Liu Shuang-Yue, Li Wen-Long, Qu Hai-Bin, Zhao Bu-Chang, Zhao Tao
Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310058, China.
Zhongguo Zhong Yao Za Zhi. 2013 Jun;38(11):1657-62.
To establish a rapid quantitative analysis method for the quality control of Danhong injection extraction using near-infrared (NIR) spectroscopy.
Online collecting the NIR spectra during the mixed extraction process of Salvia miltiorrhiza and Carthamus tinctorius, partial least squares regression (PLSR) models were developed for the quality indicators rosmarinic acid (RA), salvia acid B (SaB), lithospermic acid (LA), hydroxysafflor yellow A (HSYA) and solid content (SSC), with HPLC and weight-loss method as reference methods.
The correlation coefficients of the cross validation for RA, SaB, LA, HSYA and SSC were 0.909 3, 0.915 2, 0.901 9, 0.747 7 and 0.931 4, respectively. And the root mean square errors of cross validation (RMSECV) were 0.012 1, 0.251, 0.017 7, 0.038 1 g x L(-1) and 0.359%, respectively.
In this study, NIR spectroscopy was successfully applied to achieve the real-time determination of the contents of RA, SaB, LA and SSC, while the performance of the HSYA calibration model needed to be improved.
建立一种利用近红外（NIR）光谱法对丹红注射液提取物进行质量控制的快速定量分析方法。
在线采集丹参和红花混合提取过程中的近红外光谱，以高效液相色谱法和减重法为参考方法，建立用于质量指标迷迭香酸（RA）、丹酚酸B（SaB）、紫草酸（LA）、羟基红花黄色素A（HSYA）和固含量（SSC）的偏最小二乘回归（PLSR）模型。
RA、SaB、LA、HSYA和SSC的交叉验证相关系数分别为0.909 3、0.915 2、0.901 9、0.747 7和0.931 4。交叉验证均方根误差（RMSECV）分别为0.012 1、0.251、0.017 7、0.038 1 g·L⁻¹和0.359%。
本研究成功应用近红外光谱法实现了RA、SaB、LA和SSC含量的实时测定，而HSYA校正模型的性能有待提高。
