[Study on the Chinese medicinal Qingkailing injections intermediate by support vector machines and ultraviolet spectrometry].
The first derivative and wavelet compression methods were used to eliminate the slope-background and reduce variables for the measured ultraviolet (UV) spectra of Chinese medicinal Qingkailing injections intermediate. Then, support vector machine (SVM) was used for building the classification model to discriminate qualified and unqualified samples. The effects of spectral preprocessing and model parameters were investigated. Under optimized conditions, correct classifications of 100%, 95.4%, 97.3%, and 100% were obtained for the four batches of the intermediate of Qingkailing injection samples, respectively. A percentage of 97.3% of the intermediate samples were correctly classified for all the four batches of mixture samples. Results showed that SVM technique can be a useful means for quality control of Chinese medicinal injections owing to its good accuracy and better generalization.
Department of Chemistry, Capital Normal University, Beijing 100037, China.
Xiang-Rong
XR
Zhu
Na
N
Li
Xin-Yuan
XY
Shi
Yan-Jiang
YJ
Qiao
Zhuo-Yong
ZY
Zhang
D004365:Drugs, Chinese Herbal / Q000032:analysis* / Q000592:standards; D001330:Electronic Data Processing; D007267:Injections; D011786:Quality Control; D013056:Spectrophotometry, Ultraviolet / Q000379:methods*
D004365:Drugs, Chinese Herbal; C504928:Qingkailing