Application of a novel S3 nanowire gas sensor device in parallel with GC-MS for the identification of rind percentage of grated Parmigiano Reggiano

Abstract: 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.