Application of multivariate analysis to study genotype × environment interaction in sesame (Sesamum indicum) under stress conditions

Abstract

The present research aimed to study seed yield stability of 12 sesame (Sesamum indicum L.) genotypes evaluated across six environments (two growing years × three irrigation intervals). Data on seed yield were subjected to additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype × environment interaction (GGE) analyses using GenStat software. Results showed that environments main effect explained 73.9% of the total variation in seed yield compared with genotypes (12.3%) and genotypes × environment interactions (GEI) (10.9%). IPCAs showed significant effects and accounted for a total of 65.9% of GEI. IPCA1 had higher significant contribution to GEI (44.0%) than IPCA2 (21.9%). Based on AMMI stability value (ASV), genotypes 2, 3 followed by genotypes 1 and 11 were identified as the most stable and high yielding genotypes across tested environments. Furthermore, Environment 5, which is close to the biplot origin, is expected to be candidate environment for stable and repeatable genotype testing. Using GGE biplot model, considered G1, G7, G3 and G2 to be the most stable genotypes as they had the shortest vectors, moreover the most yielding genotypes were G7 and G2 as they were the most distance from the right side of the biplot and their yield surpassed the environmental mean. Introduced breeding lines are effective genetic source than local cultivated cultivars for high seed yield, such genotypes would be potential parental lines in sesame breeding programs.