Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloApplication of a novel S3 nanowire gas sensor device in parallel with GC-MS for the identification of rind percentage of grated Parmigiano Reggiano
Anno di pubblicazione2018
FormatoElettronico
Autore/iMarco Abbatangelo, Estefanía Núñez-Carmona, Veronica Sberveglieri, Dario Zappa, Elisabetta Comini, Giorgio Sberveglieri
Affiliazioni autoriDepartment of Information Engineering, University of Brescia, Via Branze 38, 25123, Brescia, Italy; m.abbatangelo@unibs.it, e.nunezcarmona@unibs.it, dario.zappa@unibs.it, elisabetta.comini@unibs.it, giorgio.sberveglieri@unibs.it CNR-IBBR, Institute of Biosciences and Bioresources, Via Madonna del Piano 10, 50019, Sesto Fiorentino (FI), Italy; veronica.sberveglieri@ibbr.cnr.it ?NANO SENSOR SYSTEMS srl, Via Branze 38, 25123, Brescia, Italy
Autori CNR e affiliazioni
  • VERONICA SBERVEGLIERI
Lingua/e
  • inglese
AbstractAbstract: Parmigiano Reggiano cheese is one of the most appreciated and consumed food 16 worldwide, especially in Italy, for its high content of nutrients and for its taste. However, these 17 characteristics make this product subject to counterfeiting in different forms. In this study, a novel 18 method based on an electronic nose has been developed in order to investigate the potentiality of 19 this tool to distinguish rind percentage in grated Parmigiano Reggiano packages that should be 20 lower than 18%. Different samples in terms of percentage, seasoning and rind working process were 21 considered to tackle the problem at 360°. In parallel, GC-MS technique was used to give a name to 22 the compounds that characterize Parmigiano and to relate them with sensors responses. Data 23 analysis consisted of two stages: multivariate analysis (PLS) and classification made in a hierarchical 24 way with PLS-DA ad ANNs. Results are promising in terms of correct classification of the samples. 25 The classification rate is higher for ANNs than PLS-DA, reaching also 100% values.
Lingua abstractinglese
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RivistaSensors (Basel)
Attiva dal 2001
Editore: Molecular Diversity Preservation International (MDPI), - Basel
Lingua: inglese
ISSN: 1424-8220
Titolo chiave: Sensors (Basel)
Titolo proprio: Sensors. (Basel)
Titolo abbreviato: Sensors (Basel)
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Verificato da refereeSì: Nazionale
Stato della pubblicazionePreprint
Indicizzazione (in banche dati controllate)-
Parole chiaveelectronic nose, nanowire gas sensors, food quality control, Parmigiano Reggiano, multivariate data analysis, artificial neural network
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Strutture CNR
  • IBBR — Istituto di Bioscienze e Biorisorse
Moduli/Attività/Sottoprogetti CNR-
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Allegati
Application of a novel S3 nanowire gas sensor device in parallel with GC-MS for the identification of rind percentage of grated Parmigiano Reggiano (documento privato )
Tipo documento: application/pdf