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近红外漫反射光谱法快速测定当归中阿魏酸及亚油酸     被引量:10

Rapid Determination of Ferulic Acid and Linolic Acid in Angelica sinensis by Near-Infrared Diffuse Reflectance Spectroscopy

文献类型:期刊文献

中文题名:近红外漫反射光谱法快速测定当归中阿魏酸及亚油酸

英文题名:Rapid Determination of Ferulic Acid and Linolic Acid in Angelica sinensis by Near-Infrared Diffuse Reflectance Spectroscopy

作者:顾志荣[1,2];张亚亚[2];丁军霞[2];王亚丽[1,2];孙宇靖[1,2]

第一作者:顾志荣

机构:[1]甘肃中医学院科研实验中心;[2]甘肃中医学院当归研究所

第一机构:甘肃中医药大学科研实验中心(甘肃省中医药标准化技术委员会秘书处)

年份:2015

卷号:27

期号:5

起止页码:849

中文期刊名:天然产物研究与开发

外文期刊名:Natural Product Research and Development

收录:CSTPCD;;北大核心:【北大核心2014】;CSCD:【CSCD2015_2016】;

基金:国家自然科学基金(30960037);甘肃省发改委战略新兴产业和产业技术研究与开发专项(2011)

语种:中文

中文关键词:当归;近红外漫反射光谱;定量模型;阿魏酸;亚油酸

外文关键词:Angelica sinensis ;near-infrared diffuse reflectance spectroscopy; quantitative model; ferulic acid ;linolic acid

摘要:以反相高效液相色谱法(RP-HPLC)测定的当归中阿魏酸及亚油酸含量作为参考值,利用TQ Analyst 8.0软件的偏最小二乘法(PLS)建立了快速、准确测定当归中阿魏酸及亚油酸含量的定量模型。结果表明,阿魏酸校正集的相关系数(R)为0.9721,校正均方差(RMSEC)为0.5942,预测均方差(RMSEP)为0.6747。亚油酸校正集的相关系数为0.9673,校正均方差为0.4573,预测均方差为1.0682。验证集中阿魏酸及亚油酸的平均预测回收率分别为101.98%和102.03%。该方法操作简单、快速,所建模型预测结果准确、可靠,可用于中药当归中阿魏酸及亚油酸的含量测定。
The NIR spectra of 145 batches of Angelica sinensis were collected by near-infrared diffuse reflectance spectroscopy. With the contents of ferulic acid and linolic acid determined by RP-HPLC as reference,the PLS( partial least squares) quantitative analysis model was established by TQ Analyst 8. 0 software to rapidly and accurately determine the contents of ferulic acid and linolic acid in A. sinensis. The correlation coefficient,RMSEC( the root-mean-square error of calibration) and RMSEP( the root-mean-square error of prediction) of ferulic acid of the calibration set reached 0.9721,0. 5942 and 0. 6747,respectively. The correlation coefficient,RMSEC and RMSEP of linolic acid of the calibration set reached 0. 9673,0. 4573 and 1. 0682,respectively. The average recoveries of ferulic acid and linolic acid of validation set were 101. 98% and 102. 03%,respectively. The established method was simple and rapid to operate,and the result by the prediction model was accurate and reliable. Hence,it can be routinely used for the content determination of ferulic acid and linolic acid in A. sinensis.

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