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.

Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy / Li Vigni, M.; Durante, C.; Michelini, S.; Nocetti, M.; Cocchi, M.. - In: FOODS. - ISSN 2304-8158. - 9:11(2020), pp. 1563-1579. [10.3390/foods9111563]

Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy

Li Vigni, M.;Durante, C.;Michelini, S.;Nocetti, M.;Cocchi, M.
2020

Abstract

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.
2020
9
11
1563
1579
Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy / Li Vigni, M.; Durante, C.; Michelini, S.; Nocetti, M.; Cocchi, M.. - In: FOODS. - ISSN 2304-8158. - 9:11(2020), pp. 1563-1579. [10.3390/foods9111563]
Li Vigni, M.; Durante, C.; Michelini, S.; Nocetti, M.; Cocchi, M.
File in questo prodotto:
File Dimensione Formato  
foods-09-01563.pdf

Open access

Tipologia: Versione pubblicata dall'editore
Dimensione 1.21 MB
Formato Adobe PDF
1.21 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1213991
Citazioni
  • ???jsp.display-item.citation.pmc??? 1
  • Scopus 18
  • ???jsp.display-item.citation.isi??? 17
social impact