Principal Component Analysis for Yield and Quality Traits of Blackgram (Vigna mungo (L.) Hepper)

Abstract

The study consists of fifty-nine blackgram genotypes, which were evaluated for fourteen quantitative and qualitative traits. In order to determine the relationship and diversity among the blackgram genotypes taken for study. A field experiment was conducted at the Regional Agricultural Research Station, Lam, Guntur district, Andhra Pradesh state during Kharif, 2019. Principal component analysis for various yield-contributing traits was done to evaluate diversity and some quantitative and qualitative traits that had more effects on diversity. PCA results revealed that four of the five principal components had eigen values greater than one. The first five components obtained from principal component analysis (PC 1 to 5) accounted for about 76.73% of the total variation for fourteen quantitative and qualitative traits. Out of total principal components, PC 1, PC 2, PC 3, PC 4 and PC 5 were retained with values of 35.42%, 14.85%, 11.14%, 8.75% and 6.56%, respectively. The results of 2D and 3D scatter diagrams revealed LBG 904, LBG 752 and TU 94-2 genotypes to be the most diverse. Utilizing these diverse genotypes as parents in hybridization suggests obtaining desirable transgressive segregants towards the development of high yields with nutritional quality. The clustering of blackgram genotypes based on the yield and quality-attributing traits would be helpful in identifying the appropriate genotypes for effective utilisation in upcoming breeding programmes. The outcomes of principal component analysis revealed that wide genetic variability occurs between these blackgram genotypes and proposed their potential value in blackgram yield and quality improvement.