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Vol. 11, Issue 4 (2022)

Study on genetic variability and principal component analysis in Indian mustard [Brassica juncea (L.) Czern and Coss]

Author(s):
Devesh Yadav, Lokendra Singh, Syed Kulsoom Fatima Jafri, Aman Singh and Vineet Singh
Abstract:
An experiment involving 18 genotypes of Indian Mustard (Brassica juncea L.) was conducted in randomised block design with three replications, during Rabi 2020. Data were recorded and analysed for fourteen characters. The analysis of variance revealed significant differences among all the characters. In general, Phenotypic coefficients of variation were more than the corresponding genotypic coefficients of variation for all the characters. The dimensionality of the data was reduced with the help of Principal Component analysis and it led to the identification of 4 principal components (PCs) which explained about 86% variability. The first principal component (PC1) explained 36.19% of the total variation. The remaining PC’s explained progressively lesser and lesser of the total variation. The maximum eigen root value was observed in PC1 (5.06) which contributed 36.19% towards total variation. The other components with their eigen root values were PC2 (4.69), PC3 (1.37) and PC4 (0.97); contributing about 33.56, 9.79 and 6.90% towards total variation.
Pages: 2166-2169  |  446 Views  232 Downloads


The Pharma Innovation Journal
How to cite this article:
Devesh Yadav, Lokendra Singh, Syed Kulsoom Fatima Jafri, Aman Singh, Vineet Singh. Study on genetic variability and principal component analysis in Indian mustard [Brassica juncea (L.) Czern and Coss]. Pharma Innovation 2022;11(4):2166-2169.

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