Identification of lu'an Guapian at different picking periods by using excitation-emission matrix fluorescence spectroscopy coupled with chemometrics.

Lu'an Guapian (LAGP) is a renowned green tea, with its price significantly higher when picked before the Qingming Festival compared to after, posing risks of confusion and counterfeiting. This study proposed using an excitation-emission matrix (EEM) fluorescence method combined with chemometrics for rapid identification of tea picked before and after Qingming Festival. Firstly, the differences among the EEM fingerprints of different tea samples were analyzed using the alternating trilinear decomposition (ATLD) algorithm. To determine the differences between LAGP before and after Qingming Festival, the total contents of ten main components in tea were detected, and their effects on the EEM fluorescence fingerprint of tea were analyzed using correlation heatmaps. Finally, two chemometric algorithms, partial least squares discriminant analysis (PLS-DA) and k-nearest neighbor (k-NN), were used to classify LAGP before and after Qingming Festival, achieving a classification accuracy of 100% for the training set, test set, and prediction set. To further explore the potential of this method, LAGP was further classified in detail according to four detailed picking periods, achieving an accuracy of over 83%. The same chemometric algorithm was used to classify the data based on the high-performance liquid chromatography (HPLC) method, yielding results comparable to those of the EEM-based method, though slightly inferior. Variable importance projection (VIP) analysis shows that catechin analogs are the main contributors to the classification of LAGP. The results demonstrated the EEM method's significant potential in identifying the picking time of green tea.