Abstract

Plant phenotype assessment approaches have facilitated crop improvement in recent years by providing opportunities for the dissection of complex nature quantitative traits. Fiber quality and yield are significant economic traits with a complex nature mainly due to interactions between its genetic architecture and the surrounding environment. These economic traits showed stagnant performance in recent decades due to eroded genetic diversity via the selection process. It necessitates exploiting conserved germplasm resources to rebuild genetic diversity within cotton cultivars. Compared to the conventional univariate selection methods using a single trait at a time, the multivariate analysis extends its selection to multiple variables for the selection of genotypes. In evaluating a core collection of cotton over two years using various phenotyping methods, multivariate analysis, particularly principal component analysis (PCA), was employed to assess genetic diversity. The PCA analysis demonstrated substantial variability of 39.83% and 45.37% across two years, highlighting a significant impact on yield and fiber quality attributes. The cumulative eigenvalues of principal components exceeding 80% supported the classification of accessions into six distinct groups based on their trait variability. Both PCA and cluster analysis successfully categorized accessions into six groups, indicating high diversity and suggesting their potential utility in breeding programs. The diverse genotypes identified in this study would be potential resources for variety development and accelerated breeding programs, particularly focusing on stress resilience under climate change scenarios. By utilizing these diverse genotypes, there is an opportunity to enhance breeding strategies and accelerate the development of improved cotton varieties with enhanced yield and fiber quality attributes. The significance of our study lies in its demonstration of the importance of genetic diversity in improving yield and fiber quality attributes, thus underscoring its relevance to cotton breeding programs.

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