A multi-trait index framework for dissecting genotype stability and adaptability in soybean across environments

Recognized as a key legume, soybean underpins food security and economic sustainability, yet genotype performance often varies across environments, requiring robust selection frameworks that account for genotype × environment interaction (GEI s ) and multi-trait responses. This study evaluated the stability, adaptability, and multi-trait performance of 20 Indonesian soybean genotypes across three contrasting environments representing upland and lowland production systems. Combined analysis of variance revealed significant effects of genotype, environment, and GEI for most agronomic traits, confirming that both genetic and environmental factors substantially shape soybean productivity. To strengthen selection efficiency beyond conventional approaches, we integrated the Multi-Trait Genotype–Ideotype Distance Index (MGIDI) to identify ideotype-proximal genotypes within environments and the Multi-Trait Stability Index (MTSI) to rank genotypes for broad stability across environments. MGIDI highlighted genotypes K17, K18, and K5 as closest to the ideotype in their respective environments, whereas MTSI identified K1, K12, and K5 as the most stable across environments. Factor analysis within the MTSI framework explained 87% of total variation and indicated that productivity-related traits, including yield, 100-seed weight, and seed filling period, contributed substantially to multi-trait performance and stability across environments. Trait association and network analyses further revealed strong positive linkages among yield component traits, suggesting synergistic relationships that can be jointly targeted to enhance productivity. Overall, the combined MGIDI–MTSI framework provided complementary insight into both environment-specific adaptation and broad stability, identifying K5 as promising parental materials for breeding programs targeting heterogeneous production environments.