Envirotyping-driven strategies to enhance soybean adaptation across Southern Africa.

UNLABELLED: Soybean has become a strategic crop in global agricultural systems due to its central role as a source of vegetable protein and oil, while rising demand and increasing environmental variability continue to challenge cultivar development and deployment. In this context, Southern Africa has emerged as a promising region for soybean expansion, although progress remains constrained by strong genotype-by-environment interaction (G [Formula: see text] E) interactions and the limited availability of adapted cultivars. Thus, this study aimed to (i) delineate Macro Environments (MACROs) through envirotyping-based environmental characterization in Southern Africa, (ii) rank genotypes within each MACRO using the Factor Analytic Selection Tool (FAST) from factor-analytic (FA) mixed models, and (iii) identify redundant trial sites to optimize the testing network without compromising selection reliability. Grain yield data from 180 genotypes evaluated in 97 environments (2017–2023) across Malawi, Mozambique, Zambia, and Zimbabwe were analyzed. We compiled 40 environmental features describing climate, soil, elevation, and Sentinel-2 spectral information, and applied PCA followed by k-means clustering to define four MACROs with distinct edaphoclimatic conditions. Within MACROs, FA mixed models captured the major patterns of G [Formula: see text] E and supported prediction under unbalanced connectivity, explaining 80–95% of the genetic variance. Genotypes were then ranked jointly by overall performance and stability (RMSD), enabling the identification of both broadly adapted and MACRO-specific candidates. Redundancy analysis based on environmental distance, genetic correlation, and rank concordance enabled pruning of approximately 15% of environments per MACRO while maintaining Cullis heritability and preserving 60–75% overlap in the top-20 selections. Importantly, broadly adapted genotypes represent promising candidates for cultivar release and wider regional deployment, whereas MACRO-specific selections support more precise genotype recommendation and improved targeting of breeding efforts across contrasting production environments in Southern Africa. Overall, integrating envirotyping-based MACRO definition with factor-analytic modeling and multi-criteria ranking provides a robust and operational framework to optimize MET networks and improve cultivar targeting for soybean production and expansion in diverse conditions in Southern Africa.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1038/s41598-026-48028-x.