NIR在线检测、分析技术在丹参水提过程质量监控中的应用

Research on the application of on-line detection and analytical technique by MR in quality control of water extracting process of Salvia miltiorrhiza

目的 研究丹参水提过程中在线检测的近红外光谱(NIR)信息与离线检测的产品HPLC信息间的关系,实现用NIR技术对中药提取过程的在线检测与质量控制。方法 模拟丹参水提过程的近红外在线检测并对提取物进行HPLC测试,获取提取液的NIR光谱信息与提取物中的代表性活性成分丹酚酸B,丹参酮ⅡA的含量信息,采用偏最小二乘方法建立NIR与HPLC信息间的关系。结果 近红外最佳建模波长范围为1:300-1 600 nm与2 200-2 400nm。对丹参酮ⅡA,模型相关系数r2=0.942 7,校正标准差为0.917 7,对校验集样品的最大绝对预测误差为1.4％;对丹酚酸B,模型相关系数r2=0.914 3,校正标准差=1.121 2,对校验集样品的最大绝对预测误差为3.08％。结论 NIR技术用于中药提取过程的在线检测与质量监控,可满足药品生产控制精度。

OBJECTIVE: To Study the relationship between on-line NIR spectrum information and off-line HPLC information of the product during water extracting process of Salvia miltiorrhiza Bunge. METHOD: On-line NIR detection of water extracting process of Salvia miltiorrhiza Bunge was simulated in the laboratory to obtain the NIR spectrum information, HPLC detection of the extracts was carried out to determine the contents of salvianolic acid B and tanshinone II A as the representative active components. PLS method was used to establish the relationship between the information of NIR and HPLC. RESULTS: The optimum NIR wavelength range for establishing the calibration model was 1300-1 600 nm and 2 200-2 400 nm. For tanshinone II A, r2 = 0.942 7, SEC = 0.917 7, the largest absolute predication error was 1.40%; For salvianolic acid B, r 2 = 0.914 3, SEC = 1.121 2, the largest absolute predication error was 3.08%. CONCLUSION: NIR technique can be used in the on-line detection and quality control of the exacting process of TCM, and can provide analytic results that satisfy precision requirement of industrial production.