Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy.

Mario Li Vigni,Sara Michelini,Marco Nocetti,Marina Cocchi,Caterina Durante

doi:10.3390/foods9111563

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.

Highlights

Developing objective analytical methodologies for food authentication has been one of the main issues since the introduction of the European Community regulation on quality labels [1]
The datasets and applied methodology are described in Section 2.4; as for the choice of model complexity, within the framework of alternative-Soft Independent Modeling of Class Analogy (SIMCA), we considered two cases: (i) only samples of the target class are available, as was our case, since not-Parmigiano Reggiano cheese samples (PR) samples were received at a second time from the Parmigiano Reggiano Cheese Consortium; (ii) a limited number of non-target class samples are available and can be considered in the model building phase
This is an estimate of the predictive capability toward correct acceptance of samples belonging to the target category

Summary

Introduction

Developing objective analytical methodologies for food authentication has been one of the main issues since the introduction of the European Community regulation on quality labels [1]. Authenticity encompasses several characteristics of a foodstuff and aims at defining its uniqueness or identity. In this respect, a holistic approach to food characterization, based on so-called fingerprint techniques, is emerging as most promising [2,3], and fast, non-destructive spectroscopic techniques, such as mid- (MIR) and near-infrared (NIR), Raman, nuclear magnetic resonance (NMR) aided by chemometrics modelling are used in wide-ranging applications [4,5,6,7,8], especially because they are suitable for a wide screening campaign and, in the case of NIR and Raman, for in situ analysis thanks to the development of handheld instruments.

Methods

Results

Discussion

Conclusion