Automated micro-SPE clean-up for GC-MS/MS analysis of pesticide residues in cereals

Significance of the Topic

The global demand for cereals is rising, making reliable screening for pesticide residues in these staple crops essential to ensure food safety and facilitate timely import/export operations. Regulatory limits and consumer health concerns require analytical methods that combine high throughput, robust cleanup, and compliance with EU SANTE guidelines.

Study Objectives and Overview

This study evaluates an automated micro-solid phase extraction (µSPE) cleanup of QuEChERS extracts for GC-MS/MS analysis of multi-class pesticide residues in rice and wheat. It compares the automated µSPE workflow against the conventional manual dispersive SPE (dSPE) cleanup, focusing on throughput, cleanup efficiency, recovery, precision, and compliance with regulatory criteria.

Methodology and Instrumentation

Sample Preparation and Cleanup

• Homogenize 5 g rice or wheat samples (200–500 µm), spike at 0.01 mg/kg, hydrate with 10 mL water.
• Extract with 15 mL 1% acetic acid in acetonitrile, salt out with 6 g anhydrous MgSO4 and 1.5 g sodium acetate, centrifuge.
• Freeze supernatant (−20 °C) to precipitate lipids, centrifuge at −5 °C.
• Perform automated µSPE cleanup on 300 µL aliquots using Thermo Scientific TriPlus RSH autosampler with dedicated µSPE GC cartridges (20 mg MgSO4, 12 mg PSA, 12 mg C18, 1 mg CarbonX).

Calibration

• Solvent standards at 0.0025–0.1 mg/L.
• Matrix-matched standards (rice, wheat) at 0.0025–0.1 mg/kg, cleaned by µSPE, ensuring compensation for cartridge losses.

Instrumentation

• GC: Thermo Scientific TRACE 1310 with TraceGOLD TG-5SILMS column (30 m × 0.25 mm × 0.25 µm).
• Injector: Splitless, 1 µL injection, 250 °C.
• MS: Thermo Scientific TSQ 9000 triple quadrupole with Advanced Electron Ionization (AEI) source, timed-SRM acquisition, helium carrier gas.
• Autosampler: Thermo Scientific TriPlus RSH with µSPE tool and custom scripting to overlay cleanup and analysis steps.

Main Results and Discussion

• Linearity: Matrix-matched calibration linear from 0.0025 to 0.1 mg/kg (R² > 0.995, residuals < 5%).
• Recovery and Precision: At 0.01 mg/kg, rice recoveries 78–119% (RSD ≤ 20%), wheat recoveries 75–104% (RSD < 13%) for 203 of 209 pesticides, meeting EU SANTE criteria.
• Ion Ratios and Retention Times: Two SRM transitions per analyte, ion ratios ± 30%, RT tolerance ± 0.1 min confirmed for all targets.
• Throughput: Automated µSPE reduced sample preparation time by 40–50% and increased overall sample throughput by > 1.5× compared with manual dSPE.

Benefits and Practical Applications

• Reduced manual handling lowers risk of human error and operator fatigue.
• Elimination of solvent evaporation and cartridge weighing simplifies workflow.
• Consistent cleanup across diverse cereal matrices with a single cartridge type.
• Seamless integration with autosampler scripting and CDS software for unattended operation.

Future Trends and Applications

• Extension of automated µSPE cleanup to other food matrices (fruits, vegetables, dairy) without method redesign.
• Integration with high-throughput robotic platforms and laboratory information management systems (LIMS) for full automation.
• Further miniaturization and green chemistry approaches to reduce solvent and sorbent consumption.
• Application of advanced data-processing and machine-learning algorithms to enhance throughput and anomaly detection.

Conclusion

The automated µSPE cleanup method coupled to TSQ 9000 GC-MS/MS provides a robust, high-throughput solution for the determination of pesticide residues in cereals. It delivers excellent accuracy, precision, and regulatory compliance while significantly reducing sample preparation time and manual workload.

References

1. World Trade Organization, International trade statistics, 2014.
2. European Food Safety Authority, The 2013 European Union report on pesticide residues in food, EFSA Journal, 2015, 13, 1–169.
3. USDA Agricultural Marketing Service, Pesticide Data Program Annual Summary, 2014.
4. AOAC Official Method 2007.01, Pesticide residues in foods by acetonitrile extraction and partitioning with magnesium sulfate, 2007.
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6. Lehotay SJ, Han L, Sapozhnikova Y. Automated mini-column SPE cleanup for GC-MS/MS of food contaminants. Chromatographia, 2016, 79, 1113–1130.
7. Goon et al. Journal of AOAC International, Vol. 103, No. x, 2019.
8. Budakoti SK, Singh SP, Oulkar D. Thermo Scientific Application Note 65609: Pesticide residues in apple using GC-AEI-MS/MS, 2019.
9. Singh SP, Budakoti SK, Oulkar D. Thermo Scientific Application Note 73039: Pesticide residues in milk using GC-EI-MS/MS, 2019.
10. European Commission SANTE/12682/2019 Guidance on analytical quality control and method validation for pesticide residues in food and feed, 2019.