Open AccessEvaluation the Genetic Variability and Association Analysis of Soybean (Glycine max (l.) Merrill for Some Physiological Parameters
Author(s) -
Monika Soni,
M. K. Shrivastava,
Yogendra Singh,
Stuti Sharma,
Pawan K. Amrate,
Jhilick Banerjee
Publication year - 2022
Publication title -
international journal of plant and soil science
Language(s) - English
Resource type - Journals
ISSN - 2320-7035
DOI - 10.9734/ijpss/2022/v34i1030919
Subject(s) - heritability , path coefficient , biology , randomized block design , coefficient of variation , trait , quantitative trait locus , genetic correlation , leaf area index , genetic variation , correlation coefficient , genetic gain , breeding program , horticulture , path analysis (statistics) , genetic variability , veterinary medicine , genotype , agronomy , statistics , mathematics , cultivar , genetics , medicine , gene , computer science , programming language
The present study was carried out to estimate the important genetic parameters, heritability, genetic advance correlation, and path coefficient analysis in fifty advanced breeding lines of soybean. Randomized Block design (RBD) with three replications was used to design this experiment at the Department of Plant Breeding and Genetics, JNKVV, Jabalpur in 2020. Genotypes were evaluated for eight traits based on important physiological growth parameters such as leaf area index 1 (30 DAS), leaf area index 2 (45 DAS) leaf area index 3 (60 DAS), leaf area duration 1, (30-45 DAS), leaf area duration 2 (45-60 DAS), seed filling duration, harvest index, seed yield per plant. All statistical analysis was done in CRAN R package. ANOVA revealed a sufficient amount of variability was found among soybean genotypes for all traits assessed, which gives an opportunity to plant breeders for the enhancement of these traits. The value of the phenotypic coefficient of variation (PCV) is greater than the genotypic coefficient of variation (GCV). The high GCV and PCV were observed for leaf Area Index 1, leaf Area Index 3, leaf Area Duration 2, seed filling duration, harvest index and seed yield. High heritability (0.8) coupled with high genetic advance as percentage mean (66.4) were recorded for leaf area index 1 (30 DAS). It indicates that the trait is governed by additive gene action and directional selection for this trait would be more effective for desired genetic improvement. Correlation coefficient study indicated that Leaf area index 1, leaf area duration1 and harvest index showed a significant positive correlation with seed yield. Greater LAI of soybean genotypes would be enabled greater radiation absorption during the seed filling period. Harvest index showed a significant positive direct effect along with a positive correlation with seed yield, which can be considered as suitable selection criteria for the development of high-yielding soybean genotypes.