Please use this identifier to cite or link to this item:
Type: Artigo de evento
Title: Pattern Recognition Applied To Mineral Characterization Of Brazilian Coffees And Sugar-cane Spirits
Author: Fernandes A.P.
Santos M.C.
Lemos S.G.
Ferreira M.M.C.
Nogueira A.R.A.
Nobrega J.A.
Abstract: Aluminium, Ca, Cu, Fe, K, Mg, Mn, Na, Pb, S, Se, Si, Sn, Sr, and Zn were determined in coffee and sugar-cane spirit (cachaça) samples by axial viewing inductively coupled plasma optical emission spectrometry (ICP OES). Pattern recognition techniques such as principal component analysis and cluster analysis were applied to data sets in order to characterize samples with relation to their geographical origin and production mode (industrial or homemade and organically or conventionally produced). Attempts to correlate metal ion content with the geographical origin of coffee and the production mode (organic or conventional) of cachaça were not successful. Some differentiation was suggested for the geographical origin of cachaça of three regions (Northeast, Central, and South), and for coffee samples, related to the production mode. Clear separations were only obtained for differentiation between industrial and homemade cachaças, and between instant soluble and roasted coffees. © 2005 Elsevier B.V. All rights reserved.
Rights: fechado
Identifier DOI: 10.1016/j.sab.2005.02.013
Date Issue: 2005
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
2-s2.0-19744374306.pdf357.97 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.