Screening for 1000 Pesticides and Environmental Contaminants using a new High Resolution Accurate Mass GC/Q-TOF

Importance of the Topic

Modern food safety and environmental monitoring demand broad‐scope screening of chemical contaminants. Conventional GC with triple quadrupole detection typically targets 100–300 analytes, leaving many potential hazards unmonitored. High‐resolution accurate mass GC/Q‐TOF, paired with an expanded compound library, enables simultaneous screening of hundreds to over a thousand pesticides and pollutants, enhancing laboratory throughput and confidence in contaminant detection.

Objectives and Study Overview

This work demonstrates a comprehensive workflow for:

• Quantitative analysis of known pesticide residues
• Suspect screening using a curated Personal Compound Database and Library (PCDL) of 1 000+ entries
• Untargeted identification of unknowns via high‐resolution accurate mass spectra and structure‐correlation tools

Studies were performed on complex food matrices (avocado, broccoli) to validate method performance across different compound classes.

Methodology and Instrumentation

Sample preparation followed a QuEChERS protocol with dispersive SPE cleanup. Instrumentation included an Agilent 7250 GC/Q‐TOF equipped with a mid‐column backflushing system and retention‐time locked (RTL) methods. Key GC/Q‐TOF settings:

• Dual HP-5 MS UI columns (15 m, 0.25 mm ID, 0.25 µm film)
• Multi-mode inlet, cold splitless injection of 2 µL
• Oven program: 40 °C to 170 °C at 40 °C/min, then 10 °C/min to 310 °C
• Electron ionization at 70 eV and low‐energy EI at 15 eV for MS/MS
• Spectral acquisition at 5 spectra/sec over 45–650 m/z

Data processing combined MassHunter Quantitative Analysis, PCDL-driven suspect screening, and the Unknowns Analysis software with Molecular Structure Correlator for formula confirmation.

Key Results and Discussion

Quantitative calibration in avocado extracts yielded linear response for carbofuran and deltamethrin at 5 ng/mL. Suspect screening in broccoli identified over 20 pesticides and related contaminants with retention‐time deviations under 0.05 min, fragment‐ratio scores above 70 %, and mass errors typically below 2 ppm. Unknown‐compound analysis highlighted the importance of accurate mass: a tentative NIST match for 1,3,7‐trichloronaphthalene was refined to a chlorothalonil degradation product (2,4,5-trichloroisophthalonitrile) by low‐energy EI MS/MS and formula generation.

Benefits and Practical Applications

• Single‐run, multi‐class screening of 1 000+ targets without method redevelopment
• Enhanced confidence via retention‐time locking and isotopic fidelity of Q‐TOF
• Low‐energy EI MS/MS enables structural elucidation of unknowns
• Applicable to diverse matrices in food safety, environmental analysis, and QA/QC laboratories

Future Trends and Opportunities

Further expansion of accurate‐mass libraries and integration with machine‐learning algorithms will streamline unknown identifications. Combining GC/Q‐TOF with orthogonal separations (e.g., GC×GC) or high‐throughput automation can broaden analyte coverage. Cross‐platform data sharing and cloud-based spectral repositories promise continuous library enrichment and collaborative contaminant surveillance.

Conclusion

This study validates the use of high‐resolution accurate mass GC/Q‐TOF, coupled with an enlarged PCDL, as a versatile platform for quantitative, suspect, and untargeted analysis of pesticides and environmental contaminants. The approach delivers high confidence, broad analyte scope, and efficient unknown elucidation in food matrices.

References

1. Chen K., Sanders J. Agilent Technologies Application Brief, 5991-8170EN (2017).
2. Chen K., Nieto S., Stevens J. Agilent Technologies Application Note, 5991-7691EN (2016).