Chauhan, Deepak Singh and Verma, Sanjay Kumar and Panwar, Ravindra Kumar and Arora, Anju and Pragati, Kumari and Bhatt, Ashish and Kumawat, Shubham and Rana, Anupriya and Mehra, Ayushi (2024) Multivariate Analysis of Genetic Diversity in Mung Bean [Vigna radiata (L.) Wilczek] Using Mahalanobis Statistic. International Journal of Plant & Soil Science, 36 (8). pp. 1138-1145. ISSN 2320-7035
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Abstract
Mung bean is a significant pulse crop in India, known for its high protein content, ranging from 25-28%. Understanding the genetic diversity within mung bean populations is essential for identifying genotypes that can enhance crop improvement and for the effective utilization of available genetic resources. This study aimed to evaluate the extent and patterns of morphological diversity among various mung bean genotypes and to determine the key traits contributing to genetic diversity using multivariate analysis. The present study was conducted at Norman E. Borlaug Crop Research Centre, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India, during the kharif season of 2023. Using Mahalanobis D2 statistics, 40 mung bean genotypes were grouped into 9 distinct clusters. Cluster I was the largest, comprising 15 genotypes, followed by Cluster II with 11 genotypes. Clusters IV with 4 genotypes. Cluster V and Cluster VII each had 3 genotypes; and Clusters III, VI, VIII and IX each contained a single genotype. The greatest inter-cluster distance was observed between Cluster VII and Cluster VIII (17.12), indicating that genotypes (PM 15-12, PM 5, IPM 2-14) and (Vamban 2) can be hybridized together to produce significant genetic diversity in segregating generation among the genotypes included in these clusters. Therefore, the substantial genetic distance observed within and among the clusters should be leveraged by selecting and crossing the most genetically divergent parents in future mung bean breeding programmes.
Item Type: | Article |
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Subjects: | Pustakas > Agricultural and Food Science |
Depositing User: | Unnamed user with email support@pustakas.com |
Date Deposited: | 30 Aug 2024 07:02 |
Last Modified: | 30 Aug 2024 07:02 |
URI: | http://archive.pcbmb.org/id/eprint/2096 |