Camellia japonica L. genotypes identified by an artificial neural network based on phyllometric and fractal parameters

Abstract

The potential application of phyllometric and fractal parameters for the objective quantitative description of leaf morphology, combined with the use of Back Propagation Neural Network (BPNN) for data modelling, was evaluated to characterize and identify 25 Camellia japonica L. accessions from an Italian historical collection. Results show that the… (More)
DOI: 10.1007/s00606-007-0601-7

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@article{Mugnai2007CamelliaJL, title={Camellia japonica L. genotypes identified by an artificial neural network based on phyllometric and fractal parameters}, author={Sergio Mugnai and Claudia Pandolfi and Elisa Azzarello and Elisa Masi and Salvatore Mancuso}, journal={Plant Systematics and Evolution}, year={2007}, volume={270}, pages={95-108} }