An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs’ Compliance with CFPR Guidelines

Abbatangelo, Marco; Núñez-Carmona, Estefanía; Sberveglieri, Veronica; Zappa, Dario; Comini, Elisabetta; Sberveglieri, Giorgio

doi:10.3390/bios10050047

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An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs’ Compliance with CFPR Guidelines

Marco Abbatangelo

^1,*

Estefanía Núñez-Carmona

Veronica Sberveglieri

^2,3

Dario Zappa

Elisabetta Comini

^1,3

and

Giorgio Sberveglieri

^1,3

Department of Information Engineering, University of Brescia, Brescia, via Branze, 38, 25123 Brescia, BS, Italy

CNR-IBBR, Institute of Bioscience and Bioresources, via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy

NANO SENSOR SYSTEMS, NASYS Spin-Off University of Brescia, Brescia, via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy

Author to whom correspondence should be addressed.

Biosensors 2020, 10(5), 47; https://doi.org/10.3390/bios10050047

Received: 15 April 2020 / Revised: 28 April 2020 / Accepted: 29 April 2020 / Published: 2 May 2020

(This article belongs to the Special Issue Sensors for Food Safety)

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Abstract

Parmigiano Reggiano cheese is one of the most appreciated Italian foods on account of its high nutrient content and taste. Due to its high cost, these characteristics make this product subject to counterfeiting in different forms. In this study, an approach based on an array of gas sensors has been employed to assess if it was possible to distinguish different samples based on their aroma. Samples were characterized in terms of rind percentage, seasoning, and rind working process. From the responses of the sensors, five features were extracted and the capability of these parameters to recognize target classes was tested with statistical analysis. Hence, the performance of the sensors’ array was quantified using artificial neural networks. To simplify the problem, a hierarchical approach has been used: three steps of classification were performed, and in each step one parameter of the grated cheese was identified (firstly, seasoning; secondly, rind working process; finally, rind percentage). The accuracies ranged from 88.24% to 100%. View Full-Text

Keywords: electronic nose; nanowire gas sensors; MOX sensors; rapid detection; food quality control; Parmigiano Reggiano; artificial neural network

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MDPI and ACS Style

Abbatangelo, M.; Núñez-Carmona, E.; Sberveglieri, V.; Zappa, D.; Comini, E.; Sberveglieri, G. An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs’ Compliance with CFPR Guidelines. Biosensors 2020, 10, 47. https://doi.org/10.3390/bios10050047

AMA Style

Abbatangelo M, Núñez-Carmona E, Sberveglieri V, Zappa D, Comini E, Sberveglieri G. An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs’ Compliance with CFPR Guidelines. Biosensors. 2020; 10(5):47. https://doi.org/10.3390/bios10050047

Chicago/Turabian Style

Abbatangelo, Marco, Estefanía Núñez-Carmona, Veronica Sberveglieri, Dario Zappa, Elisabetta Comini, and Giorgio Sberveglieri. 2020. "An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs’ Compliance with CFPR Guidelines" Biosensors 10, no. 5: 47. https://doi.org/10.3390/bios10050047

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An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs’ Compliance with CFPR Guidelines

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