Evaluation of Rice Genotypes for Yield Stability and Adaptability Across Multiple Environments Using AMMI and GGE Biplot Analysis
O Reshma, P Surendra, S Bhaskar Reddy, K M Shivaprasad
Journal of Advances in Biology & Biotechnology · pp. 1164–1176 · Published 8 Aug 2024
10.9734/jabb/2024/v27i81239Abstract
The study aimed to identify elite rice genotypes with the highest yield response and broad adaptability, as well as those with specific adaptability to unique or groups of environments. Three different environments were selected for the experiment with 23 rice genotypes in Dharwad, Malagi, and Sirsi, Karnataka, during the year 2020 (Kharif season). The ANOVA revealed that environments contributed the highest (33.5%) to the total sum of squares, followed by genotypes × environments (21.7%), indicating a major role played by environments and their interactions in realizing final yield. The AMMI 1 analysis identified rice genotypes BA04, BA07, BA10, BA09, and BD07 as highly stable, positioned near the origin of the biplot with smaller ASV and Di values. The AMMI2 model revealed a positive association of genotype BD08 with the Dharwad environment and BD05 with the Sirsi environment, consistent with the recorded grain yield data. The GGE biplot genotype view identified genotype BD08 as the ideal genotype, followed by BA08, with higher mean yield and good stability, while D6-2-2 and BD10 were found to be the most unstable. The GGE biplot environment view showed that Dharwad was the most ideal for adaptability and discriminating environment, followed by Sirsi, while Malagi was the least discriminating. What-won-where biplot indicated that all the three environments fell into two mega environments. Hence, BD08 was the winning genotype in mega environment 1 consisting of Dharwad and Malagi. While the genotype BD05 was the winner in mega environment 2 i.e Sirsi.
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