Publications by authors named "Alex Bedmar"
Tea is a broadly consumed beverage worldwide that is susceptible to fraudulent practices, including 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) fingerprinting 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.
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- - Tea is popular worldwide but faces issues of adulteration for profit, necessitating reliable methods to verify its authenticity and detect frauds in various tea types.
- - The study used advanced techniques like untargeted HPLC-UV and HPLC-FLD to assess different tea varieties and their potential adulteration with chicory, achieving high classification accuracy through partial least squares-discriminant analysis (PLS-DA).
- - Most tea samples were accurately classified with high prediction rates; however, some types, especially white tea, showed lower accuracy, highlighting the need for more diverse samples for better analysis.