Origin identification of Panax notoginseng by multi-sensor information fusion strategy of infrared spectra combined with random forest
文献类型： 外文期刊
作者： Zhou, Yuhou 1 ; Zuo, Zhitian 2 ; Xu, Furong 1 ; Wang, Yuanzhong 2 ;
作者机构： 1.Yunnan Univ Chinese Med, Coll Tradit Chinese Med, 1076 Yuhua Rd, Kunming 650500, Yunnan, Peoples R China
2.Yunnan Acad Agr Sci, Inst Med Plants, Kunming 650200, Yunnan, Peoples R China
关键词： Panax notoginseng; Origin identification; Sensors; Variable importance
期刊名称：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY （ 影响因子：4.098； 五年影响因子：3.464 ）
ISSN： 1386-1425
年卷期： 2020 年 226 卷
页码：
收录情况： SCI
摘要： Traditional Chinese medicine Panax notoginseng is a valuable geo-authentic herbal material. The difference of growth environment in different producing areas has significant influence on the quality of traditional Chinese medicine, and origin identification is an important part of the quality assessment of P. notoginseng. In this study, Fourier transform mid-infrared (FT-MIR) and near infrared (NIR) sensor technologies combined with single spectra analysis and multi-sensor information fusion strategy (low-, mid- and high-level) for the origin identification of 210 P. notoginseng samples from five cities in Yunnan Province, China. FT-MIR spectra were considered to play a greater role in data analysis than NIR spectra. Random forest (RF) was used to establish classification models. The result of the random forest Boruta (RF-Bo) model and the random forest variable selection (RF-Vs) model based on high-level multi-sensor information fusion strategy was satisfactory. In addition, the RF-Bo model based on high-level multi-sensor information fusion strategy was faster and simpler in data analysis and the accuracy was 95.6%. (C) 2019 Elsevier B.V. All rights reserved.
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