基于主灵敏度矢量回归评价中药色谱指纹图谱  

Evaluation of chromatographic fingerprint of herbal medicine based on principal sensitivity vector regression

作　　者：杨锦瑜[1] 李博岩[1] 梁逸曾[1] 许青松[2] 谢培山[3] 

机构地区：[1]中南大学中药现代化研究中心,湖南长沙410083 [2]湖南大学数学与计量经济学院,湖南长沙410082 [3]广州市药品检验所,广东广州510160

出　　处：《计算机与应用化学》2005年第4期282-286,共5页Computers and Applied Chemistry

基　　金：国家自然科学基金重点资助项目(20235020;20175036)

摘　　要：基于主灵敏度矢量稳健主成分回归(RPPSV)和蒙特卡罗交互检验(MCCV)方法对29个不同来源的银杏提取物和33 个不同产地的灯盏花提取物的色谱指纹图谱进行质量评价,分别定性判断出银杏样本数据集中的7个异常样本和灯盏花样本数据集中的4个异常样本。与相关系数法相比,RPPSV具有更好的异常样本检测能力,但是两者评价指纹图谱的结果基本是一致的。Robust principal component regression based on principal sensitivity vectors (RPPSV) combined with Monte Carlo cross validation (MCCV) is developed to qualitatively evaluate quality of chromatographic fingerprints of 29 herbal samples extracted from Gink-go biloba from various sources and 33 Erigeron breviscapus herbal samples from different regions in this study. Beyond a given threshold, seven samples have been detected as 'outliers' from the data set of Ginkgo biloba and four 'outlier' samples from Erigeron breviscapus. Compared with correlation coefficient, RPPSV, which has a sound statistic background, seems to have a better ability to detect 'outliers'. Thus, the common patterns of different Chinese medicines could be better established after deleting the outliers detected by the proposed method. However, the evaluation results upon the fingerprints from both correlation coefficient and RPPSV are consistent with each other on the whole.

关 键 词：中药指纹图谱 主灵敏度矢量 稳健主成分回归 蒙特卡罗交互检验 

分 类 号：O657.4[理学—分析化学] O658.12[理学—化学]