Modelling predicts that soybean is poised to dominate crop production across Africa

Foyer, C H and Siddique, K H M and Tai, A P K and Anders, S and Fodor, N and Wong, F L and Ludidi, N and Chapman, M A and Ferguson, B J and Considine, M J and Zabel, F and Vara Prasad, P V and Varshney, R K and Nguyen, H T and Lam, H M (2018) Modelling predicts that soybean is poised to dominate crop production across Africa. Plant, Cell & Environment (TSI). pp. 1-13. ISSN 01407791

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Abstract

The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume‐based farming is particularly important in Africa, where small‐scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land‐use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful “soybean bonanza” across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.

Item Type: Article
Divisions: Research Program : Genetic Gains
CRP: UNSPECIFIED
Uncontrolled Keywords: grain legumes, pulses, soybean, Africa, genetic improvements, sustainable production, production technology
Subjects: Others > Crop Modelling
Others > Crop Improvement
Others > Food Production
Others > Genetics and Genomics
Others > Africa
Others > Legume Crops
Depositing User: Mr Ramesh K
Date Deposited: 22 Nov 2018 08:57
Last Modified: 22 Nov 2018 08:57
URI: http://oar.icrisat.org/id/eprint/10961
Official URL: http://dx.doi.org/10.1111/pce.13466
Projects: UNSPECIFIED
Funders: Worldwide University Network (WUN); BBSRC, Grant/Award Number: BB/N004914/1; ARC, Grant/Award Numbers: DP150103211 and DP130102266; Hermon Slade Foundation, Grant/Award Number: DP130103084; Vice‐ Chancellor Discretionary Fund, Grant/Award Number: VCF20150
Acknowledgement: The authors thank the Worldwide University Network (WUN) for financial support. C. F. and N. F. thank BBSRC for financial support (BB/N004914/1). The work of C. F. and N. F. was undertaken within the auspices of Modelling European Agriculture with Climate Change for Food Security (MACSUR), a FACCE JPI knowledge hub. The work of HML was supported by Hong Kong RGC Area of Excellence Scheme (AoE/M‐403/16), CUHK VC Discretionary Fund VCF2014004, and the Lo Kwee‐Seong Biomedical Research Fund. APKT thanks the General Research Fund (Project ID: 14323116) from Research Grants Council of Hong Kong and the Vice‐Chancellor Discretionary Fund (Project ID: VCF2015006) from CUHK given to Institute of Environment, Energy, and Sustainability. B. F. thanks the Hermon Slade Foundation and ARC (DP130103084 and DP130102266, respectively) for financial support. M. J. C. acknowledges an ARC project (DP150103211). We thank Miss Cherry Lee (The Chinese University of Hong Kong) for helping to polish the figures and tables. We thank FAO for providing unpublished projection data for making Figure 3.
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