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Talanta

Title:		Classification of 7 monofloral honey varieties by PTR-ToF-MS direct headspace analysis and chemometrics
Author(s):		Schuhfried E; Sanchez del Pulgar J; Bobba M; Piro R; Cappellin L; Mark TD; Biasioli F;
Address:		"Institut fur Ionenphysik und Angewandte Physik, Leopold Franzens Universitat Innsbruck, Technikerstr. 25, A-6020 Innsbruck, Austria. Electronic address: erna.schuhfried@uibk.ac.at. Research Center for Food and Nutrition (CRA-NUT), Agricultural Research Council, Via Ardeatina, 546, 00100 Rome, Italy. Electronic address: jsapuri@hotmail.com. Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna (IZSLER), Department of Applied Chemistry for Food Technology - Universita del Piemonte Orientale 'Amedeo Avogadro', Via Bianchi 9, 25124 Brescia, Italy. Electronic address: marco_bobba@yahoo.it. Istituto Zooprofilattico Sperimentale delle Venezie - Food Products Valorization Department, Legnaro, PD, Italy. Electronic address: RPiro@izsvenezie.it. IASMA Research and Innovation Centre, Fondazione Edmund Mach, Food Quality and Nutrition Department, Via E. Mach 1, S Michele a/A, 38010 TN, Italy. Electronic address: luca.cappellin@fmach.it. Institut fur Ionenphysik und Angewandte Physik, Leopold Franzens Universitat Innsbruck, Technikerstr. 25, A-6020 Innsbruck, Austria. Electronic address: tilmann.maerk@uibk.ac.at. IASMA Research and Innovation Centre, Fondazione Edmund Mach, Food Quality and Nutrition Department, Via E. Mach 1, S Michele a/A, 38010 TN, Italy. Electronic address: franco.biasioli@fmach.it"
Journal Title:		Talanta
Year:		2016
Volume:		20150928
Issue:
Page Number:		213 - 219
DOI:		10.1016/j.talanta.2015.09.062
ISSN/ISBN:		1873-3573 (Electronic) 0039-9140 (Linking)
Abstract:		"Honey, in particular monofloral varieties, is a valuable commodity. Here, we present proton transfer reaction-time of flight-mass spectrometry, PTR-ToF-MS, coupled to chemometrics as a successful tool in the classification of monofloral honeys, which should serve in fraud protection against mispresentation of the floral origin of honey. We analyzed 7 different honey varieties from citrus, chestnut, sunflower, honeydew, robinia, rhododendron and linden tree, in total 70 different honey samples and a total of 206 measurements. Only subtle differences in the profiles of the volatile organic compounds (VOCs) in the headspace of the different honeys could be found. Nevertheless, it was possible to successfully apply 6 different classification methods with a total correct assignment of 81-99% in the internal validation sets. The most successful methods were stepwise linear discriminant analysis (LDA) and probabilistic neural network (PNN), giving total correct assignments in the external validation sets of 100 and 90%, respectively. Clearly, PTR-ToF-MS/chemometrics is a powerful tool in honey classification"
Keywords:		"Discriminant Analysis *Flowers Honey/*classification Least-Squares Analysis Mass Spectrometry/*methods Neural Networks, Computer Principal Component Analysis *Protons Statistics as Topic/*methods Classification Floral origin Honey Neural networks PTR-ToF-;"
Notes:		"MedlineSchuhfried, Erna Sanchez del Pulgar, Jose Bobba, Marco Piro, Roberto Cappellin, Luca Mark, Tilmann D Biasioli, Franco eng Netherlands 2015/11/26 Talanta. 2016 Jan 15; 147:213-9. doi: 10.1016/j.talanta.2015.09.062. Epub 2015 Sep 28"