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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.

This study aims to determine the optimal N, P, K, Mg and Zn rates for groundnut production on Ferric and Plintic Luvisol in the Sudano-Guinean and Sudanian zones of Benin Republic. Two years (2018 and 2019) experiment was carried out in the municipality of Ouesse in the Sudano-Guinean zone and Bembereke in the Sudanian zone. The tested nutrient doses were N (0, 20 and 40 kg⋅ha−1), P (0, 25 and 50 kg⋅ha−1), K (0, 20 and 40 kg⋅ha−1), Mg (0, 15 and 30 kg⋅ha−1) and Zn (0, 4 and 8 kg⋅ha−1). The Box and Behnken rotating design is used to define the N, P, K, Mg and Zn rate combinations leading to 46 combinations. A completely randomized bloc design was setting up considering farmers as replication. In total, four farmers’ fields were selected. A one-way analysis of variance is carried out on yield data, using the linear mixed-effect model. Response surface analyses were used to determine the optimal doses for each N, P, K, Mg and Zn. Nodule production (6.5 times higher than the control), number of gynophores (2.8 times higher than the control) and root length (19.2 ± 0.2 cm) of groundnut plants were significantly (p = 0.0001) improved with nutrient application. The response surface analysis shows that treatments N-P-K-Mg-Zn of 16.01-20.18-6.70-5.65-2.47 (in the Sudano-Guinean zone) and 13.1-25.07-11.47-0-1.82 (in the Sudanian zone) are the optimal rates that have induced optimal yield of 2.1 t⋅ha−1 (i.e. 2.5 times the yield in the farmers’ field) pod yield and the best return on investment per hectare. Nevertheless, for a sustainable groundnut producproduction, treatment 13.1-25.07-11.47-20-1.82 is suggested as regular K input is required for the respect of the fertilization laws.

The fertilizer used in Benin by rainfed rice farmers, doesn’t meet the required expectation because of lack of many essential agronomic information to formulate the appropriate nutrient compositions. Despite all the advances in improvement of rice production, its yields in traditional cropping systems are very low and the only inputs of Nitrogen, Phosphorous and Potassium do not effectively increase rice yields. The purpose of this study was to assess nutritional status of rainfed rice crops in Benin. The study covered the rainfed rice production areas of Benin Center where 72 leaves samples were taken on 3600 plants from the farmer fields. The concentrations of nitrogen, phosphorus, potassium, calcium, magnesium, iron and zinc were determined in leaves samples. The preliminary DRIS (Diagnosis and Recommendation Integrated System) norms for the rainfed rice growing in the Benin center were selected for various nutrient ratios obtained from the high yield population of the rainfed rice crop. The yields of the two subpopulations were significantly different (p < .0001). The nutrient requirement for the rainfed rice production was ranked as N> Fe> Zn>K>Mg>P>Ca. The DRIS-derived sufficiency ranges for N, P, K, Ca and Mg from the nutrient indexing survey of the rainfed rice plants grown in Benin center were 1.91-3.66, 0.30-0.64, 2.00-3.89, 0.37-1.05 and 0.18-0.38g kg-1 respectively. The limits for Fe and Zn were 89.27-206.3 and 8.21-24.91 mg kg-1 respectively. On the basis of sufficiency ranges, 4.22, 57.75, 66.20, 56.34, 45.07, 46.50 and 29.57% of samples were low in N, P, K, Ca, Mg, Fe and Zn respectively. The DRIS norms put emphasis on nutrient balance and help to differentiate between healthy and unhealthy rice plants from the nutrition status. However, it needed further researches to determine the amount of the fertilizers to supply in order to maintain nutrient balance.

Soybean is a food security crop in Benin due to its high nutritional value but its yield in the farmers’ cropping system is very low. The present study aims to provide appropriate response to the yield variability among fields in two agro-ecological zones of Benin namely: Southern Borgou zone (AEZ 3 in the north) and cotton zone of central Benin (AEZ 5). Soil samples were collected from 0-20 cm depth in 120 fields (50 in the AEZ 3 and 70 in the AEZ 5). pH (water), soil organic carbon (Walkley and Black method), total nitrogen (Kjeldahl method), CEC (0.01 N ammonium acetate at pH 7 method) and available phosphorus (Bray 1) were determined in the laboratory of Soil Science Water and Environment (LSSEE) of the National Agricultural Research Institute of Benin (INRAB). Cropping system (crop rotations, soil fertility management practices) were also collected using an open ended questionnaire. Classification and regression trees (CARTs) models were used for data analyses. Soybean yield variability among the agro-ecological zones were registered and the highest yield recorded was less than 1 t.ha-1. Considering soil characteristics, soil organic matter level was the most important variable determining yield variability. Furthermore, quantities of P applied and farmyard manure were cropping practices inducing yield variability (86.4% and 15% of the variability respectively). Our results also show that, yield differences noticed among the agro-ecological zones were induced by CEC and pH (water). The study suggested promotion of integrated soil fertility management practices to sustain soybean yield in the study area.

Feeding the world in 2050 requires us to find ways to boost yields of the main local crops. Among those crops, cowpea is one of the grain legumes that is playing an important role in the livelihood of millions of people in West Africa, especially in Benin. Unfortunately, cowpea on-farm yields are very low. In order to understand the main factors explaining cowpea yield gaps, we collected and analyzed detailed survey data from 298 cowpea fields in Benin during the 2017, 2018 and 2019′s rainy seasons, respectively. Composite soil samples were collected from cowpea fields and analyzed in the laboratory. Data on farm field management practices and field conditions were recorded through interviews with 606 farmers. Average cowpea grain yields were low and seldom surpassed 700 kg ha−1 on farmer’s fields. Significant differences were observed between cowpea grain yields from northern to southern Benin (p &lt, 0.05), and the lowest yields were observed in northern Benin. These low yields are related to crop management practices, soil nutrient contents, and the interaction of both. According to the model of regression tree from northern to southern Benin, the use of mineral fertilizer, insecticide sprays to control pests, and the improvement of phosphorus, nitrogen, potassium (P, N, K) and cation sum content in the topsoil would increase cowpea grain yields. Insect pests, diseases, and soil fertility decline are the largest constraints limiting grain yield in Benin. Future research should focus on formulating site-specific fertilizer recommendations for effective cowpea cultivation in Benin, as well as the control of insect pests and diseases.

The decline of soil fertility is a major constraint which results in lower levels of crop productivity, agricultural development and food security in Sub-Saharan Africa. This study is the first to perform a focalized investigation on the most interesting technological profiles to offer to each category of producers in Benin agricultural development hubs (ADHs) using the stated preference method, more precisely, the improved choice experiment method. The investigation focused on 1047 sampled plots from 962 randomly selected producers in villages of the Smallholder Agricultural Productivity Enhancement Program in Sub-Saharan Africa of the ADHs. An analysis of the experimental choice data with the endogenous attribute attendance and the latent class models was carried out to account for the attribute non-attendance phenomenon and the heterogeneity of the producers’ preferences. However, three classes of producer with different socio-economic, demographic, and soil physicochemical characteristics were identified. Thus, the heterogeneity of preferences was correlated with the attributes linked to the cost, sustainability, and frequency of plot maintenance. All producers, regardless of the ADHs, had a strong attachment to accessibility of technologies with short time restoration of soil fertility, and the ability to obtain additional benefits. These latest attributes, added to that relating to cost, tended to have a low probability of rejection in the decision-making process. These results have implications for local decision-makers facing the complex problem of resolving land degradation and local economic development challenges. The generalizability of these findings provides useful insight and direction for future studies in Sub-Saharan Africa.