Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/64660
Type: Artigo de periódico
Title: Elimination of iron interference in the molecular spectrophotometric determination of aluminum in soil extracts using artificial neural networks
Author: de Andrade, JC
Coscione, AR
Poppi, RJ
Mello, C
Abstract: An artificial neural network (ANN) calibration model was developed to determine aluminum in the presence of iron in soil extracts, using xylenol orange as chromogenic reagent. The spectral data of synthetic mixtures of Al3+ and Fe3+ as well as of the soil extracts, were recorded in the range between 410 and 580 nm. Method validation was carried out using 18 soil extracts. The results gave good linear correlations between the ANN model and the ICP OES measurements for both species.
Country: Japão
Editor: Japan Soc Analytical Chemistry
Citation: Analytical Sciences. Japan Soc Analytical Chemistry, v. 24, n. 9, n. 1147, n. 1150, 2008.
Rights: fechado
Date Issue: 2008
Appears in Collections:Unicamp - Artigos e Outros Documentos

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