Genotypic and Phenotypic Correlation and path Coefficient Analysis in field Pea (Pisum Sativum L.) Genotypes at Asasa, Ethiopia

International Journal of Development Research

Volume: 
14
Article ID: 
28554
6 pages
Research Article

Genotypic and Phenotypic Correlation and path Coefficient Analysis in field Pea (Pisum Sativum L.) Genotypes at Asasa, Ethiopia

Temesgen Abo and Wassu Mohamed

Abstract: 

In Ethiopia, field pea (Pisum sativum L.) is the main source of protein for resource poor growers. The improvement of varieties for yield and disease resistance is one of the important activities to support farmers and improve the productivity of the crop. Consequently, this study was showed to evaluate the genotypic correlations, phenotypic correlations and path coefficient analysis between the field pea genotypes for yield and yield associated traits. Forty-nine field pea genotypes were evaluated in simple lattice design at Asasa in 2019 cropping season. Data collected for morpho-agronomic traits were subjected for analysis of variance. The analysis of genotypic correlations, phenotypic correlations and path coefficient showed significant differences among genotypes for most of the traits. Grain yield per plot had positive and highly significant genotypic association with plant height, while highly significant phenotypic correlation observed between grain yield and harvest index and biomass yield. Days to flowering had positive and highly significant genotypic association with days to 90% physiological maturity, plant height and biological yield, while negative and highly significant genotypic association with harvest index. Days to 90% physiological maturity had positive and highly significant genotypic association with plant height and total biomass, while negative and highly significant genotypic association with harvest index. Path coefficient analysis at genotypic levels showed that harvest index and total biomass per plot had strong positive direct effect on grain yield per plot. Residual effect in genotypic path analyses at Asasa was 0.1996 (Table 4), showing that 80.04% of the variability in seed yield was explained by the component factors at genotypic levels. The remaining 19.96 % variation could be explained by other explanatory variable not control in this research; while at phenotypic level residual effect was 0.1017 at Asasa indicating that 89.83% of variability was explained by component factors (Table 5). The study showed the existence of reasonable genetic variability among the field pea genotypes that could be exploited in breeding programs.

DOI: 
https://doi.org/10.37118/ijdr.28554.08.2024
Download PDF: