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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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Original Research Articles                      Volume : 10, Issue:1, January, 2021

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com /
submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2021.10(1): 2704-2710
DOI: https://doi.org/10.20546/ijcmas.2021.1001.314


Estimation of Genetic Parameters for Yield Associated Traits and Principal Component in Advance Breeding Lines of Soybean (Glycine max. (L.) Merrill)
Vikas Verma*, M. K. Shrivastava, Shrishti Mehra, Pawan K. Amrate and R. B. Yadav
Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidhyalaya, Jabalpur, Madhya Pradesh, India
*Corresponding author
Abstract:

Soybean [Glycine max (L.) Merrill] is highly nutritious with neutraceutical valued legume crop grows across the world. Information on different genetic estimates is used to select desirable traits and genotypes for crossing programme. The present investigation was undertaken to estimate different genetic parameters i.e. genetic variability, heritability, character association and principal component on thirty four advanced breeding lines of soybean along with two checks sown in Randomized block Design during Kharif, 2018 at JNKVV, Jabalpur. The highest PCV and GCV (41.16 and 40.43 %) were recorded for number of seeds per pod. Genetic advance as percentage of mean was high (>75%) for number of seeds per plant and number of seeds per pod. The number of pods per plant was highly significantly correlated with number of seeds per plant (0.79**). Path coefficient analysis was also revealed that substantial higher positive direct effect of number of seeds per plant and number of seeds per pod on seed yield. Out of five principle components, PC1 had the highest variance percentage with Eigen value of 2.17. Number of seeds per plant contributed highest (64 %) in PC1. Hence, all these traits could be utilized in soybean crossing programme for further yield improvement.


Keywords: Correlation, Path analysis, Heritability, Principal component analysis

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How to cite this article:

Vikas Verma, M. K. Shrivastava, Shrishti Mehra, Pawan K. Amrate and Yadav, R. B. 2021. Estimation of Genetic Parameters for Yield Associated Traits and Principal Component in Advance Breeding Lines of Soybean (Glycine max. (L.) Merrill).Int.J.Curr.Microbiol.App.Sci. 10(1): 2704-2710. doi: https://doi.org/10.20546/ijcmas.2021.1001.314
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

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