Dataset on developing low glycemic index rice variety suitable for irrigated ecosystem in Bangladesh.

This dataset offers a comprehensive analysis of rice grain yield and quality traits over a period of three years, spanning 27 different environments in Bangladesh. The focus is on evaluating the performance of various genotypes (G), environments (E), and their interactions (GEI). The study's goal is to identify a stable and adaptive rice genotype that not only exhibits high-quality traits but also has a low glycemic index. The combined ANOVA showed significant effects of G, E, and GEI on grain yield ( ≤ 0.001). Genotype BRC266-5-1-1-1 achieved the highest average yield at 7.62 t/ha, while BRRI dhan28 had the lowest yield at 6.87 t/ha. In the Y2E4 environment, genotype BRC266-5-1-1-1 reached the highest yield at 8.86 t/ha. Genetic parameter estimation revealed significant effects of G, E, and GEI ( < 0.05), with GEI accounting for 82.85 % of the variance. The broad-sense heritability was low at 12 %, but the heritability of means was 0.80, indicating high selection accuracy (0.89). AMMI analysis showed significant effects from E (62.62 %) and GEI (16.19 %), with the first two principal components explaining 100 % of the variance. AMMI-based stability analysis identified BRC266-5-1-1-1 as the most stable genotype, with the highest AMMI-based stability parameter (ASTAB) at 2.11 and AMMI stability value (ASV) at 3.04. GGE biplot analysis revealed that BRC266-5-1-1-1 performed best in 14 environments. Quality trait analysis showed that BR16 and BRC266-5-1-1-1 had the highest milling outturn (70.90 %), with BRC266-5-1-1-1 also having the highest head rice yield (66.5 %). BRRIdhan28 had the highest glycemic index value (GIV) at 75.7, followed by BRC266-5-1-1-1 (55.04). These findings emphasize the significance of choosing appropriate genotypes for varietal release and taking environmental factors into account in rice breeding programs.