Trait Variability, Genotypic Relationships, and Cluster Analysis of Aromatic Rice RILs for Agronomic Improvement - Prabhat Kumar Singh,; Shambhoo Prasad; Abhishek Kumar Verma; Vandna Kushwaha; Hemant Kumar Yadav; Ashwini Kumar; Adesh Kumar; Nawaz Ahmad Khan (The Bioscan, 2025)
Aromatic rice is renowned for its premium grain quality and export potential, yet breeding efforts are often hampered by low yield and limited genetic diversity. This study evaluated 48 recombinant inbred lines (RILs), derived from a cross between Rajendra Bhagwati and Pusa Sugandh-5, to identify elite genotypes with superior agronomic and physiological traits. Field experiments were conducted during the Kharif seasons of 2023 and 2024 using a randomized block design with three replications. Twelve traits were assessed: days to 50% flowering (DFF), flag leaf area (FLA), days to physiological maturity (DPM), plant height (PH), number of tillers per plant (NOT), panicle length (PL), number of spikelets per panicle (NSP), number of grains per panicle (NGP), spikelet fertility percentage (SF%), test weight (TW), biological yield per plant (BY), and grain yield per plant (GYP). Substantial phenotypic variability was observed, with high coefficients of variation for traits like FLA, PH, NSP, and GYP. Genotypic correlation analysis identified strong positive associations between GYP and traits such as BY, NGP, and PL, indicating their significance in indirect selection. Rajendra Bhagwati exhibited early flowering and superior grain yield, while Pusa Sugandh-5 showed higher tiller number and test weight. Hierarchical cluster analysis grouped genotypes into three distinct clusters, with Cluster III containing transgressive segregants outperforming both parents in yield-contributing traits. The study demonstrates the effectiveness of integrating phenotypic screening and multivariate analysis to identify promising RILs for aromatic rice improvement and varietal development under diverse agro-climatic conditions.