摘要
建立高良姜药材中高良姜索含量的近红外光谱定量分析模型,实现药材中高良姜素的含量的快速测定方法,采用高效液相色谱法测定130批药材中高良姜素的含量,采集近红外光谱数据并用多元散射校正法、二阶导数法、Savitzky-Golay平滑法预处理,结合偏最小二乘法建立高良姜中高良姜素含量的定量分析模型,对所建模型进行了内部交叉验证和外部预测验证,并对模型进行了重复性考察。对于所建立的高良姜素近红外光谱定量分析模型,内部交叉验证决定系数达到0.9868,校正均方差为0.0529,预测均方差为0.0625,内部交叉验证均方差为0.0975,交叉检验和外部检验RPD均大于3。表明该模型稳定、准确可靠,可应用于高良姜中高良姜素的含量测定。
In order to develop a method for the determination of galangin content in Alpiniae Officinarum Rhizoma by nearinfrared reflectance spectroscopy （NIRS）, the galangin contents of 130 samples were determined by the method of HPLC. NIR spectrum were measured while the multiplicative signal correetlon, second derivative and Savizky-Golay filter method were used as spectral preprocessing options, and calibrationmodel of the galangin content was established by the partial least squares regression analysis. The models were verified by internal cross validation and external predictive validation. The model＇s repeatability was inspected. As a result, the correlation coefficients, the root-mean-square error of calibration, the root-mean-square error of prediction and the root-mean-square error of cross-validation of the calibration model for galangin content were 0.98682, 0.0529, 0.0625 and 0.09746. The RPD values of cross-validation and prediction were all above 3. So this method is steady, accurate, and can be used to predict galangin content in Alpiniae of cinarum Rhizoma rapidly.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2014年第5期632-636,共5页
Computers and Applied Chemistry
基金
广东省科技计划项目(2009B030801044)
