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Vol. 11, Issue 2 (2022)

Genetic diversity analysis in bread wheat (Triticum aestivum L.) for grain yield and its attributing traits

Author(s):
Ravishankar, Kiran Tigga, S. K. Sinha, D. K. Thakur and Priyanka
Abstract:
The present investigation was carried out during Rabi 2020-21 in a randomized block design (RBD) with 23 wheat genotypes to assess the genetic diversity for various morphological and quality traits. The experiment is performed at Indira Gandhi Krishi Vishwavidyalaya, Raj Mohini Devi College of Agriculture & Research Station, Research cum Instructional Farm, Ambikapur (Chhattisgarh). The statistical analysis for genetic divergence was done using Mahalanobis-D2 statistics and clustering of genotypes was done using Tocher method, 23 genotypes grouped into five clusters. Clustering of genotypes revealed that cluster-II has maximum number of genotypes (13) and clusters IV and V each has two genotypes only. The highest intra-cluster distance was exhibited by cluster-IV (60.64) revealing maximum genetic divergence among its constituents. The highest inter-cluster distance was found between clusters I and V (656.39) and the lowest was between cluster-II and III (410.95). Cluster-I exhibited highest cluster means for most of the agronomic traits like days to 50 percent flowering, days to maturity, flag leaf length, number of productive tillers per square meter, number of spikelets per spike, biological yield per plot and grain yield per plot while clusters-IV revealed highest cluster means for plant height, spike length, spike weight, number of grains per spike and test weight. The genotypes bearing the desired values from different clusters can be exploited in future breeding programme for the improving the wheat genotypes for yield and physiological traits.
Pages: 1386-1388  |  226 Views  43 Downloads


The Pharma Innovation Journal
How to cite this article:
Ravishankar, Kiran Tigga, S. K. Sinha, D. K. Thakur, Priyanka. Genetic diversity analysis in bread wheat (Triticum aestivum L.) for grain yield and its attributing traits. Pharma Innovation 2022;11(2):1386-1388.

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