title: Classification of 7 monofloral honey varieties by PTR-ToF-MS direct headspace analysis and chemometrics.
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.
authors.affiliation: Institut für Ionenphysik und Angewandte Physik, Leopold Franzens Universität Innsbruck, Technikerstr. 25, A-6020 Innsbruck, Austria. Electronic address: erna.schuhfried@uibk.ac.at.
authors.forename: Erna
authors.initials: E
authors.lastname: Schuhfried
authors.affiliation: Research Center for Food and Nutrition (CRA-NUT), Agricultural Research Council, Via Ardeatina, 546, 00100 Rome, Italy. Electronic address: jsapuri@hotmail.com.
authors.forename: José
authors.initials: J
authors.lastname: Sánchez del Pulgar
authors.affiliation: Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna (IZSLER), Department of Applied Chemistry for Food Technology - Università del Piemonte Orientale "Amedeo Avogadro", Via Bianchi 9, 25124 Brescia, Italy. Electronic address: marco_bobba@yahoo.it.
authors.forename: Marco
authors.initials: M
authors.lastname: Bobba
authors.affiliation: Istituto Zooprofilattico Sperimentale delle Venezie - Food Products Valorization Department, Legnaro, PD, Italy. Electronic address: RPiro@izsvenezie.it.
authors.forename: Roberto
authors.initials: R
authors.lastname: Piro
authors.affiliation: 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.
authors.forename: Luca
authors.initials: L
authors.lastname: Cappellin
authors.affiliation: Institut für Ionenphysik und Angewandte Physik, Leopold Franzens Universität Innsbruck, Technikerstr. 25, A-6020 Innsbruck, Austria. Electronic address: tilmann.maerk@uibk.ac.at.
authors.forename: Tilmann D
authors.initials: TD
authors.lastname: Märk
authors.affiliation: 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.
authors.forename: Franco
authors.initials: F
authors.lastname: Biasioli
mesh_terms: D016002:Discriminant Analysis; D035264:Flowers; D006722:Honey / Q000145:classification*; D016018:Least-Squares Analysis; D013058:Mass Spectrometry / Q000379:methods*; D016571:Neural Networks, Computer; D025341:Principal Component Analysis; D011522:Protons; D013223:Statistics as Topic / Q000379:methods*
chemical_list: D011522:Protons
keywords: Classification; Floral origin; Honey; Neural networks; PTR-ToF-MS