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

Detalhes bibliográficos
Autor(a) principal: Mansilha, Catarina
Data de Publicação: 2010
Outros Autores: Melo, A., Rebelo, H., Ferreira, Isabel M. P. L. V. O., Pinho, O., Domingues, Valentina F., Pinho, C., Gameiro, P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/3051
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.
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spelling Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemesEndocrine disruptorsPesticidesGC–MSWaterWeighted linear regression schemesValidationAmulti-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.ElsevierRepositório Científico do Instituto Politécnico do PortoMansilha, CatarinaMelo, A.Rebelo, H.Ferreira, Isabel M. P. L. V. O.Pinho, O.Domingues, Valentina F.Pinho, C.Gameiro, P.2013-11-29T16:27:01Z20102010-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/3051eng0021-967310.1016/j.chroma.2010.05.005metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:42:50Zoai:recipp.ipp.pt:10400.22/3051Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:24:04.529044Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes
title Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes
spellingShingle Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes
Mansilha, Catarina
Endocrine disruptors
Pesticides
GC–MS
Water
Weighted linear regression schemes
Validation
title_short Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes
title_full Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes
title_fullStr Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes
title_full_unstemmed Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes
title_sort Quantification of endocrine disruptors and pesticides in water by gas chromatography–tandem mass spectrometry. Method validation using weighted linear regression schemes
author Mansilha, Catarina
author_facet Mansilha, Catarina
Melo, A.
Rebelo, H.
Ferreira, Isabel M. P. L. V. O.
Pinho, O.
Domingues, Valentina F.
Pinho, C.
Gameiro, P.
author_role author
author2 Melo, A.
Rebelo, H.
Ferreira, Isabel M. P. L. V. O.
Pinho, O.
Domingues, Valentina F.
Pinho, C.
Gameiro, P.
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Mansilha, Catarina
Melo, A.
Rebelo, H.
Ferreira, Isabel M. P. L. V. O.
Pinho, O.
Domingues, Valentina F.
Pinho, C.
Gameiro, P.
dc.subject.por.fl_str_mv Endocrine disruptors
Pesticides
GC–MS
Water
Weighted linear regression schemes
Validation
topic Endocrine disruptors
Pesticides
GC–MS
Water
Weighted linear regression schemes
Validation
description 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.
publishDate 2010
dc.date.none.fl_str_mv 2010
2010-01-01T00:00:00Z
2013-11-29T16:27:01Z
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dc.language.iso.fl_str_mv eng
language eng
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10.1016/j.chroma.2010.05.005
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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