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Hierarchical cluster analysis as a tool to manage variation in germplasm collections
1Department of Applied Biology, Cambridge University, Pembroke Street, CB2 3DX, Cambridge, UK.
Abstract:
The potential of using hierarchical cluster analysis to classify entries from a germplasm collection according to their degree of similarity was assessed. Results suggest that similarity is generally greatest among individual entries by country of origin and that hierarchical cluster analysis could be used as a tool to classify entries from germplasm collections according to their respective gene pools, even when no passport data are available. Based on this technique, it is also shown that the segregative potential of entries can be estimated.
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