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Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils
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) appro...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878322/ https://www.ncbi.nlm.nih.gov/pubmed/35208191 http://dx.doi.org/10.3390/metabo12020114 |
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author | Lioupi, Artemis Sampsonidis, Ioannis Virgiliou, Christina Papoti, Vassiliki T. Zinoviadou, Kyriaki G. Spyros, Apostolos Theodoridis, Georgios |
author_facet | Lioupi, Artemis Sampsonidis, Ioannis Virgiliou, Christina Papoti, Vassiliki T. Zinoviadou, Kyriaki G. Spyros, Apostolos Theodoridis, Georgios |
author_sort | Lioupi, Artemis |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8878322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88783222022-02-26 Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils Lioupi, Artemis Sampsonidis, Ioannis Virgiliou, Christina Papoti, Vassiliki T. Zinoviadou, Kyriaki G. Spyros, Apostolos Theodoridis, Georgios Metabolites Article 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. MDPI 2022-01-25 /pmc/articles/PMC8878322/ /pubmed/35208191 http://dx.doi.org/10.3390/metabo12020114 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lioupi, Artemis Sampsonidis, Ioannis Virgiliou, Christina Papoti, Vassiliki T. Zinoviadou, Kyriaki G. Spyros, Apostolos Theodoridis, Georgios Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils |
title | Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils |
title_full | Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils |
title_fullStr | Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils |
title_full_unstemmed | Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils |
title_short | Optimisation of the HS-SPME/GC-MS Approach by Design of Experiments Combined with Chemometrics for the Classification of Cretan Virgin Olive Oils |
title_sort | optimisation of the hs-spme/gc-ms approach by design of experiments combined with chemometrics for the classification of cretan virgin olive oils |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878322/ https://www.ncbi.nlm.nih.gov/pubmed/35208191 http://dx.doi.org/10.3390/metabo12020114 |
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