近红外光谱法快速测定天南星药材中水分

目的:应用近红外光谱技术(NIR)建立快速测定天南星药材中水分的方法。方法:采用烘干法测定样品中的水分,运用偏最小二乘法(PLS)建立该含量与NIR光谱之间的多元校正模型,采用相关系数(R),校正均方根误差(RMSEC),内部交叉验证均方根误差(RMSECV)和外部预测均方根误差(RMSEP)对校正模型进行优化和评价。利用校正模型对未知样品的水分进行预测,检验模型的准确度。结果:采用二阶导数法对光谱进行预处理,在4 774~9 845 cm~(-1)波段,选择前6个主成分建立最优校正模型,所建模型的R为0.990 6,RMSEC为0.16,RMSECV为0.38。经外部验证,校正模型的RMSEP和平均回收率分别为0.298和99.8%。结论:该方法具有简便快速、结果准确、无损样品的特点,可以应用于天南星中水分的快速测定。

Quick Quantitative Analysis of Water Content in Arisaematis Rhizoma by Near-infrared Spectrometry

Objective: To establish a new method for rapidly determining the water content in Arisaematis Rhizoma using near-infrared (NIR) spectroscopy. Method: The water content in Arisaematis Rhizoma was determined by the oven drying method, and the multivariate calibration model between the measured content and the NIR spectrum was established by the partial least square (PLS) regression method. The established model was optimized and evaluated using the correlation coefficient (R), the root-mean-square error of calibration (RMSEC), the root mean square of cross-validation (RMSECV) and the root mean square of prediction (RMSEP). The accuracy of the calibration model was tested by comparing the predicted values and the measured values of the water contents in samples of the prediction model. Result: The NIR spectra were processed by the second derivative spectrophotometry, and the optimal spectral intervals for establishing model ranged between 4 774-9 845 cm^-1, and six optimal principle components were included. Under the optimal conditions, the quantitative calibration model was established, with R of 0.990 6, RMSEC of 0.16 and RMSECV of 0.38.According to the external validation, the RMSEP and average recovery of the calibration model were 0.298 and 99.8%, respectively. Conclusion: The near-infrared spectroscopy quantitative model established in this study is stable, accurate and reliable for the rapid determination of the water content in Arisaematis Rhizoma.