Classification of olive oils according to geographical origin by using H NMR fingerprinting combined with multivariate analysis |
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Authors: | F Longobardi A Ventrella C Napoli E Humpfer B Schütz H Schäfer MG Kontominas A Sacco |
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Affiliation: | 1. Dipartimento di Chimica, Università degli Studi di Bari “Aldo Moro”, Via Orabona 4, 70126 Bari, Italy;2. Bruker BioSpin S.r.l., Viale Lancetti 43, 20158 Milano, Italy;3. Bruker BioSpin GmbH, Silberstreifen, D-76287 Rheinstetten, Germany;4. Laboratory of Food Chemistry and Technology, Department of Chemistry, University of Ioannina, P.O. Box 1186, 45110 Ioannina, Greece |
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Abstract: | Authentic extravirgin olive oils from 7 different regions (Italy – 3 regions, Greece – 4 regions) have been investigated by 1H Nuclear Magnetic Resonance (NMR) fingerprinting in combination with multivariate statistical analysis. In order to cover the dominating lipid signals as well as signals from compounds of low abundance in the oil, both a simple one pulse experiment and an experiment with multiple saturation of the lipid signals was applied to each sample. Thus, the dynamic range of concentrations covered by the two experiments was of the order of 100,000 allowing for a more comprehensive NMR assessment of the samples. Monte-Carlo embedded cross-validation was used to demonstrate that a combination of principal component analysis, canonical analysis, and classification via nearest class mean can be used to predict the origin of olive oil samples from 1H NMR data. Given the rather limited number of samples tested, correct prediction probabilities of 78% were achieved with region specific correct predictions between 53% and 100%. |
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Keywords: | 1H NMR Fingerprinting Multi-signal suppression sequence Multivariate statistical analysis Olive oil Geographic origin |
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