Genetic Variability, Heritability and Genetic Advance of Dry Matter Yield and Yield Contributing Characters in Rhodes Grass (Chloris gayana) Genotypes

Abstract

Information on the communal association of traits is important for effective selection in forage-breeding program. Twenty four genotypes of Rhodes grass and one check were evaluated at Mechara Agricultural Research site (Onstation) with lattice design in 2023/24 main rainy season to evaluate Genetic variability, heritability and genetic advance of dry matter yield and yield contributing characters in Rhodes grass genotypes. The mean sum of squares of genotypes showed significant differences (p < 0.05) for  stand vigor, days to 50% emergence, date  to 50% flowering and Plant height and highly significant (p < 0.001) for biomass yield, dry matter and number of leaf per plant. Maximum phenotypic variance and genotypic variance value was recorded for days to maturity. The range observed for heritability (H²bs) was from (0.0%) to (55%). Stand vigor exhibited highest value of genetic advance as percentage of mean followed by number of leaf per plant. Highest genotypic coefficient variation were recorded from days to maturity (89.8%) flowed by Plant height (62.3%) and Highest phenotypic coefficient variation were recorded from plot cover (184.9%) followed by days to maturity (225.4%). Phenotypically and genotypically dry matter yield was highly positive significant associated with of Plot cover (0.546**), stand vigor (0.566**), leaf per plant (0.439**) and showed highly negative significant with days to 50% emergence.  The results of phenotypic path coefficient analysis showed that stand vigor (0.378) and leaf per plant had exerted moderate positive direct effect on dry matter. stand vigor followed by plant height, plot cover and leaf per plant had exerted high and positive direct effect on dry matter yield and genotypic path analysis showed stand vigor followed by plant height, plot cover and leaf per plant had exerted high and positive direct effect on dry matter yield. This indicates that selection based on these traits could be more effective to maximize dry yield.