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引用本文:蒋程,寿旦,俞忠明,许平翠,王绪平,陈礼平,张晓芹,王娜妮.基于紫外光谱和偏最小二乘回归算法的畲药地稔中浸出物和6种活性成分快速预测方法[J].中国现代应用药学,2020,37(13):1574-1579.
JIANG Cheng,SHOU Dan,YU Zhongming,XU Pingcui,WANG Xuping,CHEN Liping,ZHANG Xiaoqin,WANG Nani.Rapid Prediction of Extractum and Six Active Components in Traditional She Medicine-Melastoma Dodecandrum Lour. by Ultraviolet Spectroscopy and Partial Least Squares Regression Algorithm[J].Chin J Mod Appl Pharm(中国现代应用药学),2020,37(13):1574-1579.
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基于紫外光谱和偏最小二乘回归算法的畲药地稔中浸出物和6种活性成分快速预测方法
蒋程1,2, 寿旦2, 俞忠明2, 许平翠2, 王绪平2, 陈礼平3, 张晓芹3, 王娜妮2
1.浙江省立同德医院药学部, 杭州 310012;2.浙江省中医药研究院, 杭州 310007;3.丽水市中医院, 浙江 丽水 323000
摘要:
目的 建立基于紫外光谱的畲药地稔中浸出物、没食子酸、阿魏酸、芦丁、槲皮素、木犀草素、山奈酚的快速分析方法。方法 测定地稔水提液中的浸出物和6种化合物浓度,采集紫外光谱。采用SIMCA-P+软件,分别建立浸出物、6种化合物浓度与紫外光谱的偏最小二乘回归模型。采用Visual Basic开发应用软件,将所建模型嵌套入软件,为同时快速分析待测溶液中浸出物和6种化合物浓度提供工具。结果 验证集浸出物和6种化合物浓度的预测均方根误差分别为39.1,0.263,19.0,93.8,0.894,0.593,0.896 ng·mL-1,预测值和真实值的相关系数均>0.9,并通过软件在10 s内得到了浸出物和6种化合物浓度的预测结果。结论 本方法可为地稔的快速质量评价提供依据。
关键词:  地稔  紫外光谱  偏最小二乘回归
DOI:10.13748/j.cnki.issn1007-7693.2020.13.007
分类号:R284.1
基金项目:浙江省中医药(中西医结合)重点学科建设项目(2017-XK-A50);浙江省丽水市重点科技创新团队建设计划项目(2018cxtd06)
Rapid Prediction of Extractum and Six Active Components in Traditional She Medicine-Melastoma Dodecandrum Lour. by Ultraviolet Spectroscopy and Partial Least Squares Regression Algorithm
JIANG Cheng1,2, SHOU Dan2, YU Zhongming2, XU Pingcui2, WANG Xuping2, CHEN Liping3, ZHANG Xiaoqin3, WANG Nani2
1.Department of Pharmacy, Tongde Hospital of Zhejiang Province, Hangzhou 310012, China;2.Zhejiang Academy of Traditional Chinese Medicine, Hangzhou 310007, China;3.Lishui Traditional Chinese Medicine Hospital, Lishui 323000, China
Abstract:
OBJECTIVE To establish a rapid method for the determination of the extractum, gallic acid, ferulic acid, rutin, quercetin, luteolin and kaempferol in traditional She medicine-Melastoma dodecandrum by ultraviolet spectroscopy. METHODS The contents of extractum and 6 components in aqueous extract solutions of Melastoma dodecandrum were detected and the ultraviolet spectra were collected. The partial least squares regression models of extractum and 6 components were established separately with the use of SIMCA-P+ software. The software was devised by using Visual Basic, embeded the model into software. This method provided a convenient tool for the simultaneous and rapid determination of extractum and 6 components in unknown samples. RESULTS The root mean square error of predictions for extractum and 6 components were 39.1, 0.263, 19.0, 93.8, 0.894, 0.593, 0.896 ng·mL-1, respectively. The correlation coefficients between the predicted and the reference values for validation set were >0.9 and the predicted contents of extractum and 6 components were calculated automatically within 10 s. CONCLUSION This study provides a rapid method for the quality evaluation of Melastoma dodecandrum Lour.
Key words:  Melastoma dodecandrum Lour.  ultraviolet spectroscopy  partial least squares regression
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