近红外光谱法快速测定乳块消糖衣片的包衣厚度  

Fast determination of coating thickness of Rukuaixiao tablets' by NIRS

作　　者：刘冰[1] 陈晓辉[1] 史新元[2] 孙立新[1] 毕开顺[1] 乔延江[2] 

机构地区：[1]沈阳药科大学,沈阳110016 [2]北京中医药大学中药学院,北京100102

出　　处：《药物分析杂志》2009年第9期1435-1439,共5页Chinese Journal of Pharmaceutical Analysis

基　　金：北京市科技计划课题资助课题(D02050040040111);北京市"中药基础与新药研究重点实验室"资助课题

摘　　要：目的:利用近红外光谱分析技术,建立乳块消糖衣片包衣厚度快速、无损测定方法。方法:采用Kennard-Stone法对校正集样本和验证集样本进行分类,比较不同的建模方法,并对光谱的预处理方法、建模波段、主因子数的选择进行详细地讨论。结果:采用偏最小二乘回归方法(PLSR)建立包衣厚度的近红外光谱定量分析校正模型。所建模型的相关系数R=0.9961,校正误差均方根(RMSEC)为0.0149,预测误差均方根(RMSEP)为0.0194。结论:预测结果表明,本文所建方法快速、无损、可靠,可推广应用于中药生产包衣过程的在线检测。Objective：Near infrared spectroscopy（NIRS） analytical technique is used for establishing a rapid and nondestructive method to determine coating thickness of Rukuaixiao tablets. Methods： Calibration and validation sets were partitioned by Kennard-Stone algorithm. Different calibration methods were compared with other method. spectral pretreating methods, wavenumber selection and factors of NIRS were discussed in detail. Results：Partial least squares regression （PLSR） was used for building the quantitative calibration model. Correlation coefficients （R）, root mean square error of calibration（ RMSEC）, and root mean square error of prediction（RMSEP） obtained by PLSR model were 0. 9961,0. 0149 and 0. 0194 respectively. Conclusion：The predictive result shows that the method of this study is rapid, non-destructive and credible, which can be applied to the on-line monitor of Chinese medicine tablets＇ coating process.

关 键 词：近红外光谱 乳块消片 包衣厚度 Kennard-Stone法 偏最小二乘回归方法 在线检测 

分 类 号：R917[医药卫生—药物分析学]