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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/198964
Targeted HPLC-UV Polyphenolic profiling to detect and quantify adulterated tea samples by chemometrics
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Tea can be found among the most widely consumed beverages, but also highly susceptible of fraudulent practices by adulteration, with other plants such as chicory, to obtain an illicit economic gain. The development of simple, feasible and cheap analytical methodologies to assess tea authentication is therefore required. In this work, a targeted high-performance liquid chromatography with ultraviolet-visible detection (HPLC-UV) method for polyphenolic profiling, monitoring 17 polyphenolic and phenolic acids typically described in tea, was proposed for the classification and authentication of tea samples versus chicory. For that purpose, the obtained HPLC-UV polyphenolic profiles (based on the peak areas at three different acquisition wavelengths) were employed as sample chemical descriptors for principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) studies. Overall, PLS-DA showed a good sample grouping and discrimination of chicory against any tea variety, but also among the five different tea varieties under study (black, green, red, oolong, and white teas), with classification errors below 8% and 10.5% for calibration and cross-validation, respectively. In addition, the potential use of polyphenolic profiles as chemical descriptors for the detection and quantitation of frauds was evaluated by studying the adulteration of each tea variety with chicory, as well as the adulteration of red tea extracts with oolong tea extracts. Very satisfactory results were obtained in all cases, with calibration, cross-validation, and prediction errors below 2.0%, 4.2%, and 3.9%, respectively, when using chicory as an adulterant, clearly improving previously reported results when using non-targeted HPLC-UV fingerprinting methodologies.
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ROMERS, Thom, et al. Targeted HPLC-UV Polyphenolic profiling to detect and quantify adulterated tea samples by chemometrics. Foods. 2023. Vol. 12, num. 7, pags. 1-12. ISSN 2304-8158. [consulted: 8 of August of 2026]. Available at: https://hdl.handle.net/2445/198964