Screening of Pesticides in Lipid-rich Food Matrices by Using High Resolution GC/Q-TOF and Accurate Mass Pesticide Library

Significance of the Topic

The screening of pesticide residues in lipid-rich food matrices is critical for ensuring consumer safety and regulatory compliance. Complex matrices such as oils, fatty fruits, and seafood pose analytical challenges due to high background interferences and stringent maximum residue limits. High-resolution accurate mass GC/Q-TOF allows untargeted full-scan acquisition, enabling the detection and identification of both known and unexpected contaminants at trace levels.

Objectives and Study Overview

This work aimed to establish and validate a comprehensive GC/Q-TOF workflow, paired with an accurate mass pesticide library, to screen 120 diverse pesticides in complex lipid-rich matrices. The method was evaluated using peanut oil, avocado, and salmon extracts spiked at 5 and 10 ng/mL to assess sensitivity, precision, and identification confidence.

Methodology and Instrumentation Used

• Sample Preparation: QuEChERS EN extraction, EMR-Lipid dSPE cleanup, and dry polishing steps.
• Matrices: Organic peanut oil, avocado, and salmon were selected for their high lipid content.
• Instrumentation: Agilent 7200 Series GC/Q-TOF configured with mid-column backflushing and retention time locking (RTL).
• Chromatographic Conditions: 20 min constant flow RTL method on dual HP-5 MS UI columns; helium carrier gas; inlet parameters with cold splitless injection.
• Mass Spectrometry: Electron ionization full-scan mode (45–550 m/z) at 5 spectra/s, operated in 4 GHz high-resolution mode.
• Data Analysis: MassHunter Qualitative software (Find by Fragment workflow) using a curated accurate mass pesticide library; results transferred to MassHunter Quantitative for calibration.

Main Results and Discussion

• Detectability: Automated analysis identified over 110 of the 120 pesticides at both 5 and 10 ng/mL levels in all three matrices.
• Retention Time Repeatability: Standard deviation ≤0.01 min (RSD% ≤0.1) for all compounds at 5 ng/mL (n=6).
• Response Precision: Most pesticides exhibited single-digit %RSD at both spike levels, indicating robust quantitative performance.
• Mass Accuracy: Over 90% of identified pesticides achieved mass errors below 5 ppm; 120 in peanut oil, 108 in avocado, and 107 in salmon met this criterion.
• Ion Ratio Stability: Qualified ion pairs maintained relative ion ratio variance within 30% compared to library reference spectra.
• Long-Term Stability: Sequential injections (36 total) of avocado extracts spiked at 5 and 10 ng/mL demonstrated consistent response RSD for example analytes.
• Dynamic Range: Matrix-matched calibration in avocado from 5 to 200 ng/mL yielded R² >0.99 for 105 pesticides using an innovative profile-based algorithm.

Benefits and Practical Applications

• Enhanced identification confidence via accurate mass, retention time, and ion ratio criteria.
• Comprehensive untargeted screening suitable for regulatory and quality control laboratories.
• Capability to detect unexpected contaminants, improving food safety monitoring.
• Applicable workflow for routine analysis in industrial, environmental, and research settings.

Future Trends and Possibilities

• Expansion of accurate mass libraries to cover emerging pesticide and degradation products.
• Integration of automated data processing and AI-driven spectral interpretation for higher throughput.
• Development of faster chromatographic and sample preparation methods to increase lab efficiency.
• Portable high-resolution MS platforms for on-site rapid screening.
• Advanced non-targeted screening workflows to identify novel or unexpected compounds.

Conclusion

The demonstrated GC/Q-TOF workflow, coupled with an accurate mass pesticide library, provides a robust, sensitive, and reliable approach for screening low-level pesticide residues in lipid-rich food matrices. Excellent retention time precision, mass accuracy, and dynamic range support confident identification and quantification, facilitating compliance with regulatory standards and enhancing food safety monitoring.