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Reliability of Multiresidue Identification: HRMS versus QQQ Mass Spectrometry

RECORD | Already taken place We, 28.9.2022
The causes of “false positive” and “false negative” derived from both QqQ-MS and HR-MS detection will be discussed.
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Agilent Technologies: Reliability of Multiresidue Identification: HRMS versus QQQ Mass Spectrometry

Agilent Technologies: Reliability of Multiresidue Identification: HRMS versus QQQ Mass Spectrometry

It is of utmost importance to ensure that the analytical results from residue testing for food products are reliable. “False positive” findings of hazardous residues in food result in safe product being rejected and leading to potential huge financial and juristic implications. “False negative” findings result in contaminated product being on the shelf and increase the risk of a foodborne disease. The reliability of testing results depends on the type of methodology and the performance criteria. Identification is the important step before a residue is reported.

Procedures for identification should be rigorous and depend on sensitivity and selectivity of the MS techniques. The causes of “false positive” and “false negative” derived from both QqQ-MS and HR-MS detection will be discussed. The approaches of establishing a “fit-for-purpose” methodology and identification criteria for both QqQ-MS and HR-MS will be introduced.

This will help the testing labs build the protocols/procedures to follow to reduce the incidence of “false detections”; help set up the criteria for identification; and help deliver the highly accurate results.

Presenter: Hui Zhao (Pre-Sales Application Engineer, Agilent Technologies, Inc.)

Hui has 13 years of industry experience developing and validating analytical methods for food/feed nutrition, food safety, dietary supplements and botanicals testing, using a variety of analytical techniques including LC-TQ, LC-QTOF, LC-DAD and GC-MS and a breadth of sample preparation methodologies. She has worked as a Research Scientist at Monsanto, EPL-Bioanalytical Services, Tate & Lyle, Inc. and Lead Staff Scientist at Covance Food Solutions. She holds a Master of Science degree in Analytical Chemistry from Lanzhou University in China and a Ph.D. in Analytical Chemistry from the University of Missouri.

Prior to becoming a Pre-Sales AE, Hui worked as an LCMS application scientist in Agilent’s global market development group where her primary focus was food and environmental market development.

Agilent Technologies
 

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