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

• Type: Article in International Scientific Journal
• Date: 2010

Authors

Mansilha, C (Author) Other; Melo, A (Author) Other; Rebelo, H (Author) Other; Ferreira, IMPLVO (Author) FFUP; Pinho, O (Author) FCNAUP; Domingues, V (Author) Other; Pinho, C (Author) Other; Gameiro, P (Author) FCUP

Journal

Title: Journal of Chromatography A

Vol. 1217 No. 43

Pages: 6681-6691

ISSN: 0021-9673

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 75 Citations

Scopus - 80 Citations

Scientific classification

FOS: Natural sciences > Chemical sciences

Other information

Authenticus ID: P-003-1TQ

DOI: 10.1016/j.chroma.2010.05.005

Abstract (EN): multi-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 standaid 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 CC-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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11