摘要
目的:利用黄芩提取物样品的近红外漫反射光谱(NIRS)信息,建立能够快速分析其3种有效成分含量的校正模型。方法:共收集12个不同厂家的100批样品,其中80批样品作为校正集,20批样品作为验证集,结合偏最小二乘法(PLS),建立了黄芩提取物中黄芩苷、黄芩素和汉黄芩素3种有效成分的近红外定量校正模型。结果:3个校正模型的建模效果均较好,交叉检验决定系数(R2CV)分别为0.994 8,0.998 7,0.994 8,校正均方差(RMSEC)分别为0.440,0.022 5,0.011 1,交互验证均方差(RMSECV)分别为2.259,0.055 3,0.048 3。用验证样品进行外部验证,预测相关系数(r2)分别为0.998 2,0.996 5,0.990 9,预测均方差(RMSEP)分别为0.486,0.027 1,0.011 0。结论:结果表明,近红外光谱技术可对黄芩提取物中黄芩苷、黄芩素和汉黄芩素含量进行简便、快速、准确分析。
Objective：To rapidly analyse the three active components in Scutellaria extract by establishing calibration models with near-infrared reflectance spectroscopy（NIRS）.Method： One hundred batches of Scutellaria extract samples from 12 different pharmaceutical factories were collected and they were divided into a calibration set（80 samples） and a validation set（20 samples）.In combination with the partical least square（PLS）,the quantitative calibration models were established for baicalin,baicalein and wogonin.Result： All models had great calibration performance.The correlation coefficients of cross-validation（R2cv） were 0.994 8,0.998 7 and 0.994 8,the root-mean-square error of calibration（RMSEC） were 0.440,0.022 5 and 0.011 1,the root-mean-square error of cross-validation（RMSECV） were 2.259,0.055 3 and 0.048 3.The rest 20 samples were used to evaluate the performances of the models,the correlation coefficients of prediction（r2） were 0.988 2,0.996 5 and 0.990 9 and the root-mean-square error of prediction（RMSEP） were 0.486,0.027 1 and 0.011 0.Conclusion： The results indicated that the NIRS was simply;rapidly and exactly method for analysis of baicalin;baicalein and wogonin contents in Scutellaria extract.
出处
《中国实验方剂学杂志》
CAS
北大核心
2012年第7期84-87,共4页
Chinese Journal of Experimental Traditional Medical Formulae
基金
河南省重大公益科研项目(081100912500)
河南省杰出人才项目(084200510017)
关键词
近红外光谱
偏最小二乘法
校正模型
黄芩提取物
near-infrared spectroscope
partical least square
calibration model
scutellaria extract
