Utilizing Headspace-Gas Chromatography-Ion Mobility Spectroscopy Technology to Establish the Volatile Chemical Component Fingerprint Profiles of Processed by Different Preparation Methods and to Perform Differential Analysis of Their Components.

In order to characterize the volatile chemical components of processed by different Traditional Chinese Medicine Processing methods and establish fingerprint profiles, headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) technology was employed to detect, identify, and analyze processed by five different methods. Fingerprint profiles of volatile chemical components of processed by different methods were established; a total of 85 different volatile organic compounds (VOCs) were detected in the experiment, including esters, alcohols, ketones, aldehydes, terpenes, olefinic compounds, nitrogen compounds, lactones, pyrazines, sulfur compounds, thiophenes, acid, and thiazoles. Principal component analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), and Pearson correlation analysis methods were used to cluster and analyze the detected chemical substances and their contents. The analysis results showed significant differences in the volatile chemical components of processed by different methods; the Variable Importance in Projection () values of the OPLS-DA model and the values obtained from one-way ANOVA were used to score and screen the detected volatile chemical substances, resulting in the identification of five significant chemical substances with the highest values: Alpha-Farnesene, Methyl acetate,1-octene, Ethyl butanoate, and citral. These substances will serve as marker compounds for the identification of processed by different methods in the future.