GGE biplot and AMMI analysis of grain yield stability and adaptability behaviour of paddy (Oryza sativa L.) genotypes under different agroecological zones of Odisha

The pattern of G ×E interaction (GEI) in shaping the stability and adaptability behaviour of 23 paddy (Oryza sativa L.) genotypes grown under five different test environments (Bhubaneswar, Motto, Chipilima, Jeypore and Ranital) of Odisha state in India during kharif season of 2015 and 2016 and understanding these test environments in terms of their interrelationships, discriminating ability and representativeness for grain yield response of genotypes was analyzed and graphically visualized using additive main effects and multiplicative interactions (AMMI) and GGEBiplot tools. Overall analysis revealed that G17 (OR 2573–12), G2 (OR 2487–13), G14 (OR 2546-9) and G16 (OR 2573–11) were the most stable genotypes with above-average grain yield among all the genotypes owing to their lower value of AMMI stability parameters (ASV, Di) and lesser degree of deviation due to GE component and higher genotypic contribution (G) in the mean & stability-based ranking of genotypes in GGEBiplot. Out of these stable genotypes, based on the contribution of both genotype (G) and GE in GGEBiplot analysis, and AMMI stability parameters, G16 (OR 2573–11) was adjudged as the best genotype among all the genotypes as it exhibited higher degree of yield response coupled with relatively higher stability for grain yield response across all the test environments. "Which-Won-Where" pattern and AMMI2 biplot study revealed G3 (OR 2493-3) and G5 (OR 2500-1) to be the potential genotypes for deployment in Ranital and Jeypore and Bhubaneswar environments, respectively, due to their high degree of specific adaptation for grain yield response in the agroclimatic regimes of these centres. Based on the evaluation of the environments, Bhubaneswar and Jeypore environments of Odisha were found to be suitable for selecting generally adapted genotypes and genotypes with specific adaptive response for yield, respectively. These findings are useful in designing and deployment of environment-specific varietal interventions, selection of niche area of excellence for "quality seed production of specific genotype", agronomic zoning of genotypes and judicious selection of elite genotypes with stable yield which may play a vital role in increasing rice production in future climate change scenario.