Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils
Artemis Lioupi,
Ioannis Sampsonidis,
Christina Virgiliou,
Vassiliki T. Papoti,
Kyriaki G. Zinoviadou,
Apostolos Spyros,
Georgios Theodoridis
Affiliations
Artemis Lioupi
Laboratory of Analytical Chemistry, School of Chemistry, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
Ioannis Sampsonidis
Biomic AUTh, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center B1.4, 10th km Thessaloniki-Thermi Rd, P.O. Box 8318, GR-57001 Thessaloniki, Greece
Christina Virgiliou
Laboratory of Analytical Chemistry, School of Chemistry, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
Vassiliki T. Papoti
Department of Food Science and Technology, Perrotis College, American Farm School, GR-55102 Thessaloniki, Greece
Kyriaki G. Zinoviadou
Department of Food Science and Technology, Perrotis College, American Farm School, GR-55102 Thessaloniki, Greece
Apostolos Spyros
NMR Laboratory, Department of Chemistry, University of Crete, Voutes Campus, P.O. Box 2208, GR-71003 Heraklion, Crete, Greece
Georgios Theodoridis
Laboratory of Analytical Chemistry, School of Chemistry, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
A headspace-solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) method was developed herein for the analysis of virgin olive oil volatile metabolome. Optimisation of SPME conditions was performed by Design of Experiments (DoE) and Response Surface Methodology (RSM) approaches and factors, such as sample volume, sample stirring, extraction temperature and time, and desorption temperature and time, were examined to reach optimal microextraction conditions. The potential of the optimised method was then investigated for its use in the classification of Cretan virgin olive oil samples with the aid of multivariate statistical analysis. Certain markers were identified with significance in the geographical classification of Cretan extra-virgin olive oil (EVOO) samples. In total, 92 volatile organic compounds were tentatively identified and semi-quantified, and the data obtained confirm that the method is robust, reliable, and analytically powerful for olive oil classification.
