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P-ISSN: 2349-8528, E-ISSN: 2321-4902   |   Impact Factor: GIF: 0.565 NAAS Rating: 5.31 NEW

International Journal of Chemical Studies

Vol. 6, Issue 1 (2018)
Multivariate clustering utilizing R software analytics


Author(s): Immad A Shah, Sabreena A Wani, Showkat Yousuf, Tashooq Bhat and Faisal Noor

Abstract: Hierarchical clustering approach was used to group the Maize genotypes and the distance measure used was Euclidean distance. Cluster analysis using the R software grouped the 55 genotypes into distinct clusters using the Euclidean distances between the various genotypes. All the three types of dendrograms obtained indicate single, complete, and average linkage. Single linkage group the genotypes on the basis of the similarity. It was found that when the dendrogram for single linkage was cut at a distance of 4, it revealed two distinct clusters for the 55 genotypes. It clearly classified the genotypes, with cluster one containing the individual plants and cluster two containing crosses. Level plot was also obtained which indicated at least two distinct groups with large inter cluster distance.

Pages: 971-974  |  357 Views  10 Downloads

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How to cite this article:
Immad A Shah, Sabreena A Wani, Showkat Yousuf, Tashooq Bhat, Faisal Noor. Multivariate clustering utilizing R software analytics. Int J Chem Stud 2018;6(1):971-974.
International Journal of Chemical Studies