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作 者:李方飞 彭应枝[1,2] 许雄博 资文[1,2] 刘蕊[1,2] 刘韶[1,2]
机构地区:[1]中南大学湘雅医院药学部,湖南长沙410008 [2]中南大学药学院,湖南长沙410013
出 处:《光谱学与光谱分析》2016年第12期3945-3950,共6页Spectroscopy and Spectral Analysis
基 金:国家"十二五"科技支撑计划项目(2011BAI01B08)资助
摘 要:应用近红外光谱技术并结合化学计量学建立杜仲中松脂素二葡萄糖苷(PDG)和京尼平苷酸(GPA)含量测定模型。以积分球漫反射方式采集近红外光谱数据,应用一阶微分、多元散射校正(MSC)等优选光谱数据预处理方法和竞争自适应加权采样(CARS)筛选最优波长变量,采用偏最小二乘法(PLS)和交叉验证法建立PDG和GPA的定标模型。PDG和GPA的定标模型显示出良好的预测效果,其校正集的相关系数分别为0.961 5和0.958 3,交互验证均方差分别为0.001 5和0.006 4。表明此快速预测模型准确可靠,适合快速测定杜仲中的PDG和GPA,为杜仲质量控制在线化提供了新思路。To develop aquantitative models for simultaneous determination of pinoresinol diglucoside(PDG)and geniposidic acid(GPA)in Eucommia ulmoides with near-infrared(NIR)spectroscopy combined with chemometrics.The NIR spectra were collected in diffuse reflection mode and pretreated with various spectra preprocessing methods including first-order differentiator,multiplicative scatter correction and so on.The optimal wavelength variables were screened out by competition adaptive weighted sampling method.The quantitative models for the simultaneous determination of PDG and GPA in Eucommia ulmoides were established with partial least squares(PLS)algorithm and cross validation methods.The quantitative prediction models for simultaneous determination of PDG and GPA in Eucommia ulmoides showed good predictive ability.The correlation coefficients(R^2)of the two calibration models were 0.961 5,0.958 3while the roots mean square of cross-validation(RMSECV)were 0.001 5,0.006 4,respectively.The quantitative prediction models proved that near infrared spectra method used for the quantitative analysis of PDG and GPA in Eucommia ulmoides owned high prediction accuracy and can meet the precision need of rapid determinations of PDG and GPA in Eucommia ulmoides in reality so t it provides a new method to realize the real time on line of quality control of Eucommia ulmoides.
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