Spotting Frozen Curd in PDO Buffalo Mozzarella Cheese Through Insights on Its Supramolecular Structure Acquired by 1H TD-NMR Relaxation Experiments

Carlo Mengucci,Alessandra Aiello,Francesco Capozzi,Gianfranco Picone,Pasquale Ferranti,Raffaele Romano,Davide Rabiti,Eleonora Urbinati

doi:10.3390/app11041466

Abstract

The addition of frozen curd (FC) during the production process of “Mozzarella di Bufala Campana”, an Italian cheese with Protected Designation of Origin (PDO), is a common fraud not involving modifications of the chemical composition in the final product. Its detection cannot thus be easily obtained by common analytical methods, which are targeted at changes in concentrations of diagnostic chemical species. In this work, the possibility of spotting this fraud by focusing on the modifications of the supramolecular structure of the food matrix, detected by time domain nuclear magnetic resonance (TD-NMR) experiments, was investigated. Cheese samples were manufactured in triplicate, according to the PDO disciplinary of production, except for using variable amounts of FC (i.e., 0, 15, 30, and 50% w/w). Relaxation data were analysed through different approaches: (i) Discrete multi-exponential fitting, (ii) continuous Laplace inverse fitting, and (iii) chemometrics approach. The strategy that lead to best detection results was the chemometrics analysis of raw Carr-Purcell-Meiboom-Gill (CPMG) decays, allowing to discriminate between compliant and adulterated samples, with as low as 15% of FC addition. The strategy is based on the use of machine learning for projection on latent structures of raw CPMG data and classification tasks for fraud detection, using quadratic discriminant analysis. By coupling TD-NMR raw decays with machine learning, this work opens the way to set up a system for detecting common food frauds modifying the matrix structure, for which no official authentication methods are yet available.

Highlights

IntroductionMany food frauds involve the chemical composition alteration of the product: a large part of analytical methods aims to detect differences in chemical compositions of non-compliant products, involving highly sophisticated techniques [1]
Food authenticity issues are of great awareness between the agri-food system actors.Fraudulent practices determine misinformation and safety concerns for consumers, unfair competition towards honest producers, and non-compliances to national and international legislations and standards [1,2].Many food frauds involve the chemical composition alteration of the product: a large part of analytical methods aims to detect differences in chemical compositions of non-compliant products, involving highly sophisticated techniques [1].when the fraud involves the modification of the physical state of the food matrix rather than its chemical composition, common food authentication methods are not effective
Due to the stretching process, the mozzarella cheese structure is characterised by channels filled with serum and fat globules dispersed between the casein fibres constituting the gel network [15]

Summary

Introduction

Many food frauds involve the chemical composition alteration of the product: a large part of analytical methods aims to detect differences in chemical compositions of non-compliant products, involving highly sophisticated techniques [1]. When the fraud involves the modification of the physical state of the food matrix rather than its chemical composition, common food authentication methods are not effective. This task remains challenging in the case of mozzarella cheese added with frozen curd (FC), as no effective molecular markers of this kind of adulteration have been detected so far, at a difference with other frauds such as geographical or milk species origin [3,4]. Further studies did not confirm these findings [6]

Methods

Results

Conclusion