Dissecting Key Yield Components in Soybean (Glycine max L.) Genotypes Through Multivariate Analysis
DOI:
https://doi.org/10.66432/29mqph86Keywords:
Soybean, genetic variation, Correlation Analysis, Path coefficient AnalysisAbstract
Soybean (Glycine max L. Merrill) is a highly valued leguminous oilseed crops and can contribute to meet the Pakistan’s edible oil demand and reduce import bill, However, limited availability of high yielding and environmental adapted soybean genotypes is a major hinderance for its adoption by local farmers. The current study was executed to determine variability and adaptability patterns of seventy exotic soybean accessions under agro-climatic conditions of Okara, Pakistan. An augmented block design with two commercial checks (NARC-21 and Faisal Soybean) was used to study ten yield related characteristics. Result exhibited a substantial amount of diversity in the studied germplasm. Genotypic correlation and path coefficient analysis revealed that seed per pod, pods per plant, pod length, pod width and hundred-seed weight were significant contributors to seed yield. Heritability and genetic advance estimates depicted the predominance of additive gene action in pods per plant, plant height and the hundred-weight of the seed. The genotypes Toano, Glenwood, Delsoy 4500, Lawrence and DSR-262 were identified as promising parental lines for use in future crop improvement programs.
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