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近红外光谱结合偏最小二乘判别分析用于药用木瓜产地鉴别

Identification of Medicinal Mugua Origin by Near Infrared Spectroscopy Combined with Partial Least-squares Discriminant Analysis.

作者信息

Han Bangxing, Peng Huasheng, Yan Hui

机构信息

Department of Pharmaceutical Engineering, College of Biological and Pharmaceutical Engineering, West Anhui University, Anhui, Lu'an 237012, China.

Department of Traditional Chinese Medicine Resources, College of Pharmacy, Anhui University of Chinese Medicine, Hefei 230012, China.

出版信息

Pharmacogn Mag. 2016 Apr-Jun;12(46):93-7. doi: 10.4103/0973-1296.177907.

Abstract

BACKGROUND

Mugua is a common Chinese herbal medicine. There are three main medicinal origin places in China, Xuancheng City Anhui Province, Qijiang District Chongqing City, Yichang City, Hubei Province, and suitable for food origin places Linyi City Shandong Province.

OBJECTIVE

To construct a qualitative analytical method to identify the origin of medicinal Mugua by near infrared spectroscopy (NIRS).

MATERIALS AND METHODS

Partial least squares discriminant analysis (PLSDA) model was established after the Mugua derived from five different origins were preprocessed by the original spectrum. Moreover, the hierarchical cluster analysis was performed.

RESULTS

The result showed that PLSDA model was established. According to the relationship of the origins-related important score and wavenumber, and K-mean cluster analysis, the Muguas derived from different origins were effectively identified.

CONCLUSION

NIRS technology can quickly and accurately identify the origin of Mugua, provide a new method and technology for the identification of Chinese medicinal materials.

SUMMARY

After preprocessed by D1+autoscale, more peaks were increased in the preprocessed Mugua in the near infrared spectrumFive latent variable scores could reflect the information related to the origin place of MuguaOrigins of Mugua were well-distinguished according to K. mean value clustering analysis. Abbreviations used: TCM: Traditional Chinese Medicine, NIRS: Near infrared spectroscopy, SG: Savitzky-Golay smoothness, D1: First derivative, D2: Second derivative, SNV: Standard normal variable transformation, MSC: Multiplicative scatter correction, PLSDA: Partial least squares discriminant analysis, LV: Latent variable, VIP scores: Important score.

摘要

背景

木瓜是一种常见的中药材。中国主要有三个药用产地,分别为安徽省宣城市、重庆市綦江区、湖北省宜昌市,以及适宜的食用产地山东省临沂市。

目的

构建一种基于近红外光谱(NIRS)鉴别药用木瓜产地的定性分析方法。

材料与方法

对来自五个不同产地的木瓜进行原始光谱预处理后,建立偏最小二乘判别分析(PLSDA)模型,并进行层次聚类分析。

结果

结果表明建立了PLSDA模型。根据产地相关重要得分与波数的关系以及K均值聚类分析,有效鉴别了不同产地的木瓜。

结论

近红外光谱技术可快速、准确地鉴别木瓜产地,为中药材鉴别提供了一种新的方法和技术。

总结

经D1+自动标度预处理后,近红外光谱中预处理后的木瓜增加了更多峰。五个潜变量得分可反映与木瓜产地相关的信息。根据K均值聚类分析,木瓜产地得到了很好的区分。缩写词使用:TCM:传统中药,NIRS:近红外光谱,SG:Savitzky-Golay平滑,D1:一阶导数,D2:二阶导数,SNV:标准正态变量变换,MSC:多元散射校正,PLSDA:偏最小二乘判别分析,LV:潜变量,VIP得分:重要得分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25f2/4809173/3ce549b882a7/PM-12-93-g001.jpg

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