1Mountain Research Center for Field Crops, Khudwani , Sher-E-Kashmir University of Agricultural Sciences and Technology of Kashmir, Jammu and Kashmir (India)
2Indian Agricultural Research Institute, New Delhi-110012, (India)
3GD Goyenka University, Sohna, Haryana-122103, (India)
4High Mountain Arid Agricultural Research Institute (HMAARI), SKUAST-K Stakna, Leh-19420, Ladakh, (India)
5ICAR-Indian Institute of Soybean Research, Indore, M.P, (India)
6DARS, SKUAST-Kashmir, Rangreth, Srinagar, Jammu and Kashmir
*e-mail: shabirhussainwani@gmail.com
Online published on 24 May, 2021.
The underlying basis to develop elite niche and broadly adapting wheat genotype is primarily targeted by assessing extent of genetic variability through pre-evaluation of available germplasm resources and subsequent unique identification of the potential genotypes. Following the methodology the present investigation was undertaken to estimate the extent of genetic variability within a set of ninety five (95) wheat genotypes including three (03) checks. It was observed that the grain yield per plant had a strong and positive genotypic correlation with the number of tillers per metre (r2=0.89) followed by grains per spike(r2=0.79) and spike length (r2=0.43) with maximum direct effects. The cluster analysis grouped these wheat genotypes into four major clusters on the basis of significant level of genetic divergence present among genotypes and their clusters. Highest number of genotypes were grouped in cluster 4 followed by cluster 3, cluster 1 and cluster 2, respectively. The first three principal components explained 67.2% of the total phenotypic variation. Genotypes revealed significant level of genetic variability with respect to grain yield followed by tillers per metre, grains per spike, plant height and peduncle length. Wheat genotypes such as, PHSL-5, NW5054, WBZ, MP3336, AKAW4899 and GW 2013-491 were identified candidate wheat genotypes under temperate conditions. These elite genotypes can be utilized to develop new breeding population for scaled development of wheat germplasm resources and novel genotypes.
Cluster analysis, Correlation, Divergence, Principal component analysis (PCA), Spring wheat, Variability