MGIDI-BASED MULTI-TRAIT SELECTION AND GRAIN QUALITY ASSESSMENT IN SEGREGATING RICE (ORYZA SATIVA L.) POPULATION

Abstract

Consumption of nutrient-deficient rice contributes to global malnutrition and hunger, highlighting the need for nutritionally enriched rice cultivars. With this perspective, the Tunga x KHP 13 cross lines were evaluated during the wet season 23 at ZAHRS, Mudigere, to investigate MGIDI-assisted selection to identify lines of better performance. High values of phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were for the number of filled grains per panicle (20.39% and 20.03%, respectively). Most characters showed minimal differences between PCV and GCV. Filled grains per panicle, productive tillers per plant, spikelets per panicle, tillers per plant, and panicle length showed a significantly positive association with grain yield. A positive direct effect on grain yield was observed for days to maturity, productive tillers per plant, panicle length and filled grains per panicle. The top 10 superior lines identified by MGIDI-based selection index were analyzed for quality parameters. Entry 40 (38.50, 33.65ppm), 33 (35.20, 32.35ppm), and 49 (30.29, 29.36 ppm) outperformed all other lines in zinc content in brown rice and milled rice, respectively. For iron content, these 3 lines, Entry 40 (13.40, 10.79 ppm), 33 (14.80, 12.92 ppm), and 49 (12.20, 11.43 ppm), have outperformed parents as well as other high-yielding lines. The correlation analysis of grain quality parameters with grain yield shows that all the traits, mainly Zn BR (0.30), Zn MR (0.28), Fe BR (0.38), Fe MR (0.19), total starch (0.28), amylose (0.36), and amylopectin (0.029) have a weak positive correlation.