文献类型：期刊文献

中文题名：中药甘青青兰提取过程的近红外及紫外可见双光谱在线监测

英文题名：Near Infrared and Ultraviolet-Visible Dual-spectrum Online Monitoring of the Extraction Process of Chinese Medicine Dracocephalum Tanguticum Maxim

作者：张文婷[1];王凯君[1];路亚梅[2];杨吴烨[1];熊訚然[1];吴琼[1];杜一平[1]

机构：[1]华东理工大学化学与分子工程学院,上海市功能材料化学重点实验室,上海200237;[2]上海海关工业品中心,上海200135

年份：2024

卷号：43

期号：5

起止页码：746

中文期刊名：分析测试学报

外文期刊名：Journal of Instrumental Analysis

收录：CSTPCD;;北大核心:【北大核心2023】；CSCD:【CSCD2023_2024】；

语种：中文

中文关键词：双光谱监测;NIR;UV-Vis;在线监测;中药;甘青青兰;木犀草素;绿原酸

外文关键词：dual-spectrum monitoring;NIR;UV-Vis;online monitoring;Chinese medicine;Dracocephalum tanguticum Maxim;luteolin;chlorogenic acid

摘要：使用小型光纤光谱仪构建了近红外光谱(NIR)和紫外可见光谱(UV-Vis)在线监测系统,并利用双光谱监测提取过程。通过采样误差分布分析(SEPA)和稳定性竞争性自适应重加权抽样(SCARS)等化学计量学方法对光谱数据进行处理,建立了偏最小二乘(PLS)光谱分析模型。对NIR光谱、UV-Vis光谱以及双光谱融合模型的分析性能进行了比较。结果表明,木犀草素的NIR光谱分析模型,绿原酸的UV-Vis光谱分析模型性能较好。木犀草素模型的预测均方根误差(RMSEP)为0.0107μg·mL^(-1),绿原酸模型的RMSEP为0.0295 mg·mL^(-1),模型的预测能力较好。该研究开发的系统操作简便、快速,模型准确性高,为中药提取的在线监测提供了新的策略。
An online monitoring system of near infrared spectrum(NIR)and ultraviolet-visible spectroscopy(UV-Vis)is constructed using small optical fiber spectrometers,and the spectra are online collected with the system.After a spectrum collection,the sample is sent back into the extraction container to avoid the loss of the extraction liquid,and the pipeline is cleaned with the backward flow to prevent the pipeline from clogging.The extraction process is monitored by the dual-spectrum system to improve the acquisition of spectral information.Sampling error profile analysis(SEPA)and stability competitive adaptive reweighted sampling(SCARS)and other chemometric methods are used for the spectral process and model establishment.The analytical performances of NIR spectroscopy,UV-Vis spectroscopy and dual-spectrum fusion models are compared.The results show that the NIR spectral model of luteolin and the UV-Vis model of chlorogenic acid are better.The predicted rootmean-square error(RMSEP)of luteolin model is 0.0107μg·mL^(-1),and that of chlorogenic acid model is 0.0295 mg·mL^(-1).The system developed in this study is simple,rapid and has high model accuracy,which provides a new strategy for online monitoring of Chinese medicine extraction.