Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes


Autoria(s): Mansilha, Catarina; Melo, A.; Rebelo, H.; Ferreira, Isabel M. P. L. V. O.; Pinho, O.; Domingues, Valentina F.; Pinho, C.; Gameiro, P.
Data(s)

29/11/2013

29/11/2013

2010

Resumo

Amulti-residue methodology based on a solid phase extraction followed by gas chromatography–tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC–MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness.

Identificador

http://dx.doi.org/10.1016/j.chroma.2010.05.005

0021-9673

http://hdl.handle.net/10400.22/3051

Idioma(s)

eng

Publicador

Elsevier

Relação

Journal of Chromatography A; Vol. 1217, Issue 43

http://www.sciencedirect.com/science/article/pii/S0021967310006291

Direitos

closedAccess

Palavras-Chave #Endocrine disruptors #Pesticides #GC–MS #Water #Weighted linear regression schemes #Validation
Tipo

article