Research on World Agricultural Economy

Screening of Elite Mungbean Genotypes (Vigna radiata (L.) Wilczek) through Multivariate Analysis for Food and Nutritional Security

Sanhita Ghosh

Department of Genetics and Plant Breeding, University of Calcutta, Kolkata, West Bengal, 70019, India

Anindita Roy

Department of Genetics and Plant Breeding, University of Calcutta, Kolkata, West Bengal, 70019, India

Sabyasachi Kundagrami

Department of Genetics and Plant Breeding, University of Calcutta, Kolkata, West Bengal, 70019, India

DOI: https://doi.org/10.36956/rwae.v4i2.814

Received: 18 February 2023; Received in revised form: 18 April 2023; Accepted: 27 April 2023; Published: 10 May 2023

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Abstract

The ever-increasing urbanization to accommodate the growing population reduces substantially the agricultural land but poses a threat to meeting the requirement of proper nutrition for human health. Mungbean [Vigna radiata (L.) Wilczek] is a unique gift bestowed by nature to mankind, which has the potency to make up the gap of protein shortage with an inexpensive cost, but due to its low level of production as well as productivity, which in a roundabout way influences the nutritional status of people resulting in malnutrition. Therefore, enhancement of the total area under mungbean cultivation is not permissible, and an increase in the total productivity per unit area is necessary. In this manner, screening and evaluation of improved genotypes for high yield are necessary to ensure food security. But at the same time seed yield being a complex character governed by several other contributing traits, selection for the characters proves to be quite challenging. As a prerequisite for any breeding program aimed at yield enhancement presence of significant genetic diversity in a given population is highly important. In the present investigation principal component analysis was performed and the results revealed two principal components contributing to the total variance in the population. While the PC1 was predominated by yield and its attributing traits, the PC2 was mainly comprised of growth-related traits. The hierarchical (UPGMA) cluster analysis using standardized data classified the fifty-two mungbean genotypes into 4 clusters, which showed 2 major, 1 minor and one outlier. Among them, cluster II is the most fascinating, as its individual had high seed yield plant^–1 and related traits. The present work concluded that the identification of promising high-yielding mungbean genotypes through multivariate analysis has a good promise for future breeding programs with a view of food and nutritional security.

Keywords: Mungbean; Screening; Multivariate analysis

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