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Research Article Open access CC BY 4.0

Evaluation of Diversity among Soybean Genotypes via Yield Attributing Traits and SSR Molecular Markers

Nishi Mishra, Manoj Kumar Tripathi, Sushma Tiwari, Niraj Tripathi, Neha Gupta, Akash Sharma, Ravindra Singh Solanki

Current Journal of Applied Science and Technology · pp. 9–24 · Published 3 Sep 2021

10.9734/cjast/2021/v40i2131467

Abstract

Introduction: As an important source of nutrients to humans and animals, soybean is considered to be a major crop. Objective: The present study has been executed to identify diverse soybean genotypes on account of different morpho-physiological and microsatellite molecular markers. Study Design: Data for Morpho-physiological traits were recorded from experiment conducted under field conditions in RBD design whereas molecular work was conducted in Laboratory. Place and Duration of the Study: The present study was conducted at College of Agriculture, Gwalior, Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior, M.P., India during Kharif 2018-19. Methodology: The study was conducted to document different morphological and physiological traits related to the yield and its attributing traits in soybean. Total 32 microsatellite markers were also used in laboratory to analyze the variability among soybean genotypes. Results: Morpho-physiological analysis among 53 genotypes revealed the presence of considerable level of variability. Phylogenetic tree based on morpho-physiological traits grouped the genotypes into major and minor cluster. Major cluster had fifty genotypes while minor cluster had only three genotypes. Among polymorphic 32 microsatellite markers, the highest genetic diversity (0.66) was recorded in Satt520 whilst lowest (0.037) was in Satt557 with an average of 0.35. The highest PIC value was 0.59 prearranged by Satt520 and lowest 0.036 by Satt557. An average major allele frequency was 0.69 while, an average PIC value was 0.32. Microsatellite markers-based data also grouped the genotypes into one major and one minor cluster. Conclusion: Molecular analysis based on microsatellite markers confirms the presence of genetic variability among genotypes under the investigation. Data obtained in the present investigation may contribute towards improvement of soybean genotypes to develop high yielding varieties by considering diverse genotypes with good agronomical traits in hybridization programme.

Breeding microsatellites sustainable agriculture soybean variability

Cited by 4

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