Phyllometric parameters and artificial neural networks for the identification of Banksia accessions

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Phyllometric parameters and artificial neural networks for the identification of Banksia accessions

Taxonomic identification is traditionally carried out with dichotomous keys, or at least computer-based identification keys, often on the basis of subjective visual assessment and frequently unable to detect small differences at subspecies and varietal ranks. The aims of the present work were to (1)...

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Bibliographic Details
Main Authors:	Messina, G., Pandolfi, C., Mugnai, S., Azzarello, E., Dixon, Kingsley, Mancuso, S.
Format:	Journal Article
Published:	2009
Online Access:	http://hdl.handle.net/20.500.11937/4681

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