A review on genetic parameters estimation, trait association, and multivariate analysis for crop improvement
Punam Roka, Suraj Shrestha, Shiva Prasad Adhikari, Ayushma Neupane, Briksha Shreepaili, Mohan K. Bista
Abstract
This review paper aims to elucidate the critical genetic parameters essential for practical crop breeding, focusing on the nature and extent of variability, its inheritance, and the complexity of traits. By evaluating genetic parameters such as Genetic Coefficient of Variation (G.C.V.), Heritability, Genetic Advance as a percentage of the Mean (G.A.M.), correlation coefficients, path coefficient analysis, cluster analysis, and principal component analysis, the review provides a comprehensive framework for optimizing breeding strategies. Emphasizing higher G.C.V. values minimizes environmental effects while highlighting Heritability and G.A.M. aids in predicting trait transmission and potential genetic improvement. The review also underscores the importance of traits with high G.C.V., Heritability, and G.A.M. for effective selection and improvement. Additionally, cluster and principal component analyses are powerful tools for identifying genetically diverse parents and reducing trait dimensionality. The findings suggest that thoroughly understanding and applying these genetic parameters can significantly enhance decision-making in plant breeding programs, ultimately leading to more efficient and targeted genetic improvements.