AbstractDuring the process of fermentation, the chemical compositions of trifoliate orange (Poncirus trifoliate (L). Raf) changed greatly. To provide a completely phytochemical profile, high-performance liquid chromatography-diode array detector-hyphenated with tandem mass spectrometry (HPLC–DAD–ESI-MS/MS) has been successfully applied to screen and identify the unknown constituents of trifoliate orange during fermentation, which make it available for the quality control of fermented products. Multivariate statistical analysis was performed to classify the trifoliate oranges based on the status of fermentation. A total of 8 components were identified among the samples. Hierarchical Clustering Analysis (HCA) and Principal Component Analysis (PCA) demonstrated the fermented and unfermented trifoliate oranges were obviously different, an effective and reliable Partial Least Square Discriminate Analysis (PLS-DA) technique was more suitable to provide accurate discrimination of test samples based their different chemical patterns. Furthermore, a permutation validated the reliability of PLS-DA and variable importance plot revealed that the characterized syringing, naringin, and poncirin showed the high ability to distinguish the trifoliate oranges during fermentation. The present investigation could provide detailed information for the quality control and evaluation of trifoliate oranges during the fermentation process.
Phytochemical analysis of trifoliate orange during fermentation by HPLC–DAD–ESI–MS/MS coupled with multivariate statistical analysis
