Estimate the Genetic Diversity with PCA in Bread Wheat (Triticum aestivum L.)
Ankitesh Kumar, Vijay Kumar Yadav, C.L. Maurya, Som Veer Singh, Shweta, Jayant Kumar, Bukke Sai Dev Naik
Journal of Scientific Research and Reports · pp. 207–217 · Published 16 Mar 2024
10.9734/jsrr/2024/v30i51935Abstract
The present investigation was carried out on bread wheat (Triticum aestivum L.) crop during rabi season with the aims of analysis of genetic diversity with the help of principle component analysis. The experimental sample size included 80 genotypes, in an augmented block design with three replications. Observation was based upon twenty-six quantitative characteristics. For all characteristics Cluster I had highest number of genotypes (28) followed by cluster II (5), cluster IV, cluster V and cluster VI had presented (4), cluster VII and VIII (3), cluster III, cluster IX, cluster X, cluster XI and cluster XII (2) whereas cluster had presented one entry in each group. The minimum intra cluster distance (0.00) was found for XIII to XXXI and maximum was found for cluster XII (2.10). The maximum inter-cluster distance was found between cluster XX to XXVII (11.08). The minimum inter- cluster D2 value found in case of cluster IV to XVI and XXX to XXXI (2.12). Cluster XVIII showed earliest mean value for day to 50 per cent flowering (75.24 day) and most important character maximum mean value for yield per plot (536.13). Principal component analysis (PCA) indicated that the five principal components (PC1 to PC5) showed 50.37 per cent of the total variability. The five different groups positive maximum variable loaded component PC I for grain yield per plant (23.2542), PC II flag leave area (19.4005), PC III for peduncle length (23.9893), PC IV grain length /width ratio (21.0627), PC V for physiological maturity (16.7492). As a result of the foregoing data, it is possible to conclude that there is great potential for effective crop modification for improved yield and yield-attributing traits in present wheat germplasm.
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