The richness of diversity in a core collection of bread wheat (Triticum aestivum L.)

  • Vivek Sharma, Sumita Kumari, Ashwani kumar, Sheetalraj Sharma, and Chhagan lal Sher-e-Kashmir University of Agricultural Sciences &Technology of Jammu,Chatha, Jammu -180009, J&K (INDIA)
Keywords: Principal Component Analysis (PCA), Cluster Analysis, Wheat


Diversity evaluation provides opportunity to assess genetically important distinct traits that will effectively contribute to improvement of genotypes. Assessing genetic diversity  in a core collection is key to find out the ways to efficient utilization of genetic resource. Wheat cultivars spinning over a century were collected from the Indian Institute of Wheat & Barely Research (IIWBR), Karnal, made up of a core collection. The core set of data was analysed by multivariate methods. The experimental material consisted of ~100 genotypes which were evaluated in an Augmented Randomized Block Design. Quantitative characters like no. of grain per spike, no. of spikelet per spike, test weight and spike length were found to be the key yield contributing traits. Principal component analysis (PCA) and cluster analysis of eight quantitative characters and genotypes fall into three principal component and three cluster respectively. Based on these experiment first and third cluster genotypes have high associated with PCI and PCIII. These principal components were made by grouping them high yield contributing traits. Genotypes in these clusters have higher values for yield contributing traits then the total average of traits.   Genotypes belonging to superior clusters could be considered to very useful to developing high yielding varieties and other breeding activities.

Research Article