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Multivariate clustering utilizing R software analytics

International Journal of Chemical Studies · 2018 · Vol. 6(1) · pp. 971–974

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.

Genetics and Plant BreedingDendrogramHierarchical clusteringComplete linkageEuclidean distanceSimilarity (geometry)Linkage (software)Cluster analysisCluster (spacecraft)MathematicsMultivariate statistics
Citations
1
FWCI
0.34
field-weighted impact
References
0
Percentile
78%
vs. same field & year
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Multivariate clustering utilizing R software analytics · Scinovex