Abstract
A method based on high performance liquid chromatography with photodiode array detector (HPLC-DAD) was developed for chemical fingerprinting analysis of Herba Ephedrae. The index of chromatographic fingerprint's information content was utilized to optimize the fingerprint detection conditions, which reduced the time of analysis and increased the veracity of analysis greatly. Then, the similarity analysis of fingerprints was used in quality consistency evaluation of Herba Ephedrae samples. Moreover, hierarchical clustering analysis (HCA) was applied to classify the samples according to their sources and varieties. In addition, the overlapped chromatographic peaks were resolved with the help of heuristic evolving latent projection (HELP) method in order to gain the better quantitative evaluation. The results indicated that the samples could be successfully grouped in accordance with their varieties and sources. Furthermore, five marker constituents were firstly screened out to be the main chemical markers, which importantly contribute to the classification of Herba Ephedrae samples. This investigation shows that the developed methodology can be generalized to the research of quality control of herbal medicines.
Abbreviations:
- HPLC-DAD, High performance liquid chromatography with photodiode array detector
- hierarchical clustering analysis, HCA
- principal components analysis, PCA
- SA, similarity analysis
- TCMs, Traditional Chinese medicines
- HMs, herbal medicines
- CASE, Computer Aided Similarity Evaluation
- RSD, relative standard deviation
- RT, retention time
- PA, peak area
- SD, standard deviation
- HELP, heuristic evolving latent projection
Acknowledgments
This article is supported financially by the National Nature Foundation Committee of P.R. China (Grants No. 20875104 and No. 21075138), the International Cooperation Project on Traditional Chinese Medicines of Ministry of Science and Technology of China (Grant No. 2007DFA40680).