High-throughput FIA-MS/MS and LC-MS/MS Polyphenolics for the Authentication of Teas adulterated with Chicory

Tea is one of the beverages that is more susceptible to fraudulent practices due to its high worldwide consumption and because of the increase in prices for some specific varieties due to climate change and instability in the world of geopolitics. Tea adulteration with other plants, including chicory, is a common practice that is carried out to gain an illicit profit. Polyphenols are the most abundant bioactive substances in tea, determining its quality and health function. In addition, they can be employed as secondary markers to address authentication issues. The present contribution evaluated the potential of polyphenolic profiling using high-throughput FIA-MS/MS and LC-MS/MS methodologies to assess tea authenticity. A total of 100 tea samples belonging to different varieties (green, black, red, oolong, and white teas), as well as 20 chicory samples, were analyzed with both methodologies after a simple tea brewing process, obtaining the corresponding polyphenolic profiles by monitoring 55 polyphenols belonging to different families. The corresponding profiles were then employed as sample chemical descriptors to address tea classification and authentication using partial least squares discriminant analysis (PLS-DA). An excellent classification performance was accomplished using PLS-DA, with sensitivity and specificity values being higher than 90% and 88.9%, respectively, for FIA-MS/MS, and higher than 85% and 86%, respectively, for LC-MS/MS. A good accuracy was also attained, with calibration errors below 10.5 and 14.5% for FIA-MS/MS and LC-MS/MS, respectively. Overall, FIA-MS/MS showed a better performance than LC-MS/MS, with the advantage of requiring a lower analysis time due to the fact that no chromatographic separation was necessary. The capability of the obtained polyphenolic profiles to detect and quantify tea adulterations with chicory was also assessed using partial least squares (PLS) regression, showing excellent adulterant level determination, with prediction errors below 10.9 and 14.8% for FIA-MS/MS and LC-MS/MS, respectively. Thus, both methodologies demonstrated feasibility in assessing tea authentication issues when adulterations with chicory are involved.