Comparative Study of Several Pattern Recognition Methods in the Identification of Volatile Oils of Tradition-al Chinese Medicine by Infrared Spectroscopy
10.6039/j.issn.1001-0408.2015.21.38
- VernacularTitle:几种模式识别方法用于中药挥发油红外光谱法鉴别的比较研究Δ
- Author:
Xinhua QIU
;
Tiexin TANG
;
Yan LIU
;
Meizhu WU
;
Xiongsi TAN
;
Kelin GAN
;
Weisheng YAO
- Publication Type:Journal Article
- Keywords:
Traditional Chinese medicine;
Volatile oils;
Infrared spectroscopy;
Pattern recognition;
Chemometric fingerprinting
- From:
China Pharmacy
2015;(21):2986-2988
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To compare the performance of several pattern recognition methods in the identification of volatile oils of traditional Chinese medicine(TCM)by infrared spectroscopy. METHODS:The volatile oils of several Lonicera and Citrus TCM were determined by infrared spectroscopy. All samples of infrared spectrum were classified by hierarchical clustering,K-mean clustering,artificial neural networks,and support vector machine. RESULTS:The results of hierarchical clustering and K-mean clus-tering were ineffective. Methods of artificial neural networks and support vector machine achieved correct classification rate of 100%. CONCLUSIONS:Artificial neural networks and support vector machine can be combined with infrared spectroscopy to cre-ate chemometric fingerprinting for the identification of volatile oils of TCM.
