The Application of D2 Statistic to Measure Genetic Divergence in Different Bread Wheat Genotypes

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Date

2014-06

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Addis Abeba university

Abstract

Wheat is one of the most important cereal crop in Ethiopia, ranking third in total production next to maize and teff. Wheat covers a total arable land of 110,434 ha with average productivity of about 8.4 qt /ha, which is below the national production average (14.4 qt /ha). The objective of this research was to study the genetic dissimilarity among twenty bread wheat genotypes. The study is made based on twenty bread wheat genotypes which was obtained in 2007 and 2008 from trials conducted by the Ethiopian Institute of Agricultural Research (EIAR) and were evaluated for their diversity to estimate the genetic divergence and clustering them into homoGenous groups for the hybridization program in 8 environments using Mahalanobis D2 statistic. The D2 value data can be used in cluster analysis to identify groups of related cultivars. Using UPGMA clustering technique all the Geno types were grouped into six cluster on the basis of D2 value using Tocher's optimization technique. The intra- and inter-cluster D2 values suggested that within cluster genetic diversity is narrow, but the genetic diversity among clusters is greater. Therefore, The presence of significant genetic variability among the evaluated bread wheat genotypes suggests an opportunity for improvement of grain yield through hybridization of genotypes from different clusters and subsequent selection from the segregating generations would broaden the genetic base of bread wheat breeding populations. Thus, those analysis based on multivariate methods using D2 statistic is useful in providing information for more efficient variety development programmes.

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Statistic to Measure Genetic

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