Estimation of genetic divergence in wheat genotypes based on agro-morphological traits through agglomerative hierarchical clustering and principal component analysis

Estimation of genetic divergence and its application in breeding strategy may result in improved and viable production. A total of 6 agro-morphological traits were analysed in 77 wheat genotypes from different geographical regions of Pakistan starting from 1934 to 2016. Data were analysed for correlation, agglomerative hierarchical clustering and principal component analysis. Grain yield (kg per hectare) had significantly positive correlation with grains per spike. The PC-I revealed positive factor loadings for entire traits. The contribution of spike length was maximum in PC-I. Cluster analysis clustered entire varieties into five different groups. The D-2 statistics proved maximum distance between cluster-II and IV, whereas the highest resemblance was found in cluster-III and cluster-V. It is therefore suggested that crosses between genotypes of cluster-II and V can be used to classify germplasm which provides viable basis for choosing base material to design imminent breeding approaches for yield improvement.