首页|近红外光谱结合不同变量筛选方法用于金银花提取过程中绿原酸量的在线监测

近红外光谱结合不同变量筛选方法用于金银花提取过程中绿原酸量的在线监测

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
  • 维普
目的 采用近红外光谱技术,结合不同变量筛选方法对金银花提取过程中绿原酸量进行快速测定.方法 采用组合间隔偏最小二乘法(SIPLS)、竞争自适应抽样方法(CARS)、变量投影重要性(VIP)、连续投影算法(SPA)4种不同变量筛选方法,以HPLC测定值作参比,建立金银花中绿原酸定量模型并进行比较,优选出最佳变量筛选方法.结果 经SIPLS方法所建绿原酸模型预测能力最好,预测集决定系数(Rpre2)和预测均方根误差(RMSEP)分别为0.990 3和2.316％.结论 近红外光谱法结合SIPLS变量筛选方法建立的绿原酸定量模型性能良好,满足中药提取过程实时监测分析的精度要求,可用于中药提取过程的快速分析.
Online control of chlorogenic acid in Lonicerae Japonicae Flos by near infrared spectroscopy combined with different variable selections
Objective To determine the content of chlorogenic acid in Lonicerae Japonicae Flos by the combined near-infrared and variable selection methods.Methods Synergy interval partial least squares (SIPLS),competitive adaptive reweighted sampling method (CARS),variable importance in projection (VIP),and successive projections algorithm (SPA) were used to build a chlorogenic acid quantitative model in Lonicerae Japonicae Flos and compare.High performance liquid chromatography (HPLC) was used as a reference to select the optimum variable screening method.Results Study results showed that SIPLS was the most desirable method for chlorogenic acid in regression performance with Rpre2 at 0.990 3 and RMSEP at 2.316％.Conclusion The quantitative model of chlorogenic acid established by NIR combined with SIPLS has good performance and meets the requirement of real-time analysis of traditional Chinese medicine production process.

near infrared spectroscopyvariable selectionLonicerae Japonicae Floschlorogenic acidonline controlsynergy interval partial least squarescompetitive adaptive reweighted sampling methodvariable importance in projectionsuccessive projections algorith

杜晨朝、赵安邦、吴志生、乔延江

展开 >

北京中医药大学中药学院国家中医药管理局中药信息工程重点研究室,北京 100102

新疆医科大学中医学院,新疆乌鲁木齐830011

近红外光谱 变量筛选 金银花 绿原酸 在线监测 组合间隔偏最小二乘法 竞争自适应抽样方法 变量投影重要性 连续投影算法

北京市科技新星计划项目北京中医药大学杰出青年基金

xx20160502015-JYB-XYQ-003

2017

10.7501/j.issn.0253-2670.2017.16.009

中草药
天津药物研究院,中国药学会

中草药

CSTPCDCSCD北大核心
影响因子：1.632
ISSN：0253-2670
年,卷(期)：2017.48(16)
  • 11
  • 11