A High Performance Liquid Chromatography and Electrospray Ionization Mass Spectrometry Method for the Analysis of the Natural Medicine, Forsythia Suspensa

Abstract

Samples of Forsythia suspensa from raw (Laoqiao) and ripe (Qingqiao) fruit were analyzed with the use of HPLC-DAD and the EIS-MS techniques. Seventeen peaks were detected, and of these, twelve were identified. Most were related to the glucopyranoside molecular fragment. Samples collected from three geographical areas (Shanxi, Henan and Shandong Provinces), were discriminated with the use of hierarchical clustering analysis (HCA), discriminant analysis (DA), and principal component analysis (PCA) models, but only PCA was able to provide further information about the relationships between objects and loadings; eight peaks were related to the provinces of sample origin. The supervised classification models-K-nearest neighbor (KNN), least squares support vector machines (LS-SVM), and counter propagation artificial neural network (CP-ANN) methods, indicated successful classification but KNN produced 100% classification rate. Thus, the fruit were discriminated on the basis of their places of origin.

Keywords:

• Classification
• Forsythia suspensa (Thunb.) Vahl
• Fingerprints
• Geographical origin
• High performance liquid chromatography
• Ionization mass spectrometry

Acknowledgments

The authors greatly appreciate the financial support from the Natural Science Foundation of China (NSFC-21065007) and the State Key Laboratory of Food Science and Technology of Nanchang University (SKLF-ZZA-201302 and SKLF-ZZB-201303).

Notes

^a K = 1.

^b Parameters of [log(γ), log(σ ²)] = (3.38, 0.31).

^c Numbers in brackets are the misclassified samples.