Abstract − Analytical Sciences, 24(9), 1147 (2008).
Elimination of Iron Interference in the Molecular Spectrophotometric Determination of Aluminum in Soil Extracts Using Artificial Neural Networks
João Carlos de ANDRADE,* Aline R. COSCIONE,** Ronei J. POPPI,* and Cesar MELLO***
*Universidade Estadual de Campinas, Instituto de Química, CP 6154, 13084-971, Campinas-SP, Brazil
**Instituto Agronômico de Campinas, CP 82, 13001-970, Campinas-SP, Brazil
***Universidade de Franca, CP 82, 14404-600, Franca-SP, Brazil
**Instituto Agronômico de Campinas, CP 82, 13001-970, Campinas-SP, Brazil
***Universidade de Franca, CP 82, 14404-600, Franca-SP, Brazil
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.
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