The analyses like Additive Main effect and Multiplicative Interaction (AMMI) and Genotypic and Genotypic-by-Environment (GGE) analysis are being used world-wide to interpret Multiple Environment Trial (MET) very successfully by many researchers especially plant breeders. Measurement of relevant performance of tested genotypes and their stability over a number of tested environments particularly in terms of their yields, is the key objective in the development of high yielding varieties and is an important goal in plant breeding programs. The objective of this study was to study genotype Ã— environment (G Ã— E) interaction and its impact on rice yield stability. Eight cultivars including one check variety (Basmati 515) were tested at five different agro-ecological sites. Combined analysis of variance clarifies that the G Ã— E component was highly significant for rice paddy yield across various environments in Punjab Province, Pakistan. Thus, we proceeded with statistical analysis using AMMI and GGE biplot analyses to calculate the interactions and define their main effects, and calculated phenotypic stability. AMMI analysis of variance of paddy yield was highly significant and was affected by environments, genotypes and G Ã— E interaction. The amount of GÃ—E interaction sum of squares established that there were significant differences in genotypic responses across environments. First two Interaction Principal Components that is, IPCA1 and IPCA2 combined had almost equivalent sum of squares to genotypes and contributed to 86.29% of the total GEI. Both of these principal component axes of interaction were also very highly significant (p < 0.001). AMMI analysis depicts that PK8660 (FV7) was the highest yielding genotype and the most stable among all the genotypes studied, after PK8667 (FV6) which was also showed higher yields after PK8660. Therefore, these two lines being higher yielder and stable can be used for general cultivation. Site Farooqabad was the most stable and most productive environment. PK8680 was among four highest yielders at all the studied locations, indicating that this line had both the characters of best performance and stability to be the best genotype. Results of AMMI further show that genotypes FV2, FV3, FV5, FV7 and FV8 performed better at locations E1 and E5. Other all genotypes were better performing at E2, E3 and E4 locations. GGE biplot also depicted the same results. AMMI and GGE analysis further divided genotypes and environments in two genotypic groups and mega-environments. It can be concluded that both AMMI and GGE analyses are equally helpful in assessing the Multi-Environment Trial (MET) data.
Keywords: Additive main effect and multiplicative interaction (AMMI), genotypic and genotypic-by-environment (GGE), varietal adaptation, yield stability, GÃ—E interaction, rice (Oryza sativa L.)