dc.contributor.author
Romers, Thom
dc.contributor.author
Saurina, Javier
dc.contributor.author
Sentellas, Sonia
dc.contributor.author
Núñez Burcio, Oscar
dc.date.issued
2023-06-08T16:51:29Z
dc.date.issued
2023-06-08T16:51:29Z
dc.date.issued
2023-06-08T16:51:29Z
dc.identifier
https://hdl.handle.net/2445/198964
dc.description.abstract
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.
dc.format
application/pdf
dc.relation
Reproducció del document publicat a: https://doi.org/10.3390/foods12071501
dc.relation
Foods, 2023, vol. 12, num. 7, p. 1-12
dc.relation
https://doi.org/10.3390/foods12071501
dc.rights
cc-by (c) Romers, Thom et al., 2023
dc.rights
https://creativecommons.org/licenses/by/4.0/
dc.rights
info:eu-repo/semantics/openAccess
dc.source
Articles publicats en revistes (Enginyeria Química i Química Analítica)
dc.title
Targeted HPLC-UV Polyphenolic profiling to detect and quantify adulterated tea samples by chemometrics
dc.type
info:eu-repo/semantics/article
dc.type
info:eu-repo/semantics/publishedVersion