GENETIC VARIABILITY, TRAIT ASSOCIATION, AND YIELD PERFORMANCE OF ADVANCED WHEAT LINES USING MULTIVARIATE STATISTICAL ANALYSIS

Abstract

Wheat (Triticum aestivum L.) productivity in semi-arid regions is constrained by climatic stress and genetic limitations, necessitating the identification of high-performance and adaptable genotypes. The present study was conducted to evaluate the genetic variability, trait associations, and yield potential of fifteen wheat genotypes under semi-arid conditions at The Islamia University of Bahawalpur, Pakistan. The experiment was carried out in a randomized complete block design with three replications. Data were recorded on yield-related traits, including plant height, thousand-grain weight, number of tillers per plant, days to heading, days to maturity, number of grains per spike, peduncle length, and yield. Analysis of variance revealed highly significant differences among genotypes for all studied traits, indicating substantial genetic diversity. Correlation analysis showed that yield was positively and significantly associated with plant height (r = 0.906**), thousand grains weight (r = 0.897**), number of tillers per plant (0.921*), days to heading (r = 0.951**), days to maturity (r = 0.950**), number of grains per spike (r = 0.990**) and peduncle length (r = 0.985**). Cluster analysis grouped the genotypes into two distinct clusters, with Cluster-2 exhibiting superior yield, high thousand-grain weight, number of tillers per plant, number of grains per spike, and days to maturity. Principal component analysis explained 98.74% of the total variability through the first two principal components, highlighting yield and yield-contributing traits as major sources of genetic divergence. Wheat genotypes FWP-11, SSW-10, and ABW-1 demonstrated superior performance and can be exploited in future breeding programs aimed at improving wheat productivity under a semi-arid environment.