Parametric and Non-parametric Statistical Approaches for Estimation of Genotype × Environment Interaction of Pigeon Pea [Cajanus cajan (L.) Millspaugh] Genotypes

Background: The genotype-by-site interaction might be stronger than the genotype-by-year interaction, making it difficult to identify superior genotypes in multi-location trials. This is influenced by the Genotype × Environment interaction (GEI). The estimation of G, E and G × Einteractions (or GEI) ensures valid recommendations of suitable varieties able to overcomethe pressure due to variable occurring conditions. The determination of GEI factors helps geneticists in their breeding programs to shift the selection toward varieties suited for wide environments or specific to certain niches. Methods: This requires genotype evaluation in multi-environment trials in the latter stages of selection. To evaluate genotype-environment interaction (GEI), fourteen pigeon pea genotypes were studied in four Gujarat sites. The additive main effects and multiplicative interaction (AMMI) analysis of variance (ANOVA) showed that genotype-environment interaction (GEI), IPCA 1 and IPCA 2 were significant across all genotypes. Result: Pigeon pea genotype NPMK-15-05 (G9) yielded best. AMMI 1 and 2 plots showed stable ICPL-87119 (G12) and BP-12-31 (G5) genotypes. The genotypes with the strongest non-parametric stability were NPMK-15-05 (G9), ICPL-87119 (G12), and NPMK-15-03 (G8). GGE (Which-win-where) biplot analysis showed that NPMK-15-05 (G9) won.