Correlation and Path Analysis for Seed Yield and Quality Traits in Blackgram [Vigna mungo (L.) Hepper]

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Authors: Y. Pushpa Reni, G. Bindhumadhavi, Ramana MV.
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Abstract

Blackgram [Vigna mungo (L.)] is a vital pulse crop in India, offering dietary protein and soil fertility benefits. Improving seed yield and nutritional quality (protein, iron, zinc) is crucial, but requires understanding trait associations and cause-and-effect relationships via correlation and path coefficient analysis. The present investigation was undertaken to study the nature and magnitude of association among yield, yield components and nutritional quality traits in blackgram and to partition these associations into direct and indirect effects through path coefficient analysis. The study was conducted at the Regional Agricultural Research Station, Lam, Guntur, Andhra Pradesh, India, using 59 blackgram genotypes in an Augmented Completely Randomised Block Design-II during summer 2018 and kharif 2019. Phenotypic and genotypic correlation coefficients among fourteen characters were estimated, followed by path analysis with seed yield per plant as the dependent variable. The results revealed that the number of pods per plant, the number of clusters per plant and harvest index exhibited a strong positive association with seed yield per plant at both phenotypic and genotypic levels. Path analysis further indicated that harvest index and number of pods per plant exerted the highest positive direct effects on seed yield, suggesting that these traits should receive prime emphasis in selection programmes aimed at yield improvement in blackgram. The study concludes that harvest index and number of pods per plant are key traits for improving seed yield in blackgram, and should be prioritized in selection programmes.

Fields of Study & Subjects

Genetic and Environmental Crop Studies Genetics and Plant Breeding Agricultural Practices and Plant Genetics

Publication details

Journal / source
Journal of Advances in Biology & Biotechnology
Volume
29
Issue
2
Pages
1131–1140
Publication date
27 February 2026
Language
EN