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Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy

Raman spectroscopy, and handheld spectrometers in particular, are gaining increasing attention in food quality control as a fast, portable, non-destructive technique. Furthermore, this technology also allows for measuring the intact sample through the packaging and, with respect to near infrared spe...

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Autores principales: Li Vigni, Mario, Durante, Caterina, Michelini, Sara, Nocetti, Marco, Cocchi, Marina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7692761/
https://www.ncbi.nlm.nih.gov/pubmed/33126689
http://dx.doi.org/10.3390/foods9111563
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author Li Vigni, Mario
Durante, Caterina
Michelini, Sara
Nocetti, Marco
Cocchi, Marina
author_facet Li Vigni, Mario
Durante, Caterina
Michelini, Sara
Nocetti, Marco
Cocchi, Marina
author_sort Li Vigni, Mario
collection PubMed
description Raman spectroscopy, and handheld spectrometers in particular, are gaining increasing attention in food quality control as a fast, portable, non-destructive technique. Furthermore, this technology also allows for measuring the intact sample through the packaging and, with respect to near infrared spectroscopy, it is not affected by the water content of the samples. In this work, we evaluate the potential of the methodology to model, by multivariate data analysis, the authenticity of Parmigiano Reggiano cheese, which is one of the most well-known and appreciated hard cheeses worldwide, with protected denomination of origin (PDO). On the other hand, it is also highly subject to counterfeiting. In particular, it is critical to assess the authenticity of grated cheese, to which, under strictly specified conditions, the PDO is extended. To this aim, it would be highly valuable to develop an authenticity model based on a fast, non-destructive technique. In this work, we present preliminary results obtained by a handheld Raman spectrometer and class-modeling (Soft Independent Modeling of Class Analogy, SIMCA), which are extremely promising, showing sensitivity and specificity of 100% for the test set. Moreover, another salient issue, namely the percentage of rind in grated cheese, was addressed by developing a multivariate calibration model based on Raman spectra. It was possible to obtain a prediction error around 5%, with 18% being the maximum content allowed by the production protocol.
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spelling pubmed-76927612020-11-28 Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy Li Vigni, Mario Durante, Caterina Michelini, Sara Nocetti, Marco Cocchi, Marina Foods Article Raman spectroscopy, and handheld spectrometers in particular, are gaining increasing attention in food quality control as a fast, portable, non-destructive technique. Furthermore, this technology also allows for measuring the intact sample through the packaging and, with respect to near infrared spectroscopy, it is not affected by the water content of the samples. In this work, we evaluate the potential of the methodology to model, by multivariate data analysis, the authenticity of Parmigiano Reggiano cheese, which is one of the most well-known and appreciated hard cheeses worldwide, with protected denomination of origin (PDO). On the other hand, it is also highly subject to counterfeiting. In particular, it is critical to assess the authenticity of grated cheese, to which, under strictly specified conditions, the PDO is extended. To this aim, it would be highly valuable to develop an authenticity model based on a fast, non-destructive technique. In this work, we present preliminary results obtained by a handheld Raman spectrometer and class-modeling (Soft Independent Modeling of Class Analogy, SIMCA), which are extremely promising, showing sensitivity and specificity of 100% for the test set. Moreover, another salient issue, namely the percentage of rind in grated cheese, was addressed by developing a multivariate calibration model based on Raman spectra. It was possible to obtain a prediction error around 5%, with 18% being the maximum content allowed by the production protocol. MDPI 2020-10-28 /pmc/articles/PMC7692761/ /pubmed/33126689 http://dx.doi.org/10.3390/foods9111563 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
Li Vigni, Mario
Durante, Caterina
Michelini, Sara
Nocetti, Marco
Cocchi, Marina
Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy
title Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy
title_full Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy
title_fullStr Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy
title_full_unstemmed Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy
title_short Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy
title_sort preliminary assessment of parmigiano reggiano authenticity by handheld raman spectroscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7692761/
https://www.ncbi.nlm.nih.gov/pubmed/33126689
http://dx.doi.org/10.3390/foods9111563
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