QuEChERS extracted pesticide quantitation by LCMS QTOF using HRAM at high data acquisition speed

Importance of the Topic

Monitoring pesticide residues in food is essential to ensure consumer safety and compliance with regulatory maximum residue limits (MRLs). High-resolution accurate mass (HRAM) mass spectrometry combined with rapid data acquisition offers the sensitivity and selectivity needed to screen large panels of pesticides at trace levels.

Objectives and Study Overview

This work aimed to develop and validate a robust LC–QTOF HRAM method for quantifying 212 pesticide compounds in diverse food matrices. Using a QuEChERS extraction approach and adhering to the EU SANTE/11813/2017 guidelines, the study evaluated detection, quantitation at the default MRL of 0.01 mg/kg, and confirmation criteria across targeted and untargeted workflows.

Methodology

• Sample Preparation: QuEChERS extraction of commodities such as avocado, cocoa, curry leaf, and flaxseed; direct injection of acetonitrile extracts.
• Chromatography: Restek Raptor ARC18 column (100×2.1 mm, 2.7 µm) with a binary gradient of 0.004% formic acid/2 mM ammonium formate in water (Solvent A) and methanol (Solvent B).

Instrumentation

• LC System: Shimadzu Nexera LC.
• Mass Spectrometer: Shimadzu LCMS-9030 QTOF operated in full-scan (m/z 140–900) plus 38 data-independent acquisition (DIA) MS/MS windows (m/z 65–900), collision energy spread 0–30 V.
• Acquisition Speed: Total cycle time <0.8 s, enabling >10 points across 0.10–0.15 min peaks.

Main Results and Discussion

• Detection & Quantitation: All 212 pesticides quantified at 0.01 mg/kg with mass accuracy ≤5 ppm (≤1 mDa for m/z <200).
• Calibration: Linear or quadratic fits over 0.002–0.2 mg/kg gave R² >0.99 using four deuterated internal standards.
• Confirmation: HRAM precursor and fragment ions provided reliable compound identification under SANTE guidelines.

Benefits and Practical Applications

This HRAM QTOF approach supports high-throughput targeted monitoring and allows retrospective untargeted screening. It enhances laboratory efficiency for routine food safety testing and quality assurance.

Future Trends and Potential Uses

• AI-assisted data processing for automated library matching and anomaly detection.
• Expansion of screening libraries to cover emerging contaminants and metabolites.
• Integration of multiplexed sample introduction and microflow LC to boost throughput further.

Conclusion

The developed QuEChERS–LCMS QTOF HRAM method fulfills EU regulatory requirements for pesticide analysis, delivering high sensitivity, selectivity, and speed to meet modern food safety challenges.