近红外漫反射光谱结合偏最小二乘法快速测定厚朴中酚类成分和水分含量

目的:利用近红外漫反射光谱技术对厚朴药材中水分和酚类成分进行快速、无损的定量分析。方法:收集不同产地厚朴样品99批,采用偏最小二乘法建立水分和酚类成分的近红外定量模型,以烘干法和超高效液相色谱法,分别测定样品中水分和酚类成分的含量,作为参考值,并用相关系数和预测均方差对模型预测性能进行评价。结果:水分、厚朴酚、和厚朴酚、总酚的校正均方差分别为0.155,0.120,0.133,0.236;相关系数分别为0.872 8,0.989 9,0.976 9,0.981 2;最佳主成分数分别为4,6,9和5;预测误差均方差分别为0.161,0.154,0.179,0.248。结论:所建立的近红外分析方法快捷、准确、无损,可用于厚朴药材质量的快速检测。

Rapid Determination of Phenolic Compounds and Water Contents in Magnoliae Officinalis Cortex Using Near Infrared Diffuse Reflectance Spectroscopy Combined with PLS Algorithm

Objective: To develop quantitative methods for rapid and nondestructive determination of phenolic compounds and water in Magnolae Officinalis Cortex using near-infrared (NIR) diffuse reflectance spectroscopy. Method: 99 batches of Magnolae Officinalis Cortex samples were collected from different regions of China.Partial least squares (PLS) method was used to establish NIR quantitative models for determinations of water and phenolic compounds in samples. The reference analyses were performed with oven-drying method and ultra performance liquid chromatography method respectively for determination of water and phenolic compounds. Correlation coefficient and predicted root mean square error were also used for evaluating the estimated performance of the models. Result: For water, magnolol, honokiol, and magnolol+honokiol, root mean square errors of calibration set were 0.156, 0.120, 0.133 and 0.236, respectively;the correlation coefficients were 0.8728, 0.9899, 0.9769 and 0.9812, respectively;and principal components were 4, 6, 9 and 5, respectively. Predicted root mean square errors of the four analytes reached 0.161, 0.154, 0.179 and 0.248, respectively. Conclusion: The developed analytical method based upon NIR spectroscopy was proved to be rapid, accurate, and non-destructive, which can be used for rapid quality evaluation of Magnolae Officinalis Cortex.