Organic coffee discrimination with INAA and data mining/KDD techniques: new perspectives for coffee trade |
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| Authors: | Elisabete A. De Nadai Fernandes Fábio S. Tagliaferro Adriano Azevedo-Filho Peter Bode |
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| Affiliation: | 1.Nuclear Energy Center for Agriculture (CENA), University of S?o Paulo (USP), PO Box 96, 13400–970 Piracicaba, S?o Paulo – Brazil e-mail: lis@cena.usp.br Tel.: +55-19-34294655 Fax: +55-19-34294654,BR;2.Department of Economics and Centre for Advanced Studies in Applied Economics, College of Agricultural Engineering Luiz de Queiroz (ESALQ), University of S?o Paulo (USP), PO Box 9, 13418–900 Piracicaba, S?o Paulo – Brazil,BR;3.Interfaculty Reactor Institute (IRI), Delft University of Technology (TUDelft), Mekelweg 15, 2629JB Delft, The Netherlands,NL |
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| Abstract: | 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. Received: 12 April 2002 Accepted: 31 July 2002 Acknowledgments The authors wish to thank the financial support supplied by FAPESP and CNPq; and TUDelft for granting a research fellowship to Mr. Tagliaferro. Thanks are also given to MINASCOFFEE for supplying the coffee samples, and to an anonymous referee for valuable comments. |
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| Keywords: | Organic coffee Inorganic composition Discrimination methods Pattern recognition Quality demonstration vs. quality designation Data mining KDD |
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