High-resolution soybean trial data supporting the expansion of agriculture in Africa.

Understanding how soybean cultivars respond to diverse environmental and management conditions is critical for guiding variety recommendations across African agroecosystems. In this work, we describe a large-scale dataset from multi-environment trials (METs) conducted in Africa over a ten-year period (2015-2024/25). It includes 292 trials carried out in 138 locations across 21 countries, 26,280.00 plots, evaluating 366 soybean varieties. The dataset contains data from morphologic, agronomic and quality traits, as well as detailed environmental information, such as soil features, weather variables, and management practices. We demonstrate the potential of this resource for decision-making in an emerging African soybean production chain by analysing the seed yield across all trials and within specific countries, highlighting cultivar performance and stability. We also applied envirotyping methods to investigate how environmental covariates influence seed yield. This dataset offers a valuable foundation for advancing research on genotype  × environment  × management (G × E × M) interactions and adaptation of soybean germplasm in Africa, supporting genetic evaluation, environmental modeling, and informed decision-making for soybean expansion across the African continent.