Association Analysis Studies in Mung bean (Vigna radiata (L.) Wilczek) Genotypes for Yield and its Contributing Traits

Author: R. Aravinth, John Kingsly N.B., Wilson D., Adlin Pricilla Vasanthi and Dinesh Kumar P.

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Abstract

Green gram (Vigna radiata L. Wilczek) is a vital pulse crop in India, providing a significant source of protein for the predominantly vegetarian population. However, the productivity of green gram is currently low, and there is a need to develop high-yielding varieties that are resistant to diseases and pests while maintaining nutritional value. In this study, a total of 94 green gram genotypes were evaluated to assess the relationships between yield and various contributing traits. Correlation and path coefficient analyses were performed to determine the associations between traits and yield. The results revealed significant positive correlations between yield and its contributing traits such as plant height, number of primary branches per plant, number of clusters per plant, number of pods per plant, number of seeds per pod, hundred seed weight, and harvest index. These findings were consistent with previous studies, further supporting the importance of these traits in determining yield potential of green gram. Path coefficient analysis identified harvest index as the trait with the highest positive direct effect on yield, followed by days to fifty per cent flowering. However, indirect effects were observed between early flowering and traits such as the number of pods per plant and protein content. Similarly, the number of primary branches per plant and number of clusters per plant exhibited negative direct effects on yield, indicating potential limitations in maximizing yield. Overall, this study provides valuable insights into the relationships between yield and its contributing traits in green gram. The findings can guide plant breeding programs in selecting and prioritizing traits to develop improved varieties with enhanced yield potential. Additionally, these identified trait associations contribute to a deeper understanding of the genetic and physiological mechanisms governing yield determination, facilitating more targeted and efficient crop improvement efforts. Association analysis studies in mung bean genotypes face various challenges when assessing yield and its contributing traits. One of the primary obstacles is the extensive phenotypic variation observed in mung bean, which makes it difficult to accurately measure and characterize these traits across different genotypes. Factors such as growth habit, flowering time, pod setting, and seed size contribute to this complexity, further complicating the phenotypic evaluation. Another challenge lies in the genetic complexity of mung bean genomes, which are influenced by both additive and non-additive genetic effects. Yield and its contributing traits are controlled by multiple genes, and their expression can be influenced by environmental interactions. Understanding the intricate genetic architecture and deciphering the effects of individual genes amidst complex genetic interactions pose significant challenges for researchers. To ensure reliable results, association analysis requires a substantial sample size of genotypes that adequately represents the genetic diversity within mung bean. Obtaining a diverse and representative set of genotypes is crucial for accurate analysis.

Keywords

Association studies, green gram, correlation, path coefficient, crop improvement

Conclusion

In conclusion, the correlation analysis, considering both genotypic and phenotypic coefficients, has provided valuable insights into the relationships between yield and its contributing traits. The findings highlight the significance of traits such as plant height, number of primary branches per plant, number of clusters per plant, number of pods per plant, number of seeds per pod, hundred seed weight, and harvest index in determining yield potential. These results are consistent with previous studies, confirming the importance of these traits in maximizing yield. Additionally, the correlation analysis revealed interesting associations among the traits themselves, shedding light on their combined contribution to yield enhancement. The path coefficient analysis further elucidated the direct effects of each trait on yield per plant. Harvest index emerged as the trait with the highest positive direct effect on yield, indicating its crucial role in overall yield performance. Days to fifty per cent flowering also showed a positive direct effect on yield, suggesting that early-flowering varieties have the potential to achieve higher yields. However, trade-offs and indirect effects among traits were observed, emphasizing the need for a holistic approach in trait selection. The comprehensive understanding provided by these analyses has practical implications for plant breeding programs. Breeders can prioritize and select traits based on their positive correlations and direct effects on yield, such as harvest index and early flowering. By targeting these key traits, improved varieties with enhanced yield potential can be developed. Furthermore, the identified trait associations can guide future research on the underlying genetic mechanisms governing these relationships, facilitating more targeted and efficient crop improvement efforts. Overall, the correlation and path coefficient analyses offer valuable insights into the complex relationships between yield and its contributing traits. These findings contribute to our understanding of crop yield determination and can inform breeders and researchers in their efforts to develop high-yielding and resilient crop varieties to meet the increasing demands for food security and sustainability.

References

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How to cite this article

R. Aravinth, John Kingsly N.B., Wilson D., Adlin Pricilla Vasanthi and Dinesh Kumar P. (2023). Association Analysis Studies in Mung bean (Vigna radiata (L.) Wilczek) Genotypes for Yield and its Contributing Traits. Biological Forum – An International Journal, 15(5): 937-942.