| Title: | Traceability of honey origin based on volatiles pattern processing by artificial neural networks |
| Author(s): | Cajka T; Hajslova J; Pudil F; Riddellova K; |
| Address: | "Institute of Chemical Technology, Prague, Faculty of Food and Biochemical Technology, Department of Food Chemistry and Analysis, Technicka 5, 16628 Prague 6, Czech Republic" |
| DOI: | 10.1016/j.chroma.2008.12.066 |
| ISSN/ISBN: | 1873-3778 (Electronic) 0021-9673 (Linking) |
| Abstract: | "Head-space solid-phase microextraction (HS-SPME)-based procedure, coupled to comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GCxGC-TOF-MS), was employed for fast characterisation of honey volatiles. In total, 374 samples were collected over two production seasons in Corsica (n=219) and other European countries (n=155) with the emphasis to confirm the authenticity of the honeys labelled as 'Corsica' (protected denomination of origin region). For the chemometric analysis, artificial neural networks with multilayer perceptrons (ANN-MLP) were tested. The best prediction (94.5%) and classification (96.5%) abilities of the ANN-MLP model were obtained when the data from two honey harvests were aggregated in order to improve the model performance compared to separate year harvests" |
| Keywords: | "Food Analysis/*methods Gas Chromatography-Mass Spectrometry/methods Honey/*analysis *Neural Networks, Computer Principal Component Analysis/methods Reproducibility of Results Solid Phase Microextraction/methods Volatile Organic Compounds/analysis;" |
| Notes: | "MedlineCajka, Tomas Hajslova, Jana Pudil, Frantisek Riddellova, Katerina eng Research Support, Non-U.S. Gov't Netherlands 2009/01/20 J Chromatogr A. 2009 Feb 27; 1216(9):1458-62. doi: 10.1016/j.chroma.2008.12.066. Epub 2008 Dec 27" |
