Evaluating soybean genotype-by-environment interactions and multi-trait stability across South African environments

Abstract

Soybean is one of the significant legume crops in South Africa, yet genotype × environment interactions (GEI) complicate reliable cultivar selection. Despite this, GEI, performance, and stability of soybean genotypes have not been comprehensively evaluated across South Africa’s major soybean–producing provinces (Mpumalanga, North–West and Free State). Therefore, this study assessed GEI, performance, and stability of soybean genotypes across key agronomic traits using multi–environment trials (METs) over three growing seasons. Additive main effects and multiplicative interaction (AMMI) and genotype plus genotype–by–environment (GGE) biplot approaches were used to quantify trait variation, identify best genotypes, and characterizing environmental relationships. Stability and performance were further assessed using multi–trait stability index (MTSI), weighted average of absolute scores (WAASB), and weighted average of absolute scores and yield (WAASBY), while chord diagrams visualized inter–trait correlations. Results indicated that environmental effects dominated trait variation across all traits. Which–Won–Where patterns revealed that no genotype excelled across all environments, but G5 (LG60260IPRO) was the best genotype across all evaluated traits, particularly in cool (E1) and moderate (E2) environments across seasons. Vector analyses showed positive correlations among environments within the same location and negative correlations among contrasting environments. WAASB highlighted G8 (PAN1521R) as the most stable and high–performing genotype across all evaluated traits with dominant performance in moderate environment. WAASBY identified G5 as a superior genotype across all traits, with superiority particularly evident in cool and moderate environments. MTSI identified G2 (DM59I60 RSF IPRO) as a consistently stable genotype across all evaluated environments. Chord diagrams revealed predominantly positive inter–trait correlations across all traits in E2 and mixed correlations in E1 and E3 (warm environment). Overall, the identified superior, high–performing, and stable genotypes are promising candidates for cultivar recommendation and soybean breeding programmes targeting productivity, stability, and adaptation across South Africa’s diverse environments.