Multivariate Analyses of Phenotypic Diversity of Bread Wheat (Triticumaestivum L.) in the Highlands of Northern Ethiopia
Received Date: Sep 07, 2017 / Accepted Date: Sep 19, 2017 / Published Date: Sep 27, 2017
An assessment of genetic variation within diverse germplasm is needed to allow more efficient genetic improvement. Forty-nine bread wheat genotypes were evaluated for 11 traits in simple lattice design at two locations to determine the extent of genetic diversity among the genotypes for grain yield and other agronomic traits. Mean squares of the traits studied showed statistically significant differences among the genotypes listed (P<0.01), indicating the presence of adequate variability. In the PC analysis, five PCAs explained 80.4% of total variability residing in the bread wheat genotypes. The first principal component, followed by the second, had the largest variance, and consequently explained much of the variability in the bread wheat genotypes. The traits which were important in these PCAs, plant height, grain yield, number of productive tillers, days to heading, spike length and number of spikelets per spike are the important traits in differentiating the genotypes. Average linkage cluster analysis classified the 49 genotypes into six clusters. Higher inter-cluster distance was exhibited between cluster I and III (D2=25.79**) followed by cluster II and IV (D2=22.82), and cluster II and III (D2=22.75), indicating wider genetic diversity among these clusters. Thus, future crossing program between members of cluster I with cluster III, and cluster II with III and IV could possibly result in heterosis in the F1, and a great deal of variability in the F2 generations.
Keywords: Bread wheat; Cluster analysis; Genetic distance; Grain yield; Principal component analysis
Citation: Getachew A, Worede F, Alamerew S (2017) Multivariate Analyses of Phenotypic Diversity of Bread Wheat (Triticum aestivum L.) in the Highlands of Northern Ethiopia. Adv Crop Sci Tech 5: 309. Doi: 10.4172/2329-8863.1000309
Copyright: © 2017 Getachew A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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