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Geographic origin of European Emmental. Use of discriminant analysis and artificial neural network for classification purposes
Auteur(s)
Pillonel, Laurent
Editeur(s)
Bütikofer, U.
Schlichtherle-Cerny, H.
Tabacchi, Raphael
Bosset, Jacques-Olivier
Date de parution
2005
In
International Dairy Journal, Elsevier, 2005/15/6-9/557-562
Résumé
The goal of this work was to classify European Emmental cheeses according to their geographic origin using analytical approaches. Twenty-five analytical parameters (factors) were measured in 183 samples. Results were combined by multivariate statistical analysis. Discriminant analysis (DA) and an artificial neural network (ANN) delivered similar results when all regions and factors were included; 95% and 91%, respectively, of the samples were correctly classified in the validation procedure. To reduce the analytical costs and the risk of overfitting, a DA based on a selection of only 11 factors was calculated. In this case, the Jackknifed validation delivered 95% correct assignments. Finally, a system was optimised to discriminate between the Swiss samples and cheeses from other regions. Building a new model for each of the six pairs, Switzerland vs. another region, 100% correct classification could be achieved for the Swiss samples.
Autre version
http://dx.doi.org/10.1016/j.idairyj.2004.10.010
Type de publication
Resource Types::text::journal::journal article
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