Traceability of olive oil based on volatiles pattern and multivariate analysis

An automated head-space solid-phase microextraction (HS-SPME)-based sampling procedure, coupled to gas chromatography–ion trap mass spectrometry (GC–ITMS), was developed and employed for fast characterisation of olive oil volatiles. In total, 914 samples were collected, over three production seasons...

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Bibliographic Details
Published in:Food chemistry 2010-07, Vol.121 (1), p.282-289
Main Authors: Cajka, Tomas, Riddellova, Katerina, Klimankova, Eva, Cerna, Monika, Pudil, Frantisek, Hajslova, Jana
Format: Article
Language:English
Subjects:
Authenticity
Biological and medical sciences
Comprehensive two-dimensional gas chromatography
equipment performance
Fat industries
food analysis
food composition
Food industries
Fundamental and applied biological sciences. Psychology
Head-space solid-phase microextraction
headspace analysis
Mass spectrometry
Multivariate analysis
new methods
Olive oil
product authenticity
provenance
rapid methods
Traceability
volatile compounds
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Summary:An automated head-space solid-phase microextraction (HS-SPME)-based sampling procedure, coupled to gas chromatography–ion trap mass spectrometry (GC–ITMS), was developed and employed for fast characterisation of olive oil volatiles. In total, 914 samples were collected, over three production seasons, in north-western Italy—Liguria ( n = 210) and other regions—in addition to the rest of Italy, Spain, France, Greece, Cyprus, and Turkey ( n = 704) with the aim to distinguish, based on analytical (profiling) data, the olive oils labelled as “Ligurian” (protected denomination of origin region, PDO) from all the others (“non-Ligurian”). For the chemometric analysis, linear discriminant analysis (LDA) and artificial neural networks with multilayer perceptrons (ANN-MLP) were tested. Employing LDA, somewhat lower recognition (81.4%) and prediction (61.7%) abilities were obtained. The classification model was significantly improved using ANN-MLP. Under these conditions, the recognition (90.1%) and prediction (81.1%) abilities were achieved. The diagnostic value of the data obtained by one-dimensional GC–ITMS were compared with those generated by two-dimensional gas chromatography–time-of-flight mass spectrometry (GC × GC–TOFMS), allowing a comprehensive analysis of olive oil volatiles.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2009.12.011