Trait association and principal component analysis of morphological, biochemical and yield traits in upland cotton (Gossypium hirsutum L.)

Om Prakash Yadav
Minakshi Jattan
Harpreet Singh

Abstract

The present investigation evaluated 127 upland cotton genotypes during Kharif 2021 and 2022 at CCS Haryana Agricultural University, Hisar, to characterize morphological, biochemical, and yield traits using principal component, correlation, and cluster analyses.  PCA analysis showed four components with eigenvalues greater than one, explaining 71.57 % of the total variation. PC1 and PC2 together contributed 53.67 % of the variability and were mainly influenced by biochemical and yield-contributing traits, respectively. K-means clustering of the PCA score plot grouped the genotypes into four distinct clusters, indicating substantial genetic divergence. Correlation analysis showed that seed cotton yield was significantly and positively associated with lint yield, number of bolls per plant, seed index, boll weight, and leaf trichome density. Cluster II exhibited distinct divergence from Clusters I and III, while Cluster IV displayed intermediate variability among groups. Genotypes HS 45, SA 320 F, and Atlas 59-182 showed unique trait combinations, making them valuable for future cotton improvement programs. 

Keywords Clusters, Correlation, Cotton, Principal component analysis.
Published 02/09/26