Multielement determination in orange juice by ICP-MS associated with data mining for the classification of organic samples

查看全文 作　　者：Christian [1]Turra;Marcio Dias de [3,4]Lima;Elisabete A.De Nadai [1]Fernandes;Marcio Arruda [1]Bacchi;Fernando Barbosa [2]Jr.;Rommel [3]Barbosa

机构地区：[1]Centro de Energia Nuclear na Agricultura,Universidade de Sao Paulo,Piracicaba,Brazil;[2]USP-Ribeirao Preto,Brazil;[3]Instituto de Informatica,Universidade Federal de Goias,Goiania,GO,Brazil;[4]Instituto Federal de Educacao Ciencia e Tecnologia de Goias,Goiania,GO,Brazil

出　　处：《Information Processing in Agriculture》索引2017年第4卷第3期,共7页

摘　　要：The aim of this study was to discriminate organic from conventional orange juice based on chemical elements and data mining applications.A comprehensive sampling of organic and conventional oranges was carried out in Borborema,state of Sao Paulo,Brazil.The fruits of the variety Valencia(Citrus sinensis(L.)Osbeck)budded on Rangpur lime(Citrus limonia Osbeck)were analyzed.Eleven chemical elements were determined in 57 orange samples grown in organic and conventional systems.In order to classify these samples,data mining techniques(Support Vector Machine(SVM)and Multilayer Perceptron(MLP))were combined with feature selection(F-score and chi-squared).SVM with chi-squared had a better performance compared with the other techniques because it reached 93.00% accuracy using only seven chemical components(Cu,Cs,Zn,Al,Mn,Rb and Sr),and correctly classified 96.73% of the samples grown in an organic system. 关键词：Data mining Support vector machines Multilayer perceptron Orange juice Trace elements Inductively coupled plasma mass spectrometry(ICP-MS)

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Multielement determination in orange juice by ICP-MS associated with data mining for the classification of organic samples

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