Application of Data Mining on HPLC Fingerprints of Szechwan Lovage Rhizome Analysis

Abstract

Based on the integration of Java language and open-source R software environment, the article was developed a Traditional Chinese Medicine fingerprints analysis and visualization system and taken Szechwan Lovage Rhizome HPLC fingerprints as the study object to conduct data processing, information analyzing, and data mining research. In the article, 24 batches of Szechwan Lovage Rhizome from three different growth regions together with 3 standard samples were selected to make experiment detection. Data from HPLC fingerprints were processed by principal component analysis (PCA), and were completed the regional difference analysis for the main active components of the medicine from the different growth regions, and then with 3D visualization of the result, the growth regions were significantly distinguished from system. In addition, embedded with the GIS technology, the system was initially accomplished the correlation analysis between the Szechwan Lovage Rhizome fingerprints data and the geographical space data. Therefore the fingerprints data quantitative analysis method and system developed here can be regarded as an efficient way for quality detection and analysis automatically and intelligently of the traditional Chinese medicine.