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Vol. 11, Issue 3 (2022)

Principal component analysis in mungbean [Vigna radiata L. Wilczek] genotypes under two seasons

Author(s):
Shruti Paliwal, Stuti Sharma and Nidhi Pathak
Abstract:
To find out the promising genotypes of mungbean which have maximum yield and can be grown in both seasons i.e. kharif and zaid we conducted this present investigation of sowing 60 mungbean genotypes in both growing seasons and pooled the result to obtain maximum high yielding genotypes through Principal Component Analysis (PCA). In kharif analysis only five principal components (PCs) exhibited more than 1.00 Eigen value, and showed about 77.64% variability among the traits studied. During zaid analysis six principal components (PCs) exhibited more than 1.00 Eigen value, and showed about 81.56% variability among the traits studied. In Pooled analysis only five principal components (PCs) exhibited more than 1.00 Eigen value, and showed about 70.70% of variability among the traits studied. Rotated component matrix revealed that the PC1 which accounted for the highest variability (19.146%) was mostly related with traits such as hundred seed weight, Harvest Index, seed yield per plant (g).
Pages: 1500-1505  |  361 Views  134 Downloads


The Pharma Innovation Journal
How to cite this article:
Shruti Paliwal, Stuti Sharma, Nidhi Pathak. Principal component analysis in mungbean [Vigna radiata L. Wilczek] genotypes under two seasons. Pharma Innovation 2022;11(3):1500-1505.

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