Headspace solid-phase microextraction (HS-SPME) coupled with mass spectrometry-based electronic nose (MS-eNose), in combination with multivariate statistical analysis was used as untargeted method for the rapid authentication of 100% Italian durum wheat pasta. Among the tested classification models, i.e. PCA-LDA, PLS-DA and SVMc, SVMc provided the highest accuracy results in both calibration (90%) and validation (92%) processes. Potential markers discriminating pasta samples were identified by HS-SPME/GC-MS analysis. Specifically, the content of a pattern of 8 out of 59 volatile organic compounds (VOCs) was significantly different between samples of 100% Italian durum wheat pasta and pasta produced with durum wheat of different origins, most of which were related to different lipidic oxidation in the two classes of pasta. The proposed MS-eNose method is a rapid and reliable tool to be used for authenticating Italian pasta useful to promote its typicity and preserving consumers from fraudulent practices.
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| http://dx.doi.org/10.1016/j.foodchem.2022.132548 | DOI Listing |
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