近红外光谱法快速测定白芍中芍药苷含量  

Rapid Determination of Paeoniflorin in Paeoniae Radix Alba by Near-Infrared Spectroscopy

作　　者：白雁[1] 李小庆[1] 雷敬卫[1] 

机构地区：[1]河南中医学院,郑州450046

出　　处：《天然产物研究与开发》2013年第3期358-362,共5页Natural Product Research and Development

基　　金：河南省教育厅科技攻关项目(2008A360016);河南省重大公益科研项目(081100912500)

摘　　要：本研究旨在应用近红外光谱法建立一种白芍药材中芍药苷含量的快速测定方法。利用HPLC测定样品中芍药苷含量,并以其作为参考值,运用偏最小二乘法(PLS)建立芍药苷含量与近红外光谱之间的多元校正模型,对未知样品进行含量预测。结果表明,所建芍药苷定量分析模型的相关系数(R2)、内部交叉验证均方差(RMSECV)、校正均方差(RMSEC)分别为0.99395、0.33068、0.0563;经内部验证,模型的预测均方差(RMSEP)和平均回收率分别为0.0756和100.07%。该方法操作简便,无污染,结果准确可靠,可用于白芍中芍药苷含量的快速测定。The objective of the present study was to establish an analytical method for the rapid determination of paeoniflorin in Paeoniae Radix Alba by near-infrared spectroscopy. The near-infrared spectral data of 106 samples was collected by Nicolet 6700 NIR spectroradiometer and the data of the concentrations of paeoniflorin were obtained by HPLC. A multivar/ate calibration model was then developed by partical least square （PLS） analysis using HPLC analytical data as reference. The developed model was used to predict the concentration of paeoniflorin in unknown samples. The results showed that the correlation coefficients （R^2 ） of the developed calibration model was 0.99395 ; the root-mean-square error of cross-validation （RMSECV） was 0. 33068 ; the root-mean-square error of calibration （RMSEC） was 0. 0563, the root-mean-square error of prediction （RMSEP） and the average rate of recovery were 0.0756 and 100.07%. The method was simple,non-polluted and accurate. It can be applied for the fast determination of large quantifies of samples.

关 键 词：近红外光谱法 偏最小二乘法 白芍 芍药苷 快速测定 

分 类 号：R284.2[医药卫生—中药学]