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Evaluation of Two Statistical Tools (Least Squares Regression and Artificial Neural Network) in the Multivariate Optimization of Solid-Phase Extraction for Cadmium Determination in Leachate Samples
Author(s) -
Hélio Rocha Sousa Filho,
Daniel M. Oliveira,
Valfredo Azevedo Lemos,
Marcos Almeida Bezerra
Publication year - 2014
Publication title -
journal of the brazilian chemical society
Language(s) - Portuguese
Resource type - Journals
SCImago Journal Rank - 0.337
H-Index - 70
eISSN - 1678-4790
pISSN - 0103-5053
DOI - 10.5935/0103-5053.20140211
Subject(s) - multivariate statistics , artificial neural network , extraction (chemistry) , partial least squares regression , leachate , statistics , phase (matter) , least squares function approximation , regression , computer science , mathematics , chromatography , chemistry , artificial intelligence , environmental chemistry , organic chemistry , estimator
Este trabalho propoe a otimizacao multivariada de um procedimento para determinacao de cadmio em amostras de chorume usando-se espectrometria de absorcao atomica com chama apos a extracao em fase solida usando-se uma minicoluna empacotada com Amberlite XAD-4 modificada com acido 3,4-diidroxibenzoico. As variaveis relacionadas a pre-concentracao (pH, razao de amostragem e concentracao do tampao) foram otimizadas usando-se planejamento Doehlert. Duas ferramentas para modelagem estatistica (regressao por minimos quadrados e redes neurais artificiais) foram aplicadas aos dados e seus desempenhos foram comparados. Procedimentos de digestao do chorume por aquecimento em meio acido e por radiacao ultravioleta foram avaliados sendo este ultimo mais adequado para evitar a perda de Cd por volatilizacao. O procedimento desenvolvido apresentou um fator de enriquecimento de 9 vezes com limites de deteccao e de quantificacao (3s b ) de 0,72 e 2,4 µg L -1 , respectivamente, e precisao - expressa como porcentagem do desvio padrao relativo - de 4,0 e 6,4% (RSD%, n = 4 para 5,0 e 20,0 µg L -1 , respectivamente). Testes de adicao/recuperacao de Cd foram realizados obtendo-se valores entre 97 e 112%. O procedimento foi aplicado na determinacao de cadmio em amostras de chorume coletadas no aterro sanitario do municipio de Jaguaquara-BA, Brasil. This work proposes the use of multivariate optimization as a procedure for cadmium determination in leachate samples via flame atomic absorption spectrometry after solid phase extraction using a minicolumn packed with Amberlite XAD-4 modified with 3,4-dihydroxybenzoic acid. The variables related with the preconcentration (pH, sampling flow rate and buffer concentration) were optimized using Doehlert design. Two statistical modeling tools (least squares regression and artificial neural networks) have been applied to the data and their performances were compared. Digestion procedures of the leachate by heating in acid medium and ultraviolet radiation were evaluated being the latter more appropriate to prevent loss of Cd by volatilization. The developed procedure has promoted an enrichment factor of 9, with detection and quantification limits (3sb) of 0.72 and 2.4 µg L -1 , respectively, and precision - expressed as relative standard deviation percentage - of 4.0 and 6.4% (RSD%, n = 4 for 5.0 and 20.0 µg L -1 , respectively). Addition/recovery tests for Cd were carried out and values between 97 and 112% were obtained. The procedure was applied for cadmium determination in leachate samples collected at the sanitary landfill of Jaguaquara-BA, Brazil.

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