Authentication of the production season of Xinyang Maojian green tea using two-dimensional fingerprints coupled with chemometric multivariate calibration and pattern recognition analysis
Xiaohua Zhang, Renjun Liu, Jingjing Zheng, Xiang-Dong Qing, Kai-Long Yang, Yaqian Zhang, Le-Yuan Pan, Jin-Fang Nie
Abstract
This study aimed to authenticate the production season of Xinyang Maojian green tea, and screen and identify its characteristic components through non-targeted metabonomics methods based on two-dimensional fingerprints combined with chemometric analysis. Firstly, two-dimensional fingerprints of spring and autumn teas were obtained through HPLC-DAD analysis to form a three-dimensional array (retention time × absorption wavelength × sample). Subsequently, the multiple co-elution peaks and spectral profiles in two-dimensional HPLC-DAD fingerprints were resolved by using alternating trilinear decomposition assisted multivariate curve resolution (ATLD-MCR) algorithm. We obtained the relative concentration matrix C (24 × 122), which was further used to distinguish the production season of Xinyang Maojian green tea through chemometric pattern recognition analysis. The evaluation results of both orthogonal partial least squares-discriminant analysis (OPLS-DA) and partial least squares-discriminant analysis (PLS-DA) models were better than those of PCA models, and could effectively distinguish the production season of Xinyang Maojian green teas. Moreover, 5 variables were selected through VIP method to build new UV-scaling and Par-scaling OPLS-DA models. In conclusion, the following characteristic components were identified in accordance with the analytical standards and published data: gallocatechin (GC), theobromine (THB), epigallocatechin gallate (EGCG), gallocatechin gallate (GCG), and epicatechin gallate (ECG).