丹参提取过程多源信息融合建模方法研究

Chinese Traditional and Herbal Drugs(2018)

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Abstract
目的 探索采用多源信息融合建模技术提高中药提取工艺模型的校正和预测性能.方法 以丹参脂溶性成分乙醇提取过程为研究对象,收集不同来源丹参饮片模拟原料波动,采用实验设计(DOE)模拟工艺参数变化,以提取过程近红外光谱(NIRS)作为过程状态变量.采用HPLC法分析提取液中丹参酮ⅡA、隐丹参酮和丹参酮Ⅰ的含量.将原料属性、工艺参数和过程状态变量组合为自变量,以提取液有效成分含量为因变量,采用偏最小二乘(PLS)法建立提取液质量预测模型.结果 建模结果为丹参酮ⅡA交叉验证均方根误差(the root mean squared error of cross validation,RMSECV)为0.172 8 mg/g,预测均方根误差(the root mean squared error of prediction,RMSEP)为0.031 7 mg/g,性能偏差比(ratio of performance to deviation,RPD)为6.91;隐丹参酮RMSECV为0.153 4 mg/g,RMSEP为0.024 2 mg/g,RPD为4.02;丹参酮Ⅰ RMSECV为0.117 1 mg/g,RMSEP为0.043 2 mg/g,RPD为4.76.结论多源信息融合模型的校正和预测性能均优于常规模型,可有效提升丹参提取液质量可预测性和可控性.
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Key words
Salvia miltiorrhiza Bunge,extraction process,multi-source information fusion,modeling method,partial least squares,near infrared spectra,tanshinone ⅡA,cryptotanshinone,tanshinone Ⅰ
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