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Title: | High-throughput Flow Injection Analysis-Mass Spectrometry (FIA-MS) Fingerprinting for the Authentication of Tea. Application to the Detection of Teas Adulterated with Chicory. |
Author: | Vilà Romeu, Mònica Bedmar Chamarro, Àlex Saurina, Javier Núñez Burcio, Oscar Sentellas, Sonia |
Keywords: | Te Quimiometria Espectrometria de masses Tea Chemometrics Mass spectrometry |
Issue Date: | 2022 |
Publisher: | MDPI |
Abstract: | 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. |
Note: | Reproducció del document publicat a: https://doi.org/10.3390/foods11142153 |
It is part of: | Foods, 2022, vol. 11, num. 2153 |
URI: | http://hdl.handle.net/2445/189617 |
Related resource: | https://doi.org/10.3390/foods11142153 |
ISSN: | 2304-8158 |
Appears in Collections: | Articles publicats en revistes (Institut de Recerca en Nutrició i Seguretat Alimentària (INSA·UB)) Articles publicats en revistes (Enginyeria Química i Química Analítica) |
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