This summary accompanies a recent event produced by Separation Science in collaboration with Agilent.
Data-independent acquisition (DIA) allows for suspect screening in complex matrices with retroactive analysis capabilities important to emerging compounds of interest in food safety. However, with increased analyte scope, the review of questionable identifications can create an analysis burden requiring timely review and reinjections.
Here, we present a robust DIA methodology with a novel prototype LC/Q-TOF, leveraging a combination of high-resolution, extended dynamic range, stable and accurate mass, and isotopic fidelity with coeluting fragmentation ions for identification, analyzed with MH Quantitative Analysis 12.1 and LC Screener Tool.
Topics covered in this summary include:
- Robust and reliable screening methods for pesticides in food
- Generating high-quality data
- Keeping up with current and future regulations
- Simplifying workflow solutions
Meet the experts:
Cate Simmermaker
LC/MS Applications Engineer, Agilent Technologies, Inc.
Cate Simmermaker is an LC/MS application engineer with Agilent Technologies working primarily with high-resolution mass spectrometry in small-molecule analysis. Cate has worked in applications including metabolomics, food safety, and forensics on Q-TOF and QQQ platforms. She completed her PhD in chemistry at the University of the Pacific and received a Master's in biochemistry from San Francisco State University.
Christian Klein
LC/Q-TOF Portfolio Product Manager, Agilent Technologies, Inc.
With an education in chemistry, Chris Klein received his PhD in 2005 at the Max Planck Institute for Biochemistry in Martinsried, Germany. He joined Agilent Technologies in 2010 as the lead chemist in the LC/Q-TOF R&D team. In 2018, Chris joined the marketing team as Portfolio Product Manager, responsible for LC/Q-TOF and ion mobility.
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