Method validation using weighted linear regression models for quantification of UV filters in water samples


Autoria(s): Silva, Claudia Pereira da; Emidio, Elissandro Soares; Rodrigues de Marchi, Mary Rosa
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

18/03/2015

18/03/2015

01/01/2015

Resumo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

This paper describes the validation of a method consisting of solid-phase extraction followed by gas chromatography-tandem mass spectrometry for the analysis of the ultraviolet (UV) filters benzophenone-3, ethylhexyl salicylate, ethylhexyl methoxycinnamate and octocrylene. The method validation criteria included evaluation of selectivity, analytical curve, trueness, precision, limits of detection and limits of quantification. The non-weighted linear regression model has traditionally been used for calibration, but it is not necessarily the optimal model in all cases. Because the assumption of homoscedasticity was not met for the analytical data in this work, a weighted least squares linear regression was used for the calibration method. The evaluated analytical parameters were satisfactory for the analytes and showed recoveries at four fortification levels between 62% and 107%, with relative standard deviations less than 14%. The detection limits ranged from 7.6 to 24.1 ng L-1. The proposed method was used to determine the amount of UV filters in water samples from water treatment plants in Araraquara and Jau in sao Paulo, Brazil. (C) 2014 Elsevier B.V. All rights reserved.

Formato

221-227

Identificador

http://dx.doi.org/10.1016/j.talanta.2014.07.041

Talanta. Amsterdam: Elsevier Science Bv, v. 131, p. 221-227, 2015.

0039-9140

http://hdl.handle.net/11449/116757

10.1016/j.talanta.2014.07.041

WOS:000343691000032

Idioma(s)

eng

Publicador

Elsevier B.V.

Relação

Talanta

Direitos

closedAccess

Palavras-Chave #UV filters #Validation #Matrix effect #Heteroscedasticity #Weighted regression
Tipo

info:eu-repo/semantics/article