标题:Identification of green tea origins by near-infrared (NIR) spectroscopy and different regression tools
作者:Zhuang, XinGang; Wang, LiLi; Chen, Qi; Wu, XueYuan; Fang, JiaXiong
作者机构:[Zhuang Xingang] Advanced Research Center for Optics, Shandong University, State Key Laboratories of Transducer Technology, Jinan, Shandong 250100, Ch 更多
通讯作者:Wang, Li Li(wanglili1983@sdu.edu.cn)
通讯作者地址:[Wang, LL]Shandong Univ, Adv Res Ctr Opt, Jinan 250100, Peoples R China;[Wang, LL]Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, State 更多
来源:中国科学. 技术科学
出版年:2017
卷:60
期:1
页码:84-90
DOI:10.1007/s11431-016-0464-0
关键词:near-infrared spectroscopy (NIRS); green tea; origin; regression tool
摘要:In this study, near-infrared (NIR) spectroscopy was applied to efficiently and non-destructively identify Shandong green tea origins coupled with three different regression tools. Analysis results indicated that partial least squares (PLS) had better performance than back propagation artificial neural network (BP-ANN) and support vector machine (SVM). For PLS, the accuracies of identification were up to 100% for both training and testing. The results sufficiently demonstrate that NIR spectroscopy can be efficiently utilized for the non-destructive identification of green tea origins.
收录类别:EI;CSCD;SCOPUS;SCIE
WOS核心被引频次:4
Scopus被引频次:5
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995403882&doi=10.1007%2fs11431-016-0464-0&partnerID=40&md5=a67352defb1d76926fd6e6a6cfbedf0f
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