Fertilizer recommendations for optimal soybean production in North and Center Benin

In the traditional cropping systems of Benin Republic, soybean is mostly cultivated with no mineral fertilizer supply, despite the decrease of soil fertility. Furthermore, there is no specific fertilizer available for the crop, in spite of its cash crop character. This leads to weak crop yield in the farmers’ fields. The present study aims to determine the optimal doses of each N, P, K, Mg and Zn nutrient to improve soybean production in the Sudano-Guinean and Sudanian zones of Benin Republic. Two years (2018 and 2019) experiment has been carried out in Ouesse district (Sudano-Guinean zone) and Bembereke district (Sudanian zone). Box and Behnken rotating design was used to define N, P, K, Mg and Zn dose combinations leading to 46 combinations. A completely randomized block design was set up considering farmers as replication. In total four farmers’ fields are selected. A one-way analysis of variance is made on the yield data, using the linear mixed-effect model. Response surface analyses are used to determine the optimal dose for each N, P, K, Mg and Zn. The supply of macronutrients combined with Zn, significantly (p = 0.001) improved the soybean grain and above biomass yields as well as the harvest index. The quadratic models were efficient (R² > 0.7) to estimate soybean grain yields considering the nutrient dose variation. The optimal N, P, K, Mg and Zn doses of 15.46, 23.20, 28.6, 16.8 and 6.9 kg.ha-1, respectively (for the Sudano-Guinean zone) and 14.02, 23.89, 17.82, 11.45 and 4.26 kg.ha-1, respectively (for the Sudanian zone) lead to an optimal seed yield of 2 t.ha-1 (that is, almost 2.2 times the yield in the farmers’ field). The development of fertilizer formulas using these determined optimal doses would constitute a suitable technology helping to increase soybean production in both areas. Key words: Soil fertility, biofortication, Box and Behnken design, linear mixed-effect model, leguminous, response surface, micronutrient.