近红外光谱技术快速测定麦门冬药材中水分的含量

[目的]利用近红外漫反射光谱法结合化学计量法建立一种快速测定麦门冬药材中水分含量的方法。[方法]以烘干法测定90批麦门冬的水分含量作为参考值,利用近红外光谱仪采集麦门冬漫反射光谱结合偏最小二乘法(PLS)建立麦门冬药材中水分定量校正模型。[结果]运用SNV+First Derivative+Norris平滑光谱预处理方法,筛选最佳建模波段在5 000~9 000 cm-1,主因子数为8,建立的定量模型内部交叉验证相关系数R为0.981 1,交叉验证误差均方差RMSECV为0.131,12批验证集样品的参考值与预测值经统计学t检验,P=0.950.05,表明2组数据无统计学意义。[结论]运用近红外光谱技术建立麦门冬水分定量模型可快速预测其水分值,该方法快速、简便,结果准确,为中药材质量的实时监测提供数据支持。

Rapid determination of moisture content in Ophiopogon japonicus by near-infrared spectroscopy

[Objective] To establish a rapid method to determine the moisture content in Ophiopogon japonicus by using near-infrared spectroscopy combined with stoichiometric method.[Methods] The reference values of moisture content was determined by the moisture content of 90 batches of Ophiopogon japonicus whicn obtained by oven-drying method, the diffuse reflectance spectra data of Ophiopogon japonicus was collected by near infrared spectroscopy. Then the quantitative calibration model of moisture content in Ophiopogon japonicus was established by partial least square(PLS).[Results] The pretreatment method of smoothing spectrum (SNV+First Derivative+Norris) was used to screen the best modeling in 5 000~9 000 cm^-1, the principal factor number is 8,the internal cross validation correlation coefficient R of the quantitative model is 0.981 1 and the cross validation error variance RMSECV is about 0.131,The reference values and predicted values,which were analyzed by statistical test about the 12 batches of validation samples, P=0.95>0.05, indicated that the data of the 2 groups were not statistically significant.[Conclusion] The quantitative model of moisture content in Ophiopogon japonicus which was established by the near infrared spectroscopy technology can quickly predict the moisture value of Ophiopogon japonicus.This method is simple,apid and accurate,it provide the data support for the real-time monitoring of the quality of Chinese herbal medicines.