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PubMed · 11767553

[Cluster analysis methods appropriate for classification of drought-resistant wheat ecotypes].

S Chai
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Abstract

The appropriate cluster analysis methods for classification of drought-resistant wheat ecotypes were investigated, based on the analysis of 21 morphologic and agronomic characters of 15 winter wheat cultivars. According to the proximity degree to the results from experts experiences, the cluster results using original data were orderly better than those using Varimax orthogonal rotation, Promax skew intersection rotation, and principal component analysis with phenotypic mean's correlation matrix. The results using Euclidean distance were greater than those using Mahalanobis distance. The clustering methods of correspondent analysis and fuzzy cluster were better than those of nearest distance, furthest distance or group average method (UPGMA). Among all cluster results from various methods combined, the two cluster results from the fuzzy cluster using original data and from the correspondence analysis method were closest to the results of experts' experience. Based on both comparisons of results and examination of the performance of different strategies with several statistical properties, the two methods mentioned above were also acceptable.

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S Chai. 2000. [Cluster analysis methods appropriate for classification of drought-resistant wheat ecotypes].. https://pubmed.ncbi.nlm.nih.gov/11767553/

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