Comparison of analyte identification criteria and other aspects in triple quadrupole tandem mass spectrometry: Case study using UHPLC-MS/MS for regulatory analysis of veterinary drug residues in liquid and powdered eggs.

Analytical and Bioanalytical Chemistry
Steven J Lehotay

Abstract

Ultrahigh-performance liquid chromatography (UHPLC) coupled with triple quadrupole tandem mass spectrometry (MS/MS) is one of the most powerful tools for the multiclass, multiresidue analysis of veterinary drugs, pesticides, mycotoxins, and other chemical contaminants in foods and other sample types. Until approximately 2010, commercial MS/MS instruments using multiple reaction monitoring (MRM) were generally limited to minimum dwell (and inter-dwell) times of 10 ms per ion transition. To achieve the needed accuracy and detection limits for hundreds of targeted analytes, older UHPLC-MS/MS methods typically acquired only two ion transitions per analyte (yielding only one ion ratio for qualitative identification purposes), which is still the norm despite technological advancements. Newer instruments permit as little as 1 ms (inter-)dwell times to afford monitoring of more MRMs/analyte with minimal sacrifices in accuracy and sensitivity. In this study, quantification and identification were assessed in the validation of 169 veterinary drugs in liquid and powdered eggs. Quantitatively, an "extract-and-inject" sample preparation method yielded acceptable 70-120% recoveries and < 25% RSD for 139-141 (82-83%) of the 169 diverse drug a...Continue Reading

References

May 15, 2003·Journal of the American Society for Mass Spectrometry·Robert BethemStephen Stein
Aug 25, 2015·Food Additives & Contaminants. Part A, Chemistry, Analysis, Control, Exposure & Risk Assessment·Paul Zomer, Hans G J Mol
Mar 6, 2016·Clinica Chimica Acta; International Journal of Clinical Chemistry·Courtney HeideloffSihe Wang
May 1, 2018·Journal of Mass Spectrometry : JMS·Anton Kaufmann
Aug 14, 2018·Clinica Chimica Acta; International Journal of Clinical Chemistry·Dustin R BunchSihe Wang

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