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Fast Pesticide Residue Analysis Using a Novel Benchtop Time-of-Flight Mass Spectrometer

Posters | 2017 | LECOInstrumentation
GC/MSD, GC/TOF
Industries
Food & Agriculture
Manufacturer
Agilent Technologies, LECO

Summary

Significance of the Topic


The ability to rapidly screen and quantify pesticide residues in food matrices is essential for ensuring consumer safety and meeting stringent regulatory standards. Benchtop time-of-flight mass spectrometry combines high sensitivity, full mass-range acquisition, and advanced data deconvolution to deliver both qualitative and quantitative information from a single fast chromatographic run.

Objectives and Study Overview


This study aimed to optimize analysis throughput by reducing chromatographic run times without compromising peak resolution or detection limits. Key goals included:
  • Transitioning from a conventional 30 m column to a shorter 15 m column for sub-9 minute runs
  • Leveraging proprietary NonTarget Deconvolution to maintain qualitative spectral fidelity
  • Employing Target Analyte Find for robust quantitation and method detection limit determination in strawberry QuEChERS extracts

A bulk strawberry extract was fortified with a multiresidue pesticide mix across a wide concentration range and analyzed alongside an unfortified sample to assess both spiked and incurred compounds.

Methodology and Instrumentation


Sample preparation followed a QuEChERS protocol on strawberry matrix. Instrumental conditions included:
  • Gas chromatograph: Agilent 7890B with LECO L-PAL3 autosampler
  • Injection: 1 µL pulsed splitless, 20 psi for 0.7 min, injector temperature 250 °C
  • Column: Rxi-5ms, 15 m × 0.25 mm ID, 0.25 µm film thickness
  • Oven program: 70 °C (0.7 min), ramp to 150 °C at 60 °C/min, then to 330 °C at 30 °C/min (hold 0.5 min)
  • Carrier gas: Helium, 2.0 mL/min constant flow
  • Transfer line: 300 °C; Ion source: 225 °C; Mass range: 45–650 m/z; Acquisition rate: 10 spectra/s
  • Mass spectrometer: LECO Pegasus BT time-of-flight system

Main Results and Discussion


Calibration curves for representative organonitrogen pesticides exhibited excellent linearity (R2 > 0.999) over four orders of magnitude. Limits of detection ranged from 0.10 to 5 ng/g, with most analytes detected at or below 0.5 ng/g. Key observations:
  • The 15 m column facilitated total run times under 9 minutes while preserving adequate resolution.
  • NonTarget Deconvolution successfully isolated and identified incurred pesticides in unfortified extracts, confirmed by NIST library similarity scores above 900.
  • Target Analyte Find quantified spiked pesticides at concentrations up to 100 times lower than typical regulatory thresholds.

Chromatograms demonstrated clear separation of over twenty analytes in a complex strawberry matrix without extensive cleanup steps.

Benefits and Practical Applications


This workflow enables laboratories to achieve high throughput, comprehensive screening, and accurate quantitation in a single injection. Practical advantages include:
  • Rapid turnaround times for routine pesticide monitoring
  • Enhanced sensitivity to detect low-level residues
  • Full-scan data acquisition for retrospective non-target analysis
  • Reduced solvent and consumable usage due to shorter runs

Future Trends and Opportunities


Emerging developments may further enhance pesticide residue analysis by integrating machine learning with spectral deconvolution, expanding screening libraries for non-target compounds, and coupling with automated sample preparation platforms. Advances in multiplexed chromatography and faster detector electronics promise even shorter run times without sacrificing data quality.

Conclusion


The benchtop time-of-flight platform demonstrated here offers a superior blend of qualitative and quantitative capabilities in under 9 minutes per sample. The combination of NonTarget Deconvolution and Target Analyte Find delivers reliable identification and quantitation across a broad dynamic range, supporting robust pesticide monitoring in food safety applications.

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