贝母混合品中川贝母含量近红外光谱检测方法优化

Optimization of near infrared spectroscopy detection method for fritillaria cirrhosa content in fritillaria mixture

关键词:  近红外光谱  贝母  正交试验  参数优化  偏最小二乘回归

Key words:  near infrared spectroscopy  fritillaria  orthogonal test  parameter optimization  partial least squares regression

摘要:

近红外光谱技术用于中药材贝母混合品中川贝母含量的检测结果容易受到采集条件的影响。本研究提出应用正交实验设计优化贝母近红外检测条件，如粒径大小、扫描次数、分辨率和增益4个参数。实验获得9不同水平参数组合下的109例贝母样品近红外光谱，并结合偏最小二乘建立定量模型。采用决定系数（R²）、预测均方根误差（RMSEP）以及F值对模型进行评价。实验结果发现，扫描次数对模型精度影响最大，粒径大小次之，其次为分辨率和增益。并且当贝母粉末过120目筛，扫描次数为64，分辨率为8，增益为8时，模型预测性能最优。实验结果表明，4个参数均会给贝母检测结果带来影响，正交实验设计能够为贝母粉末样品近红外光谱质量检测参数优化提供参考。

Abstract:

Near-infrared spectroscopy (NIR) is used to detect the content of fritillaria cirrhosa in Chinese medicinal, which is easily affected by the collection conditions. The research proposes the application of orthogonal experimental design to optimize the NIR detection conditions of fritillaria,such as particle size,scanning times, resolution and gain are four parameters. The experiment obtained the NIR spectra of 109 fritillaria samples under 9 different levels of parameter combinations,and quantitative model is established based on partial least squares. Coefficient of determination (R²),root mean square error of prediction (RMSEP) and F value were used to evaluate the model. Experimental results showed that the scanning times had the greatest influence on the model accuracy, followed by particle size,resolution and gain. And when fritillaria powder passes through 120 mesh screen,the scanning times were 64,the resolution was 8 and the gain was 8,the prediction performance of the model was the best. Experimental results indicated that the four parameters would affect the detection results of fritillary,and the orthogonal experimental design could provide reference for the optimization of NIR quality detection parameters of fritillary powder.