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New Non-Invasive Method for the Authentication of Apple Cultivars

Food authentication is very important to protect consumers, sellers, and producers from fraud. Although several methods have been developed using a wide range of analytical techniques, most of them require sample destruction and do not allow in situ sampling or analysis, nor reliable quantification...

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Detalles Bibliográficos
Autores principales: Barberis, Elettra, Amede, Elia, Dondero, Francesco, Marengo, Emilio, Manfredi, Marcello
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750361/
https://www.ncbi.nlm.nih.gov/pubmed/35010215
http://dx.doi.org/10.3390/foods11010089
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author Barberis, Elettra
Amede, Elia
Dondero, Francesco
Marengo, Emilio
Manfredi, Marcello
author_facet Barberis, Elettra
Amede, Elia
Dondero, Francesco
Marengo, Emilio
Manfredi, Marcello
author_sort Barberis, Elettra
collection PubMed
description Food authentication is very important to protect consumers, sellers, and producers from fraud. Although several methods have been developed using a wide range of analytical techniques, most of them require sample destruction and do not allow in situ sampling or analysis, nor reliable quantification of hundreds of molecules at the same time. To overcome these limitations, we have developed and validated a new noninvasive analytical workflow for food authentication. The method uses a functionalized strip to adsorb small molecules from the surface of the food product, followed by gas chromatography–mass spectrometry analysis of the desorbed analytes. We validated the method and applied it to the classification of five different apple varieties. Molecular concentrations obtained from the analysis of 44 apples were used to identify markers for apple cultivars or, in combination with machine learning techniques, to perform cultivar classification. The overall reproducibility of the method was very good, showing a good coefficient of variation for both targeted and untargeted analysis. The approach was able to correctly classify all samples. In addition, the method was also used to detect pesticides and the following molecules were found in almost all samples: chlorpyrifos-methyl, deltamethrin, and malathion. The proposed approach not only showed very good analytical performance, but also proved to be suitable for noninvasive food authentication and pesticide residue analysis.
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spelling pubmed-87503612022-01-12 New Non-Invasive Method for the Authentication of Apple Cultivars Barberis, Elettra Amede, Elia Dondero, Francesco Marengo, Emilio Manfredi, Marcello Foods Article Food authentication is very important to protect consumers, sellers, and producers from fraud. Although several methods have been developed using a wide range of analytical techniques, most of them require sample destruction and do not allow in situ sampling or analysis, nor reliable quantification of hundreds of molecules at the same time. To overcome these limitations, we have developed and validated a new noninvasive analytical workflow for food authentication. The method uses a functionalized strip to adsorb small molecules from the surface of the food product, followed by gas chromatography–mass spectrometry analysis of the desorbed analytes. We validated the method and applied it to the classification of five different apple varieties. Molecular concentrations obtained from the analysis of 44 apples were used to identify markers for apple cultivars or, in combination with machine learning techniques, to perform cultivar classification. The overall reproducibility of the method was very good, showing a good coefficient of variation for both targeted and untargeted analysis. The approach was able to correctly classify all samples. In addition, the method was also used to detect pesticides and the following molecules were found in almost all samples: chlorpyrifos-methyl, deltamethrin, and malathion. The proposed approach not only showed very good analytical performance, but also proved to be suitable for noninvasive food authentication and pesticide residue analysis. MDPI 2021-12-29 /pmc/articles/PMC8750361/ /pubmed/35010215 http://dx.doi.org/10.3390/foods11010089 Text en © 2021 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
Barberis, Elettra
Amede, Elia
Dondero, Francesco
Marengo, Emilio
Manfredi, Marcello
New Non-Invasive Method for the Authentication of Apple Cultivars
title New Non-Invasive Method for the Authentication of Apple Cultivars
title_full New Non-Invasive Method for the Authentication of Apple Cultivars
title_fullStr New Non-Invasive Method for the Authentication of Apple Cultivars
title_full_unstemmed New Non-Invasive Method for the Authentication of Apple Cultivars
title_short New Non-Invasive Method for the Authentication of Apple Cultivars
title_sort new non-invasive method for the authentication of apple cultivars
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750361/
https://www.ncbi.nlm.nih.gov/pubmed/35010215
http://dx.doi.org/10.3390/foods11010089
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