Classification and Characterization of Elite Cotton Lines for their Agronomic Performance through Multivariate Statistical Approaches

Abstract

Cotton (Gossypium hirsutum L.) productivity in semi-arid regions is constrained by climatic stress and genetic limitations, necessitating the identification of high-performing and adaptable genotypes. The present study was conducted to evaluate the genetic variability, trait associations, and yield potential of thirty-two cotton genotypes under semi-arid conditions at the Cotton Research Station, Bahawalpur, Pakistan. The experiment was laid out in a randomized complete block design with three replications. Data were recorded on key agronomic, physiological, and fiber quality traits, including plant height, nodes per plant, monopodial and sympodial branches, green bolls, open bolls, seed cotton yield, fiber length, net photosynthetic rate, and ginning out turn. Analysis of variance revealed highly significant differences among genotypes for all studied traits, indicating substantial genetic diversity. Correlation analysis showed that seed cotton yield was positively and significantly associated with open bolls (r = 0.470^*), green bolls (r = 0.455^*), sympodial branches (r = 0.443^*), monopodial branches (r = 0.424^*), nodes per plant (r = 0.369^*), and plant height (r = 0.446^*), while a significant negative correlation was observed between yield and fiber length (r = -0.769^**). Cluster analysis grouped the genotypes into two distinct clusters, with Cluster-1 exhibiting superior yield, higher boll number, and enhanced photosynthetic activity. Principal component analysis explained 78.41% of the total variability through the first three principal components, highlighting yield and yield-contributing traits as major sources of genetic divergence. Cotton genotypes Emp-1, SI-3, and SI-22 demonstrated superior performance and can be exploited in future breeding programs aimed at improving cotton productivity under semi-arid environments.