Abstract
A method combining ultra-high-performance liquid chromatograph/quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and chemometrics was established to evaluate the differences in chemical composition between Aconiti Lateralis Radix (Fuzi in Chinese) before and after combination with Glycyrrhizae Radix et Rhizoma (Gancao in Chinese). UPLC-Q-TOF-MS was used to characterize the chemical components before and after the combination of Fuzi with Gancao, and genetic algorithm selection variables were applied to extract important variables. Partial least square discriminant analysis was used to verify the reliability of the variables obtained by genetic algorithm selection in differentiating Fuzi and combinations with Gancao, and nine potential chemical markers were obtained. The changes in content of chemical markers in Fuzi before and after combination were visualized using a heat map and hierarchical cluster analysis. Based on the chemical markers, characteristic profiling of UPLC-Q-TOF-MS data was developed, then unsupervised principal components analysis and a supervised counter-propagation artificial neural network were used to validate the characteristic profiling approach and showed that it performed well in differentiating between Fuzi and combinations with Gancao.
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