Comparison of parametric and non-parametric stability models for yield performance of wheat (<i>Triticum aestivum</i> L.) across different agro-climatic zones of Bihar

Genotype × environment (G×E) interaction significantly influences wheat productivity, underscoring the need to identify genotypes with both high yield and yield stability. In this study, 15 bread wheat genotypes were evaluated across eight environments representing three agro-climatic zones of Bihar. Stability analysis employed the Lin and Binns (1988) cultivar superiority index (a parametric measure) and two non-parametric models (Huehn’s rank-based stability statistics and Kang’s yield-stability index, YSi). Using the Lin and Binns index, genotypes RAUW 120 and DBW 327 had the lowest superiority index (Pi), identifying them as the most stable and widely-adapted. The non-parametric methods gave consistent results: Huehn’s statistics and Kang’s YSi simlarly ranked RAUW 120 and DBW 327 as highly stable. Notably, DBW 303, the highest-yielding genotype, was also ranked among the most stable by Kang’s YSi and Huehn’s statistics, highlighting its excellent performance. Overall, RAUW 120, DBW 327, and DBW 303 emerged as the most desirable genotypes, with RAUW 120 and DBW 327 showing reliable stability across all methods. These results underscore that using multiple stability indices provides complementary insights for robust genotype selection.