NIRS结合TQ软件对不同产地野菊花定性定量分析

目的:采用近红外光谱技术(NIRS)结合TQ软件对不同产地野菊花进行定性定量分析。方法:运用近红外漫反射光谱技术采集不同产地野菊花药材的NIR光谱,采用TQ软件中的判别分析法对不同产地野菊花进行产地判别;采用HPLC法测定野菊花中绿原酸含量,偏最小二乘法对不同产地野菊花药材中的绿原酸进行定量预测,分别建立了定性定量分析模型,并对模型进行了验证。结果:所建定性模型可快速准确鉴别出不同产地的野菊花药材,验证集样品错判例数为0;绿原酸定量预测模型的校正集内部交叉验证相关系数(R2),校正均方差(RMSEC)和预测均方差(RMSEP)分别为0.995 38,0.008 12和0.012 8。结论:定性定量模型可准确地对不同产地野菊花进行定性定量分析,该方法简便可靠,可用于野菊花药材的快速质量分析。

Qualitative and Quantitative Analysis of Chrysanthemi Indici Flos from Different Origins by Using NIRS and TQ Software

Objective: To conduct qualitative and quantitative analysis of Chrysanthemi Indici Flos from different origins by using near-infrared spectroscopy(NIRS) and TQ software. Method: Near-infrared spectra (NIR) of Chrysanthemi Indici Flos from different origins were collected by near-infrared diffuse reflectance spectroscopy technique, and discriminant analysis of TQ software was uesd to distinguish the origin of Chrysanthemi Indici Flos. The content of chlorogenic acid was determined by using HPLC, and the partial least squares (PLS) method was used to quantitatively predict the chlorogenic acid in the Chrysanthemi Indici Flos from different origins. The qualitative and quantitative analysis models were established and verified respectively. Result: The established qualitative model can quickly and accurately identify the Chrysanthemi Indici Flos from different origins, and the number of wrong discrimination cases in verification set was 0; the correlation coefficients (R²) of the quantitative analysis model was 0.995 38; the root mean square error of calibration (RMSEC) was 0.008 12; and the root mean square error of predication (RMSEP) was 0.012 8. Conclusion: The qualitative and quantitative models could be used to accurately analyze the Chrysanthemi Indici Flos from different origins. This method is simple, accurate and could be used for the rapid quality analysis of Chrysanthemi Indici Flos.