Abstract

A set of 36 promising genotypes were evaluated for 33 agro-morphological traits. Sufficient genetic variability was found for almost all the characteristics of wheat. Genetic diversity among nineteen traits of wheat genotypes was estimated using Mahalanobis D2 analysis and principal component analysis (PCA). Sufficient genetic diversity was observed among the genotypes and grouped genotypes into five clusters by Tocher’s method. Cluster I contained the maximum numbers of genotypes (32) and the remaining clusters II, III, IV and V were mono-genotypic. The lowest inter cluster distance was noticed between clusters III and I (260.57) and maximum between Cluster IV and V (891.62). The larger inter-cluster distances between clusters were considered more diverged than those with small distances. The major contributing character towards genetic divergence was found to be grain yield per plant (25.24%), followed by wet gluten (21.59%), chlorophyll content (11.11%) and protein content (10.63%). Principal component (PC) analysis resulted in eight principal components (PCs) having Eigenvalue >1 which contributed 78.67 per cent of the total variability amongst the wheat genotypes assessed for various morpho-physiological traits. The traits with the highest weight in component first were the number of tillers per plant, the number of ear per plant, grain yield per plant and harvest index which explained 15.17 per cent of the total variation. Component 2 was associated with protein content and wet gluten content which account for 13.91 per cent variation. In component 3, traits with highest weight were days to heading, days to maturity, plant height, the number of spikelets per ear, ear length and relative water content which explained 13.41 per cent of the total variation. Similarly, the traits with the highest weight in component 4 were sedimentation value; biological yield per plant in component 5; ear weight and chlorophyll content in component 6; peduncle length, 1000-grain weight and canopy temperature in component 7 was the major contributing traits which account for 8.89, 7.78, 7.20 and 6.31 per cent variability, respectively for the above traits. The result of the present study could be exploited in the planning and execution of a future breeding programme in wheat. Key words: Principal component, genetic divergence, cluster analysis &nbsp

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