Closing the yield gap of soybean (Glycine max (L.) Merril) in southern Africa: a case of Malawi, Zambia, and Mozambique
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Omondi, J.O., Siyabusa, M., Mugo, J., Chibeba, A.M., Chiduwa, M.S., Chigeza, G., ... & Nyagumbo, I. (2023). Closing the yield gap of soybean (Glycine max (L.) Merril) in southern Africa: acase of Malawi, Zambia and Mozambique. Frontiers in Agronomy, 5: 1219490, 1-14.
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Abstract/Description
Introduction: Smallholder farmers in Sub-Saharan Africa (SSA) are increasingly producing soybean for food, feed, cash, and soil fertility improvement. Yet, the difference between the smallholder farmers’ yield and either the attainable in research fields or the potential from crop models is wide. Reasons for the yield gap include low to nonapplication of appropriate fertilizers and inoculants, late planting, low plant populations, recycling seeds, etc.
Methods: Here, we reviewed the literature on the yield gap and the technologies for narrowing it and modelled yields through the right sowing dates and suitable high-yielding varieties in APSIM.
Results and Discussion: Results highlighted that between 2010 and 2020 in SSA, soybean production increased; however, it was through an expansion in the cropped area rather than a yield increase per hectare. Also, the actual smallholder farmers’ yield was 3.8, 2.2, and 2.3 times lower than the attainable yield in Malawi, Zambia, and Mozambique, respectively. Through inoculants, soybean yield increased by 23.8%. Coupling this with either 40 kg ha−1 of P or 60 kg ha−1 of K boosted the yields by 89.1% and 26.0%, respectively. Overall, application of 21–30 kg ha-1 of P to soybean in SSA could increase yields by about 48.2%. Furthermore, sowing at the right time increased soybean yield by 300%. Although these technologies enhance soybean yields, they are not fully embraced by smallholder farmers. Hence, refining and bundling them in a digital advisory tool will enhance the availability of the correct information to smallholder farmers at the right time and improve soybean yields per unit area.
Author ORCID identifiers
Amaral Machaculeha Chibeba https://orcid.org/0000-0001-6019-4482
Godfree Chigeza https://orcid.org/0000-0002-9235-0694
Stephen Boahen Asabere https://orcid.org/0000-0001-8946-401X
Patricia Masikati https://orcid.org/0000-0002-1143-0554
Isaiah Nyagumbo https://orcid.org/0000-0003-0180-234X