Evaluate the Genetic Divergence and Principal Component Analysis in Bread Wheat (Triticum aestivum L.)
Jayant Kumar *
Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur (Uttar Pradesh) 208002, India.
Vijay Kumar Yadav
Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur (Uttar Pradesh) 208002, India.
R. K. Yadav
Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur (Uttar Pradesh) 208002, India.
Som Veer Singh
Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur (Uttar Pradesh) 208002, India.
Shweta
Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur (Uttar Pradesh) 208002, India.
C.L. Maurya
Department of Seed Science and Technology, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur (Uttar Pradesh) 208002, India.
Ankitesh Kumar
Department of Genetics and Plant Breeding, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur (Uttar Pradesh) 208002, India.
*Author to whom correspondence should be addressed.
Abstract
The current investigation was carried out on some bread wheat (Triticum aestivum L.) genotypes throughout spring season to evaluate their heat tolerance via Cluster Analysis and principal component analysis (PCA). The experiment was accomplished in an augmented block design with 60 genotypes and three replications. Evaluations were carried out on 26 quantitative traits. Cluster analysis showed five clusters, cluster I with 56 genotypes and clusters II, III, IV and V with only one genotype each. The clusters II, III, IV and V have only one genotype each, so their intra-cluster distances were zero. The intra-cluster distance for cluster I was 57.879. The maximum and minimum inter cluster distance was found between cluster II and III (267.377) and between cluster I and II (86.469), respectively. Cluster I showed the earliest (76.689 days) average for early maturity (days to 50% heading) and cluster III showed the maximum (27.664) average for grain yield (grain yield per plant). PCA indicated that the five principal components (PC1 to PC5) accounted for 65.61% of the total variance. PC1 accounted for 11.51% of the total variance and showed positive factor loading for almost traits. Harvest index, grain yield per plant, flag leaf width and leaf rolling showed the highest factor loadings for PC1. As a result of the foregoing data and analysis, it is possible to conclude that there is great potential for effective genetic improvement for grain yield and correlated traits in the present wheat genotypes.
Keywords: Wheat, genetic divergence, cluster analysis, morphological traits