Evaluation of Genetic Variability and Divergence for Yieldcontributing Traits in Wheat (Triticum aestivum L.)

The present investigation was carried out at the Research Farm, Faculty of Agriculture, Tantia University, Sri Ganganagar, during the Rabi season of 2024–2025 to evaluate thirty wheat (Triticum aestivum L.) genotypes to assess variability, heritability, genetic advance, and genetic divergence using hierarchical cluster analysis. Analysis of variance revealed significant differences among genotypes for all traits, confirming substantial genetic variability. Mean performance across genotypes indicated moderate to high values for key traits, with grain yield per plant (16.19 g), biological yield (41.82 g), and test weight (35.98 g) serving as benchmarks for comparative assessment. Wide variation was observed, particularly for grain yield (10.59-26.15 g), biological yield (20.27-66.43 g), and plant height (75.82-98.33 cm), reflecting the diverse genetic base. Estimates of genetic parameters revealed that phenotypic coefficient of variation (PCV) consistently exceeded genotypic coefficient of variation (GCV), indicating environmental influence; however, narrow differences for grain yield per plant, biological yield, and test weight suggested strong genetic control. High heritability coupled with high genetic advance as percent of mean (GAM) was recorded for biological yield (74%, 35.26%), harvest index (89%, 31.20%), and grain yield per plant (69%, 28.64%), pointing to the predominance of additive gene action and the reliability of direct selection for these traits. Hierarchical clustering grouped the genotypes into five distinct clusters, with Clusters II and IV being the most populous, while Clusters I and V were mono-genotypic, reflecting unique divergence. Maximum inter-cluster distance (9.28) between Clusters I and V highlighted their potential as parents for generating heterotic combinations. Cluster III excelled in yield components, while Cluster V combined early maturity with the highest grain yield per plant (42.74 g), underscoring its relevance for climate-resilient breeding. Overall, the study demonstrated the presence of robust variability and identified key traits and divergent clusters that can be strategically exploited to accelerate wheat improvement programs.