Analysis of genetic divergence for quality improvement of rapeseed and mustard

Abstract

Twenty two genotypes of Brassica (B. rapa, B.iuncea, and B. napus) were studied for genetic divergence using principal component analysis and nonhierarchical Euclidean cluster analysis on the basis of major fatty acid compositions. The genotypes were grouped into four clusters irrespective of the geographical divergence. Cluster I, III, and IV consisted of six genotypes each followed by cluster II and it was 4. Cluster I had the highest mean value for stearic acid and erucic, while the lowest value was for palmitic acid, linoleic, and linolenic acid. Cluster II had only the lowest mean value for stearic acid. Cluster III showed the highest mean value for palmitic acid, oleie, acid and eicosenoic acid, and the lowest mean value for erucic acid. The highest mean value for linoleic acid and linolenic acid and the lowest mean value for oleic acid and eicosenoic acid were observed in cluster IV. Those genotypes may be used in hybridization programmes for the improvement of quality traits of rapeseed and mustard. The cluster I had the highest intra-cluster D2 value (0.65). So, the genotypes belong to this cluster would be more stable in different environments. Being the highest inter-cluster D2 value (10.24) between the clusters I and III, the genotypes of I would produce desirable recombinants crossing with those of the cluster III. The principal component analysis revealed that oleic acid and erucic acid contributed maximum to the total divergence in the present materials.

Bangladesh J. Agril. Res. 32(4) : 553-558