International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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Original Research Articles                      Volume : 10, Issue:1, January, 2021

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : /
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2021.10(1): 304-312

Assessing Diversity of Sesame Genotypes Using Cluster Analysis and Principal Component Analysis
Deepak Gupta1*, Suresh Muralia2, Vikas Khandelwal3 and Anju Nehra1
1Department of Plant Breeding and Genetics, SKN College of Agriculture, Jobner, India
2Agriculture Research Station, Navgaon, India
3ICAR-AICRP on Pearlmillet, Jodhpur, India
*Corresponding author

The present research work comprises twenty one genotypes of sesame were evaluated in a randomized complete block design (RCBD) with three replications at Agricultural Research Station, Navgaon (Alwar) during Kharif 2019. The presence of genetic divergence among these lines was observed by Mahalanobis’s D2 statistic. All the accesses were grouped into five distinct clusters. The highest number of genotypes appeared in cluster I (14) followed by cluster II (3) and cluster III (2) while the lowest numbers of entries were reported in cluster IV (1) & V (1). Principal component analysis (PCA) indicated that the three principal components (PC1 to PC3) showed 67.43 per cent of the total variability. The first principal component had high positive loading for seed yield per plant, capsules bearing length and seeds per capsule which contributed more to the diversity. The second principal component had high loading for days to maturity, number of primary branches per plant and 1000-seed weight. The genotypes viz., RT-346, GT-10 and EC-351880 were identified as the most diverse genotypes, based on component scores and these genotypes could be utilized as parents in hybridization programme.

Keywords: Sesame, PCA, Genetic diversity, Genotypes, Inter cluster distance, Intra cluster distance

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How to cite this article:

Deepak Gupta, Suresh Muralia, Vikas Khandelwal and Anju Nehra. 2021. Assessing Diversity of Sesame Genotypes Using Cluster Analysis and Principal Component Analysis.Int.J.Curr.Microbiol.App.Sci. 10(1): 304-312. doi:
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.