Quality evaluation for Ficus hirta Vahl granules, using TLC and HPLC fingerprint combined with chemical pattern recognition

Abstract

Ficus hirta Vahl is a healthy food with both medicinal and culinary properties and with anti-inflammatory and anti-aging effects. There is currently no standardized or universally accepted research strategy for evaluating the quality of Ficus hirta Vahl granules (FHGs). Therefore, the development of a comprehensive quality evaluation method is crucial for the quality control of FHGs. In this study, we used n-hexane : trichloromethane : ethyl acetate : glacial acetic acid = 20 : 4 : 7 : 1 as the optimal developing agent for TLC to separate and identify 15 batches of FHGs from different origins. Using HPLC, a fingerprint with 7 common peaks was established, and peaks 6 and 7 were attributed to psoralen and bergapten, respectively. The content of the identified components was determined. Further quality evaluation of FHGs was performed using chemical pattern recognition, and the results showed that hierarchical cluster analysis (HCA) could cluster 15 batches of FHGs into 2 categories. Principal component analysis (PCA) showed that 2 principal components can show the similarities and differences between different batches of FHGs. Orthogonal partial least squares discrimination (OPLS-DA) showed that components 5, 6 (psoralen) and 7 (bergapten) are landmark components that cause differences in FHG quality from different regions. By integrating the analytical modes of TLC, HPLC fingerprint and chemical pattern recognition, a scientific basis is provided for the comprehensive control and evaluation of herbal medicine quality.