Multilaboratory Collaborative Study of a Nontarget Data Acquisition for Target Analysis (nDATA) Workflow Using Liquid...

Area of Science:

• Food safety analysis
• Analytical chemistry
• Mass spectrometry

Background:

• Nontarget data acquisition (nDATA) workflows using liquid chromatography-high-resolution accurate mass (LC-HRAM) spectrometry offer potential for broad screening of pesticides in food.
• However, rigorous evaluation of these workflows, including instrument processing software, is crucial before routine implementation.

Purpose of the Study:

• To collaboratively evaluate an nDATA workflow for pesticide screening in high-moisture produce across multiple laboratories.
• To assess the performance of LC-HRAM platforms (QOrbitrap and QTOF) using full-scan/data-independent acquisition (FS MS/DIA MS/MS) and a restricted pesticide database.

Main Methods:

• Twenty-five laboratories participated, extracting pesticides from produce using the QuEChERS method.
• Data were acquired via UHPLC-MS/MS, and pesticide identification relied on retention time and mass accuracy criteria for precursor and product ions.
• The workflow was tested with a 51-pesticide database and vendor software, analyzing unfortified and fortified samples (10 and 100 μg/kg).

Main Results:

• Elution profiles of 51 pesticides were consistent across 24 laboratories (±0.5 min).
• Low false negative rates (0.7% at 10 μg/kg, 0.1% at 100 μg/kg) and a false positive rate of 1.1% were achieved.
• Twenty-two laboratories successfully identified all blinded fortified pesticides (5-50 μg/kg) in produce samples, yielding a 99.7% detection rate.

Conclusions:

• The nDATA workflow demonstrates broad screening capabilities for pesticide analysis in food matrices.
• This validated approach provides a robust platform for identifying chemical residues and contaminants, with potential for expansion to other analytes.