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研究旨在探讨利用银黄颗粒样品的近红外漫反射光谱(NIRS)信息,建立黄芩苷和绿原酸含量的校正模型,为银黄颗粒质量的快速评价提供1种新方法。以HPLC分析值为参照,采用近红外漫反射光谱技术采集100批银黄颗粒样品的近红外漫反射光谱,结合偏最小二乘法(PLS)建立了黄芩苷和绿原酸含量的校正模型。黄芩苷和绿原酸含量的校正模型相关系数(R2)分别为0.998和0.995,校正均方差(RMSEC)为0.578和0.123,内部交叉验证均方差(RMSECV)为2.356和0.412;经外部验证,预测相关系数(r)分别为0.995和0.984,预测均方差为(RMSEP)0.597和0.166。结果表明,该方法准确、简便、无污染,可实现大批量银黄颗粒样品的快速分析。
The aim of this study was to explore a calibration model for the determination of baicalin and chlorogenic acid by using near-infrared diffuse reflectance spectroscopy (NIRS) of silver-yellow particles. The results provide a new method for the rapid evaluation of silver-yellow particles. Near - infrared diffuse reflectance spectroscopy was used to measure the near - infrared diffuse reflectance spectra of 100 samples of Yinhuang granules, and the calibration model of baicalin and chlorogenic acid was established by using partial least squares (PLS). Correlation coefficients of baicalin and chlorogenic acid were 0.998 and 0.995 respectively, RMSEC was 0.578 and 0.123 respectively, RMSECV was 2.356 and 0.412 respectively. After external validation, the correlation coefficient (R2) The correlation coefficients (r) were 0.995 and 0.984, respectively. The mean square error of prediction (RMSEP) was 0.597 and 0.166 respectively. The results show that the method is accurate, simple and non-polluting, and can be used for rapid analysis of large quantities of silver-yellow particles.