Assessment of Genetic Variability, Correlation and Path Analysis in Wheat (Triticum aestivum L.)

Abstract

A study was conducted during the Rabi 2024–2025 season at Tantia University, Sri Ganganagar, Rajasthan, India, to evaluate genetic variability, correlations, and path coefficients for yield and yield-contributing traits in 30 wheat genotypes sourced. The experiment, set in a Randomized Complete Block Design with three replications, assessed traits including grain yield, grains per spike, tillers per plant, 1000-grain weight, biological yield, and harvest index under semi-arid conditions. Analysis of variance revealed significant genotypic differences (p < 0.01) for all traits. High genotypic and phenotypic coefficients of variation (GCV: 20–25%, PCV: 25–30%), heritability (>80%), and genetic advance (>30%) were observed for grain yield and grains per spike, indicating strong selection potential. Strong positive genotypic correlations were found between grain yield and grains per spike (r = 0.75), tillers per plant (r = 0.65), and 1000-grain weight (r = 0.70), with a negative correlation between tiller number and spike length (r = -0.30). Path analysis identified biological yield (direct effect = 0.80) and harvest index (direct effect = 0.75) as major contributors to grain yield, with grains per spike (0.60) and tillers per plant (0.55) showing moderate direct effects. The findings highlight grains per spike, grain yield, biological yield, and harvest index as key traits for phenotypic selection, with tillers per plant and 1000- grain weight as secondary traits for indirect selection. The diverse germplasm, including high- performing genotypes like PBW-826 ,DBW-222 ,HD-3086 , AKDW-4905, and GW-1330 performed consistently well for yield and related traits, making them prime candidates for further breeding and improvement programs., supports breeding high-yielding, resilient wheat varieties for Rajasthan’s semi-arid conditions, aligning with India’s 2% annual genetic gain target. Multi-environment trials and molecular marker integration are recommended to enhance trait stability and selection efficiency.