Genetic Parameters Estimation and Identification of Promising Rice Genotypes Grown in Rainfed Condition Using Mgidi Index in Rampur, Chitwan: Genetic Evaluation and Selection of Rice Genotypes in Rainfed Rampur - Roka, Punam; Adhikari, Bhim Nath; Shrestha, Suraj; Roka, Dikshya; Adhikari, Avilasha; Shreepaili, Briksha (SAARC Journal of Agriculture, 2025)
Rice, the world’s most vital crop with over 40,000 varieties cultivated for 8 to 13 thousand years, produced around 520.65 million metric tons annually—largely in China, India, and Bangladesh—while nearly half the global population relies on it as a primary food source, facing significant challenges in rainfed areas that impede productivity. This study evaluated 24 rice genotypes, including 22 pipeline varieties from the National Rice Research Program (NRRP) in Dhanusa and two checks, Bahaguni-2 and Sabitri. The Multi-Trait Genotype-Ideotype Distance Index (MGIDI) was used as selection tool to rank genotypes based on their proximity to an ideal genotype. Broad-sense heritability (h²) estimates ranged from 0.03 for panicle length to 0.96 for days to 80% maturity, suggesting high potential for selection gains in days to 80% maturity (h² = 0.96) and plant height (h² = 0.91), while tiller number and grain yield showed low heritability (h² > 0.5). Variance analysis indicated substantial genetic control for plant height and days to 80% maturity, while panicle length and grain yield were more influenced by environmental factors. Principal component analysis revealed four factors explaining 76.5% of the trait variation, with FA1 (days to 50% flowering, days to 80% maturity) accounting for the most variation. Selection gains were assessed using MGIDI and FAI-BLUP indexes, with MGIDI achieving a 15.13% gain for targeted traits and FAI-BLUP yielding 1.25%. Selected genotypes from MGIDI included SVIN 127, SVIN 098, SVIN 643, SVIN 084, and IR 18F1085, with SVIN 127 and SVIN 098 also appearing in the FAI-BLUP index, highlighting their potential value for breeding. This research demonstrates the effectiveness of both selection indexes in identifying superior genotypes for enhanced breeding efficiency. SAARC J. Agric., 22(2): 239-255 (2024)