Quantitative LC-ESI-MS Analysis for Pesticides in a Complex Environmental Matrix Using External and Internal Standards
- 1 August 2000
- journal article
- research article
- Published by Taylor & Francis in International Journal of Environmental Analytical Chemistry
- Vol. 77 (4), 305-322
- https://doi.org/10.1080/03067310008032699
Abstract
Quantitative liquid chromatography electrospray mass spectrometry (LC-MS) analysis for pesticides in a complex environmental matrix using external and internal standard calibration was investigated. Various approaches to introducing different internal standard compounds to address quantitative errors associated with signal suppression were also examined. The study involved the analysis of pesticides in wheat hay matrix samples using three kinds of internal standard compounds: deuterium labeled (D3), carbon-13 (singly labeled), and structural analogs (derivatives) of the target analytes. Introduction of the internal standard by volumetric addition and direct post-column infusion were also studied and compared. Isotopically labeled internal standards (i.e. D3- 13C-) were found to be effective in correcting quantitative errors associated with signal suppression. The application of singly labeled 13C compounds may result in nonlinear calibration due to mass interference with the target analyte species. The interference may be compensated by using quadratic curve-fitting or subtraction of the interfering component. Although ineffective as volumetric internal standards, structural analogs can be effective in compensating for signal suppression when introduced into the LC effluent by continuous post-column infusion. Furthermore, the post-column introduction method allows the application of a single internal standard compound for the quantification of each analyte in a multi-component mixture. The use of internal standards can be effectively incorporated into residue analysis development methods for pesticides in environmental matrices. High accuracy and reproducibility can be achieved while improving method efficiency by reducing the need for comprehensive sample clean-up.Keywords
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