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The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples
In the present study, volatile compound analysis of olive oil samples belonging to ten Greek cultivars was carried out. A total of 167 olive oil samples collected from two consecutive harvest years were analyzed by Head Space-Solid Phase Microextraction-Gas Chromatography/Mass Spectrometry (HS-SPME-...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696207/ https://www.ncbi.nlm.nih.gov/pubmed/33203191 http://dx.doi.org/10.3390/foods9111672 |
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author | Kosma, Ioanna S. Kontominas, Michael G. Badeka, Anastasia V. |
author_facet | Kosma, Ioanna S. Kontominas, Michael G. Badeka, Anastasia V. |
author_sort | Kosma, Ioanna S. |
collection | PubMed |
description | In the present study, volatile compound analysis of olive oil samples belonging to ten Greek cultivars was carried out. A total of 167 olive oil samples collected from two consecutive harvest years were analyzed by Head Space-Solid Phase Microextraction-Gas Chromatography/Mass Spectrometry (HS-SPME-GC/MS). Volatile compound data were combined with chemometric methods (Multivariate Analysis of Variance (MANOVA) and Linear Discriminant Analysis (LDA)) with the aim not only to differentiate olive oils but also to identify characteristic volatile compounds that would enable differentiation of botanical origin (marker compounds). The application of Stepwise LDA (SLDA) effectively reduced the large number of statistically significant volatile compounds involved in the differentiation process, and thus, led to a set of parameters, the majority of which belong to compounds that are highly dependent on variety. In addition, the use of these marker compounds resulted in an increased correct classification rate (85.6%) using the cross-validation method indicating the validity of the model developed despite the use of a large number of dependent variables (cultivars). |
format | Online Article Text |
id | pubmed-7696207 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76962072020-11-29 The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples Kosma, Ioanna S. Kontominas, Michael G. Badeka, Anastasia V. Foods Article In the present study, volatile compound analysis of olive oil samples belonging to ten Greek cultivars was carried out. A total of 167 olive oil samples collected from two consecutive harvest years were analyzed by Head Space-Solid Phase Microextraction-Gas Chromatography/Mass Spectrometry (HS-SPME-GC/MS). Volatile compound data were combined with chemometric methods (Multivariate Analysis of Variance (MANOVA) and Linear Discriminant Analysis (LDA)) with the aim not only to differentiate olive oils but also to identify characteristic volatile compounds that would enable differentiation of botanical origin (marker compounds). The application of Stepwise LDA (SLDA) effectively reduced the large number of statistically significant volatile compounds involved in the differentiation process, and thus, led to a set of parameters, the majority of which belong to compounds that are highly dependent on variety. In addition, the use of these marker compounds resulted in an increased correct classification rate (85.6%) using the cross-validation method indicating the validity of the model developed despite the use of a large number of dependent variables (cultivars). MDPI 2020-11-15 /pmc/articles/PMC7696207/ /pubmed/33203191 http://dx.doi.org/10.3390/foods9111672 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kosma, Ioanna S. Kontominas, Michael G. Badeka, Anastasia V. The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples |
title | The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples |
title_full | The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples |
title_fullStr | The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples |
title_full_unstemmed | The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples |
title_short | The Application of Chemometrics to Volatile Compound Analysis for the Recognition of Specific Markers for Cultivar Differentiation of Greek Virgin Olive Oil Samples |
title_sort | application of chemometrics to volatile compound analysis for the recognition of specific markers for cultivar differentiation of greek virgin olive oil samples |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696207/ https://www.ncbi.nlm.nih.gov/pubmed/33203191 http://dx.doi.org/10.3390/foods9111672 |
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