ABSTRACT
Objective: To study the quality of Eucommiae Cortex from different resources using flow injection mass spectrometric fingerprinting (FIMS) method combined with chemical pattern recognition approaches. Methods: Different Eucommiae Cortex samples were extracted in a simple way and were directly injected into the mass spectrometer for the analyses with no column used. Based on the intensities of the ions at m/z 100-1000, principal components analysis and partial least square discrimination analysis were performed using Simca-P software. Results: Eucommiae Cortex samples from different resources were classified into four clusters in scores plot, and the biomarkers which played the most important roles in classification were screened out. Conclusion: As a novel and characteristic fingerprinting method, FIMS can be widely and efficiently used in true or false identification, identification of origins, and rapid discrimination of herbs from different regions.