A total workflow for multi-class, multi-residue analysis of pesticides in fatty food matrices

Join this webinar to learn strategies for sample preparation, instrument method development and optimization, plus workflow applicability to their practical applications

16 Jul 2020
Diane Li
Assistant Editor

The development of multiresidue methods for the determination of fat‑soluble pesticides in edible oil at low levels is still a challenging issue. Much effort has been invested in extraction of hydrophobic pesticides from sample matrices and cleanup of lipids prior to analysis. Matrix co-extractives deposit on the instrument flowpath, decreasing analyte sensitivity by degrading the flowpath inertness. An efficient cleanup of the oil extract is necessary to improve column lifetime and reduce instrument maintenance frequency.

In this upcoming webinar, Limian Zhao and Dr. Xia Yang from Agilent Technologies will present a complete workflow for the analysis of multi-class, multi-residue pesticides in fatty food matrices including milk, salmon and vegetable oils. From sample preparation through to analysis using either GC-MS/MS, LC-MS/MS or both, the entire workflow is designed to provide a simple and efficient sample extraction and fatty food matrix cleanup with accurate and precise analysis for both LC and GC amenable pesticides.

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In this webinar, you will:

  • Understand the challenges posed by fatty food matrices and strategies for both sample preparation and analysis
  • Learn sample preparation methodologies for efficient extraction of pesticides from fatty foods
  • Learn about common Agilent GC-MS/MS and LC-MS/MS system performance for analysis of pesticides
  • A total workflow for analysis of pesticides in fatty food matrices that can be used directly for practical applications

Who should attend

  • Scientists in food labs responsible for method development and sample analysis
  • Lab managers in food labs
  • Bench chemists regularly carrying out sample preparation

The live webinar takes place on Tuesday, July 28, 2020, at:

14:00 BST
09:00 EDT
06:00 PDT
15:00 CEST

Scheduling conflict? No matter, register to receive an on-demand link to watch later>>

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