The Estimation of the Degree of Genetic Divergence Using Cluster Analysis of the Varietiesof Wheat

A field experiment has beencarried out at eight different environmental sites in the province of Diwaniya for seasonal years in 2014 and 2015 to test nine varieties of different origin wheat (Triticum aestivum L) and assembled in homogeneous groups and assess the degree of divergence between them and estimate distances Euclidean using cluster analysis. The grain yield data analysis using hierarchical consolidation method (hierarchical) after it has been estimating the degree of similarity by creating a matrix of proximities. The result of the cluster analysis to combine items in five groups formed during the ten stages is every group consists of  two varieties  except the fifth group  consists of one variety. The results of cluster analysis shows that cultivars sabah  and Iba 99 have the most similarity the  highest distance Euclidean This refers to the similarity of genes that control the yield  grains, which indicate that the degree of divergence of genetic height and reflects the positive to perform tow variety  and they possess some of the majorfavorite genes and crosses to take advantage of them in education programs, while Ibahas got less Euclidean distance Maxibak of the variety, which shows a genetic dimension of this product may be due to the different genetic origins. Varieties aredistributed to two main groups: the first group (A) includesvariety  (4 and 5) while the second group (B) the rest of the totals and characterized by the average of the sum which is higher including than the first group when is an indication of the existence of favoritesgenes segregated  for a recipe made in the categories for the second group which can benefit from segregation. divergent varieties genetically engineered can be used to improve the local varieties by transferring genes winning one of the superior ways of education breeding because the spacing will ensure that genetic similarity between genes tested varieties.