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(1)H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils
During the last few years, the global demand for extra virgin olive oil (EVOO) is increased. Olive oil represents a significant percentage of world fat consumption determining an important development of its market. In this context, the problems related to counterfeiting and product fraud is becomin...
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/PMC7761774/ https://www.ncbi.nlm.nih.gov/pubmed/33287272 http://dx.doi.org/10.3390/foods9121797 |
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author | Girelli, Chiara Roberta Calò, Francesca Angilè, Federica Mazzi, Lucia Barbini, Daniele Fanizzi, Francesco Paolo |
author_facet | Girelli, Chiara Roberta Calò, Francesca Angilè, Federica Mazzi, Lucia Barbini, Daniele Fanizzi, Francesco Paolo |
author_sort | Girelli, Chiara Roberta |
collection | PubMed |
description | During the last few years, the global demand for extra virgin olive oil (EVOO) is increased. Olive oil represents a significant percentage of world fat consumption determining an important development of its market. In this context, the problems related to counterfeiting and product fraud is becoming extremely relevant. Thus, the quality and authenticity control of EVOOs is nowadays mandatory. In this study we focused on the use of (1)H NMR technique associated with multivariate statistical analysis to characterize Italian EVOOs commercial blends. In particular, a specific database including 126 monocultivar EVOOs reference samples, was used to characterize a total of 241 Italian EVOOs blends over four consecutive harvesting years. Moreover, the effect of the minor components (phenolic compounds) on the qualitative characterization of blended EVOOs was also evaluated. The correlation analysis of classification scores obtained using two pairwise orthogonal partial least square-discriminant analysis models (built with major and combined major–minor components NMR data) revealed that both could be profitably used to generally classify the studied Coratina containing blends. |
format | Online Article Text |
id | pubmed-7761774 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77617742020-12-26 (1)H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils Girelli, Chiara Roberta Calò, Francesca Angilè, Federica Mazzi, Lucia Barbini, Daniele Fanizzi, Francesco Paolo Foods Article During the last few years, the global demand for extra virgin olive oil (EVOO) is increased. Olive oil represents a significant percentage of world fat consumption determining an important development of its market. In this context, the problems related to counterfeiting and product fraud is becoming extremely relevant. Thus, the quality and authenticity control of EVOOs is nowadays mandatory. In this study we focused on the use of (1)H NMR technique associated with multivariate statistical analysis to characterize Italian EVOOs commercial blends. In particular, a specific database including 126 monocultivar EVOOs reference samples, was used to characterize a total of 241 Italian EVOOs blends over four consecutive harvesting years. Moreover, the effect of the minor components (phenolic compounds) on the qualitative characterization of blended EVOOs was also evaluated. The correlation analysis of classification scores obtained using two pairwise orthogonal partial least square-discriminant analysis models (built with major and combined major–minor components NMR data) revealed that both could be profitably used to generally classify the studied Coratina containing blends. MDPI 2020-12-03 /pmc/articles/PMC7761774/ /pubmed/33287272 http://dx.doi.org/10.3390/foods9121797 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 Girelli, Chiara Roberta Calò, Francesca Angilè, Federica Mazzi, Lucia Barbini, Daniele Fanizzi, Francesco Paolo (1)H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils |
title | (1)H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils |
title_full | (1)H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils |
title_fullStr | (1)H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils |
title_full_unstemmed | (1)H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils |
title_short | (1)H NMR Spectroscopy to Characterize Italian Extra Virgin Olive Oil Blends, Using Statistical Models and Databases Based on Monocultivar Reference Oils |
title_sort | (1)h nmr spectroscopy to characterize italian extra virgin olive oil blends, using statistical models and databases based on monocultivar reference oils |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7761774/ https://www.ncbi.nlm.nih.gov/pubmed/33287272 http://dx.doi.org/10.3390/foods9121797 |
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