Geographical origin identification and chemical markers screening of Chinese green tea using two-dimensional fingerprints technique coupled with multivariate chemometric methods

Identifying the geographical origins of green teas produced in specific regions is of significance since the geographical origin of tea influences its quality and price greatly. In this work, a novel two-dimensional (2D) fingerprints acquired by high-performance liquid chromatography-diode array detector (HPLC-DAD) was firstly proposed to identify geographical origins of Chinese green teas. A total number of 62 chemical components were extracted from 2D HPLC-DAD fingerprints of 78 tea samples by multivariate curve resolution-alternating least squares (MCR-ALS) algorithm. Afterward, principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to classify tea samples based on the extracted components. Inspection of PCA score plots of two scaling types (UV and Par) showed that tea samples from two different geographical origins have an obvious clustering tendency. As for the OPLS-DA analysis, the Q2cum of two typesscaling OPLS-DA models are greater than 0.75, and the total recognition rates for test set are 92.86%. What's more, according to p value of t-test, VIP values, V-plot and S-plot, 17 characteristic components were screened and identified as chemical markers to distinguish between Zhejiang teas and Shandong teas. This work indicated that the proposed strategy is suitable for identifying geographical origins of Chinese green teas.

Automated summary

This study proposes a novel two-dimensional fingerprinting method using HPLC-DAD to identify the geographical origins of Chinese green teas. Through multivariate curve resolution and orthogonal partial least squares-discriminant analysis, characteristic components were identified as chemical markers to distinguish between different tea origins.