Abstract

Abstract Climate change drives huge differences between the actual and projected yield and growing season precipitation. Therefore, this work identifies yield and precipitation gaps for maize and millet at the national and subnational scales as well as policy considerations for agricultural policy experts that can mitigate these gaps. Yield data for the national and subnational scale analyses were obtained for the period 1961–2021 from the FAOSTAT and the Ministry of Agriculture (MINAGRI)/IRAD of Cameroon, respectively. Growing season precipitation data for the national and subnational scales were collected from the World Bank climate change portal and the Climate Research Unit (CRU). Various machine learning algorithms were used to bias-adjust the data and to compute the potential yield and growing season precipitation from which the yield and precipitation gaps were computed. The results show a positive correlation between yield and precipitation gaps, with millet depicting the strongest correlation. The average yield gap for maize is 0.55 t/ha, higher than the average yield gap for millet that is 0.28 t/ha. Not all years with yield gaps are correlated with precipitation gaps. The average precipitation gap for maize is 108 mm/year, and it is higher than the 101 mm/year recorded for millet.

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