Multivariate analysis in cotton

The study analyzed the genetic diversity among 30 cotton genotype, which were grouped into seven clusters using Tocher's method. The largest cluster (Cluster I) contained 13 genotypes, followed by Cluster II with 10 genotypes, and Cluster III with 3 genotypes. Clusters IV, V, VI, and VII each contained a single genotype. The study found that intra-cluster genetic distances were smaller than inter-cluster distances, indicating less variation within clusters. Key traits contributing to genetic divergence included days to 50% flowering (43.68%), seed index (12.64%), monopodia per plant (11.49%), boll weight (9.89%), bolls per plant (6.67%), and lint index (6.2%). Principal Component Analysis (PCA) revealed five components with Eigen values greater than 1, explaining 79.68% of the variation. The first principal component (PC1) accounted for 29.16% of the variability, primarily driven by seed cotton yield per plant, sympodia per plant, bolls per plant, and lint yield per plant. Other significant components included days to first picking, fiber fineness, and boll weight. Scatter plot based on PCA showed the genetic diversity of the genotypes, with genotypes like BHV-76, CP-1512, CAK-NS-15 and IAA 3932 located at the vertices of the polygon, indicating they were the most genetically diverse.