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urn:hdl:2445/189617 High-throughput Flow Injection Analysis-Mass Spectrometry (FIA-MS) Fingerprinting for the Authentication of Tea. Application to the Detection of Teas Adulterated with Chicory. Vilà Romeu, Mònica Bedmar Chamarro, Àlex Saurina, Javier Núñez Burcio, Oscar Sentellas, Sonia Te Quimiometria Espectrometria de masses Tea Chemometrics Mass spectrometry Tea is a broadly consumed beverage worldwide that is susceptible to fraudulent practices, in-cluding its adulteration with other plants such as chicory extracts. In the present work, a non-targeted high-throughput flow injection analysis-mass spectrometry (FIA-MS) fingerprint-ing methodology was employed to characterize and classify different varieties of tea (black, green, red, oolong, and white) and chicory extracts by principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Detection and quantitation of frauds in black and green tea extracts adulterated with chicory were also evaluated as proofs of concept using partial least squares (PLS) regression. Overall, PLS-DA showed that FIA-MS fingerprints in both negative and positive ionization modes were excellent sample chemical descriptors to dis-criminate tea samples from chicory independently of the tea product variety, as well as to clas-sify and discriminate among some of the analyzed tea groups. The classification rate was 100% in all the paired cases ¿i.e., each tea product variety versus chicory¿ by PLS-DA calibration and prediction models showing their capability to assess tea authentication. The results obtained for chicory adulteration detection and quantitation using PLS were satisfactory in the two adultera-tion cases evaluated (green and black teas adulterated with chicory), with calibration, cross-validation, and prediction errors bellow 5.8%, 8.5%, and 16.4%, respectively. Thus, the non-targeted FIA-MS fingerprinting methodology demonstrated to be a high-throughput, cost-effective, simple, and reliable approach to assess tea authentication issues. 2022-10-05T15:05:08Z 2022-10-05T15:05:08Z 2022 2022-10-05T15:05:08Z info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Reproducció del document publicat a: https://doi.org/10.3390/foods11142153 Foods, 2022, vol. 11, num. 2153 https://doi.org/10.3390/foods11142153 cc-by (c) Vilà Romeu, Mònica et al., 2022 https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess MDPI Articles publicats en revistes (Enginyeria Química i Química Analítica)