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International Journal of Applied Agricultural & Horticultural Sciences
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Language : English
DOI Prefix : 10.37322
P-ISSN : 0974-0775
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Vol. 7 (3) : May-June 2016 issue
Green Farming Vol. 7 (3) : 598-601 ; May-June, 2016
Genetic diversity analysis in blackgram [Vigna mungo (L.) Hepper] based on quantitative traits
ASIF HADIMANI1*, C.R. KONDA2, J.M. NIDAGUNDI3 and RAJENDRAGOUDA PATIL4
Department of Genetics and Plant Breeding, University of Agricultural Sciences, Raichur - 584 104 (Karnataka)
Designation :  
1Res. Associate *(adh4992@gmail.com), 2Breeder (Pulses), 3Breeder (Cotton), 4Ph.D. Scholar
Subject : Crop Genetics and Plant Breeding
Paper No. : P-4222
Total Pages : 4
Received : 16 September 2015
Revised accepted : 14 April 2016
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Citation :

ASIF HADIMANI, C.R. KONDA, J.M. NIDAGUNDI and RAJENDRAGOUDA PATIL. 2016. Genetic diversity analysis in blackgram [Vigna mungo (L.) Hepper] based on quantitative traits. Green Farming Vol. 7 (3) : 598-601 ; May-June, 2016

ABSTRACT
Genetic divergence of blackgram (Vigna mungo L. Hepper) was assessed using Mahalanobis's D2 analysis and 64 genotypes were grouped into 12 clusters where, cluster-I was the largest with 19 genotypes followed by cluster-II and cluster-III with 13 genotypes each, cluster-VII with 7 genotypes, cluster-VI with 6 genotypes. Whereas, cluster-IV, cluster-V and clusters-VIII to XII had one genotype in each cluster. The intra cluster distance was maximum in cluster-VII followed by cluster-VI and cluster-III. Whereas, inter cluster distance was maximum between cluster-IV and cluster-XII. The cluster means estimated for 14 characters revealed that the cluster-IV showed lowest mean values and cluster-V showed highest mean value for most of the characters studied. Plant height contributed maximum to divergence followed by days to 50 per cent flowering, days to maturity, clusters per plant, 100 seed weight, these traits can be utilized for future crop improvement programme.
Key words :
Blackgram genotypes, D2 analysis, Genetic diversity, Inter-cluster, Intra-cluster, Quantitative traits.