Uality evaluation of Astmgali Radix based on three-dimensional fluorescence spectroscopy with parallel factor analysis / 国际中医中药杂志

Objective:To establish the quality evaluation method of Astmgali Radix based on three-dimensional fluorescence spectroscopy. Methods:The three-dimensional fluorescence spectra of Astmgali Radix extract was measured by fluorescence spectrum analysis technology, and the characteristics of fluorescence components of three-dimensional fluorescence spectrum of Astmgali Radix were analyzed by parallel factor analysis. The three-dimensional fluorescence spectra of Astmgali Radix samples from 23 different places were measured for quality discriminant analysis. Results:After the optimization, the three-dimensional fluorescence spectrum of 80% ethanol extract of Astmgali Radix showed that three groups of characteristic excitation/emission (λex/λem) peak, which located at 305 nm/420 nm (Peak 1), 280 nm/315 nm (Peak 2) and 265 nm/475 nm (Peak 3), respectively. The results of parallel factor analysis showed that Peak 1 and Peak 3 both contained one isoflavones fluorescent component, and Peak 2 contained two amino acid fluorescent components. There were differences in the number of characteristic peaks and fluorescence intensity of three-dimensional fluorescence spectra of Astmgali Radix samples from different origins. Conclusion:The three-dimensional fluorescence spectrum could evaluate the consistency of Astmgali Radix from different places. The method is simple, fast, and efficient. This method is accurate, which could provide reference for the quality evaluation of Astmgali Radix.

Research on optimal modeling strategy for licorice extraction process based on near-infrared spectroscopy technology / 中国中药杂志

The manufacture of traditional Chinese medicine (TCM) products is always accompanied by processing complex raw materials and real-time monitoring of the manufacturing process. In this study, we investigated different modeling strategies for the extraction process of licorice. Near-infrared spectra associate with the extraction time was used to detemine the states of the extraction processes. Three modeling approaches, i.e., principal component analysis (PCA), partial least squares regression (PLSR) and parallel factor analysis-PLSR (PARAFAC-PLSR), were adopted for the prediction of the real-time status of the process. The overall results indicated that PCA, PLSR and PARAFAC-PLSR can effectively detect the errors in the extraction procedure and predict the process trajectories, which has important significance for the monitoring and controlling of the extraction processes.