Quality Difference Analysis of Pomegranate Peels Based on Multidimensional Fingerprint With Chemical Pattern Recognition

To evaluate the quality of pomegranate peels from different cultivars, pomegranate peel samples from 47 cultivars were compared and classified based on fingerprints and chemical components obtained using HPLC-PDA-MS/MS combined with chemometric methods. Three pattern recognition methods, namely, hierarchical cluster analysis, principal component analysis, and partial least square–discriminant analysis, were used to establish classification models. Results showed that the contents of 10 components from pomegranate peel were determined. A total of 21 liquid chromatographic characteristic peaks and 26 mass spectra characteristic peaks were obtained from HPLC-PDA-MS/MS fingerprint analysis. Pomegranate peel samples from 47 cultivars were divided into three groups, and four and three chemical markers were labeled with identification based on HPLC and MS/MS models, respectively. In conclusion, this study firstly establishes an adequate method for quantitative profiling across multiple active ingredients for quality assessment and prediction of pomegranate peels of a specific cultivar set from different production areas and provides novel ideas for the research of Traditional Chinese Medicine.