Exploring Genetic Variability, Trait Associations and Path Coefficient Analysis in Pea (Pisum sativum L.) to Advance Breeding Strategies
DOI:
https://doi.org/10.23910/1.2024.5522Keywords:
Correlation coefficients, heritability, path analysis, pea, quantitative traitsAbstract
The experiment was conducted at seed breeding farm, Department of Plant Breeding and Genetics, College of Agriculture, JNKVV, Jabalpur, Madhya Pradesh, India during the rabi season (November, 2019–April, 2020) to estimate the parameters of genetic variability, assess the correlation among traits, and estimate direct and indirect effects. The ANOVA revealed that the mean sum of squares due to genotypes was highly significant for all the traits. The phenotypic coefficient of variation was higher than the genotypic coefficient of variation for all the characters. High values of phenotypic coefficient of variation and genotypic coefficient of variation were observed for most of the traits, while moderate values of phenotypic coefficient of variation and genotypic coefficient of variation were recorded for 100 seed weight, pod length, days to 50% flowering and days to first flower opening. High heritability with high genetic advance as a % of mean was recorded for most of the traits. Moderate heritability and high genetic advance were recorded for the number of primary branches plant-1, secondary branches plant-1 and pod length, indicating the control of additive gene action. Meanwhile, high heritability with moderate genetic advance for days to maturity showed non-additive gene action. Correlation coefficients and path analysis for phenological and quantitative traits indicated that the most important traits are number of seeds plant-1, number of effective pods plant-1, biological yield plant-1 and harvest index. Hence, directional selection through these traits may effectively improve seed yield and its attributes.