Genetic Components and Diversity Analysis in Indian Mustard [Brassica juncea (Linn.) Czern & Coss] Based on Different Morpho-physiological Traits
Chitralekha Shyam, M. K. Tripathi, Sushma Tiwari, Niraj Tripathi
Current Journal of Applied Science and Technology · pp. 34–57 · Published 30 Aug 2021
10.9734/cjast/2021/v40i2031462Abstract
Aim: Indian mustard [Brassica juncea (Linn.)] is the third vital oilseed crop in the world which contributes 28.6% in the production of oilseeds. Genetic diversity assessment plays a fundamental role in the preservation and improvement of the targeted plant species. Study Design: In the present investigation, 196 Indian mustard genotypes including checks were grown in the field and evaluated based on different morpho-physiological traits. Place and Duration of the Study: All the genotypes were grown in randomized block design with two replications in Rabi 2016-17 and 2017-18 at the experimental field of Department of Genetics & Plant Breeding, College of Agriculture, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior, M.P., India. Methodology: The study was conducted to record different morphological and physiological traits that play a major role in differentiating the targeted genotypes. Results: Based on the present study, the highest genotypic and phenotypic coefficients of disparity were documented for seed yield per plant tracked by harvest index and numbers of silique per plant. Maximum heritability and genetic advance were documented for seed yield per plot tracked by harvest index, biological yield per plot, days to 50% flowering, length of the main raceme, numbers of silique per plant, seed yield per plant, numbers of seeds per silique, 1000-seed weight and numbers of silique per the main raceme. Conclusions: In principal component analysis, 15 principal components were evidenced while cluster analysis gave 16 clusters. The highest inter-cluster distance was evidenced between cluster 9 and cluster 16 which suggests that the hybridization scheme considering parents from these clusters is supposed to be given a higher occurrence of better-wanted combination(s) for expansion of beneficial genetic stocks.
Cited by 1
Rakesh Kumar Yadav, Manoj Kumar Tripathi, Sushma Tiwari · Current Journal of Applied Science and Technology · 2023
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