alexa Traits Diversity Analysis of Malt Barley (Hordeum vulgare L.) Genotypes under irrigation at Koga of west Gojjam in Ethiopia | OMICS International | Abstract
ISSN: 2168-9547

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Research Article

Traits Diversity Analysis of Malt Barley (Hordeum vulgare L.) Genotypes under irrigation at Koga of west Gojjam in Ethiopia

Addisu Tilahun1* and Fisseha Alemu2

1Samara University, College of Dry land Agriculture, Department of Plant Science, Ethiopia

2Addis Ababa University, Institute of Biotechnology, Ethiopia

*Corresponding Author:
Addisu Tilahun
Samara University, College of Dry land Agriculture
Department of Plant Science, Ethiopia
Tel: +251918803371
E-mail: addisu[email protected]

Received date: April 29, 2017; Accepted date: May 11, 2017; Published date: May 18, 2017

Citation: Tilahun A, Alemu F (2017) Traits Diversity Analysis of Malt Barley (Hordeum vulgare L.) Genotypes under Irrigation at Koga of West Gojjam in Ethiopia. Mol Biol 6: 190. doi: 10.4172/2168-9547.1000190

Copyright: © 2017 Tilahun 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.

Abstract

Barley is one of the most highly cultivated crops in Ethiopia. The assessment of genetic diversity using quantitative traits is of prime importance in many contexts, particularly in differentiating well defined populations. The aim of this study was to select superior malt barley genotypes that meet the yield and quality standards for malting purposes. Forty nine malt barley genotypes including two checks were tested at koga of west Gojjam in Ethiopia under irrigation in a 7x7 simple lattice designs with two replications during off season of 2013. Using estimated D² values 49 genotypes were grouped into nine clusters with maximum genotypes (20) in cluster I and (14) in cluster II. Principal component analysis for malt barley genotypes revealed that the first four principal components accounted for more than 68.3% of the variation explained by explanatory variables. Agronomic characters having relatively higher value in the first four principal components had more contribution to the total diversity and they were responsible for the differentiation of the nine clusters. Nonetheless, considering the tremendous variability observed among the genotypes, further testing of these genotypes in different localities is suggested.

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