Estimation of G × E Interaction of Lentil Genotypes for Yield using AMMI and GGE Biplot in Pakistan

Stable high-yielding varieties are the goal of plant breeding rather than just focusing on high yield because the changing environment has a significant role in the final response of the plants. Therefore, 20 lentil genotypes were evaluated for genotype × environment interaction (GEI) and yield stability across seven environments during two growing seasons. Genotypes were sown in RCBD with three replicates. ANOVA for individual environments and also three-way pooled ANOVA were performed. Additive main effects and multiplicative interaction (AMMI) analysis was performed to identify the stable genotypes and to study genotype-environment-interaction (GEI). Moreover, GGE biplots were developed to identify mega-environments and environment-specific genotypes. Yield, AMMI-stability-value (ASV), and genotype selection index (GSI) were used for selection of superior genotypes. Genotypes, environments, and genotype × environment interaction showed highly significant ( p < 0.001) pooled ANOVA with environment and GEI explaining 57% of the total variation. AMMI model revealed that IPCA1 and IPCA2 (principal components 1 and 2) were highly significant ( p < 0.001) and explained 49.3% of the total variation in yield. GGE biplot components PC1 and PC2 are explained as 34% and 18%, respectively. Based on yield, G6, G4, and G2 were ranked highest, while on basis of ASV, G18, G3, and G19 were identified as the most stable because of their low ASV. Out of 20 genotypes studied, G6 was ideal genotype with stable yield and four genotypes G2, G4, G5, and G7 were identified as desirable. Five mega-environments were identified with respective suitable genotypes. The significant genotype × environment interactions (GEI) and the change in stability ranks across environments suggest a breeding strategy for selecting genotypes specifically adapted in mega-environments.