Organic coffee discrimination with INAA and data mining/KDD techniques: new perspectives for coffee trade

被引：1

作者：

Elisabete A. De Nadai Fernandes

Fábio S. Tagliaferro

Adriano Azevedo-Filho

Peter Bode

机构：

[1] Nuclear Energy Center for Agriculture (CENA),

[2] University of São Paulo (USP),undefined

[3] PO Box 96,undefined

[4] 13400–970 Piracicaba,undefined

[5] São Paulo – Brazil e-mail: lis@cena.usp.br Tel.: +55-19-34294655 Fax: +55-19-34294654,undefined

[6] Department of Economics and Centre for Advanced Studies in Applied Economics,undefined

[7] College of Agricultural Engineering Luiz de Queiroz (ESALQ),undefined

[8] University of São Paulo (USP),undefined

[9] PO Box 9,undefined

[10] 13418–900 Piracicaba,undefined

[11] São Paulo – Brazil,undefined

[12] Interfaculty Reactor Institute (IRI),undefined

[13] Delft University of Technology (TUDelft),undefined

[14] Mekelweg 15,undefined

[15] 2629JB Delft,undefined

[16] The Netherlands,undefined

来源：

Accreditation and Quality Assurance | 2002年 / 7卷

关键词：

Keywords Organic coffee; Inorganic composition; Discrimination methods; Pattern recognition; Quality demonstration vs. quality designation; Data mining; KDD;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Samples of green coffee (Coffea arabica) produced in the crop year 1999/2000 in Minas Gerais state, Brazil, were analyzed for the elements Al, Ba, Br, Ca, Cl, Co, Cs, Cu, Fe, K, Mg, Mn, Na, Rb, S, Sc, and Zn using instrumental neutron activation analysis (INAA), in an attempt to establish fingerprints of organically grown coffee. Using data mining/KDD techniques the elements Br, Ca, Cs, Co, Mn, and Rb were found to be suited as markers for discrimination of organic from conventional coffees.

引用

页码：378 / 387

页数：9