P.
Author: Giller, K.E.
Year: 2019
ISSN: 0314-521X
URI: https://hdl.handle.net/10883/20145
Abstract: We investigated the role of labour in explaining the yield gap of cereals at both crop and farm levels on smallholder farms in Southern Ethiopia. A household survey containing detailed information of labour use at crop and farm level of ca. 100 farms in a maize-based system around Hawassa and ca. 100 farms in a wheat based system around Asella was used for this purpose. Stochastic frontier analysis was combined with the principles of production ecology to decompose maize and wheat yield gaps. Actual maize and wheat yields were on average 1.6 and 2.6 t ha−1, respectively, which correspond to 23 and 26% of the water-limited yield (Yw) of each crop. For both crops, nearly half of the yield gap was attributed to the technology yield gap, indicating suboptimal crop management to achieve Yw even for the farmers with the highest yields. The efficiency yield gap was ca. 20% of Yw for both crops; it was negatively associated with sowing date and with the proportion of women's labour used for sowing in the case of maize but with the proportion of hired labour used for sowing and weed control in the case of wheat. The resource yield gap was less than 10% of Yw for both crops due to small differences in input use between highest- and lowest-yielding farms. The contribution of capital and farm power availability to crop yields, input use and labour use was analysed at the farm level. Labour calendars showed that crops cultivated in Hawassa were complementary, with peak labour occurring at different times of the year. By contrast, crops cultivated in Asella competed strongly for labour during sowing, hand-weeding and harvesting months, resulting in potential trade-offs at farm level. Oxen ownership was associated with capital availability, but not farm power in Hawassa and with both capital availability and farm power in Asella. Farmers with more oxen applied more nitrogen (N) to maize in Hawassa and cultivated more land in Asella, which is indicative of an intensification pathway in the former and an extensification pathway in the latter. Differences in land: labour ratio and in the types of crops cultivated explained the different strategies used in the two sites. In both sites, although gross margin per unit area increased linearly with increasing crop yield and farm N productivity, gross margin per labour unit increased up to an optimal level of crop yield and farm N productivity after which no further response was observed. This suggests that narrowing the yield gap may not be economically rational in terms of labour productivity. We conclude that labour (and farm power) is not a major determinant of maize yield gaps in Hawassa, but is a major determinant of wheat yield gaps in Asella.
Format: PDF
Language: English
Publisher: Elsevier
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Type: Article
Place of Publication: Barking, Essex (United Kingdom)
Pages: 39-51
Volume: 174
DOI: 10.1016/j.agsy.2019.04.009
Keywords: Frontier Analysis
Keywords: Farm Power
Country of Focus: ETHIOPIA
Agrovoc: LABOUR
Agrovoc: ZEA MAYS
Agrovoc: TRITICUM AESTIVUM
Agrovoc: INTENSIFICATION
Agrovoc: EXTENSIFICATION
Agrovoc: YIELD GAP
Related Datasets: https://ars.els-cdn.com/content/image/1-s2.0-S0308521X18306711-mmc1.pdf
Journal: Agricultural Systems


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  • Sustainable Intensification
    Sustainable intensification agriculture including topics on cropping systems, agronomy, soil, mechanization, precision agriculture, etc.

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