Multi-pesticide residues analyses of QuEChERS extracts using an automated online μSPE clean-up coupled to LC-MS/MS

Significance of the topic

The increasing diversity of pesticides and the globalization of the food supply demand fast, robust and high-throughput multi-residue analytical methods to ensure consumer safety and regulatory compliance. Traditional QuEChERS dispersive SPE clean-up can suffer from matrix interferences and instrument contamination when analyzing complex samples such as fruit, cereals and teas.

Objectives and study overview

This work demonstrates the feasibility and performance of a fully automated online micro-SPE (μSPE) clean-up integrated with LC-MS/MS for the rapid quantitation of over 190 pesticides in representative food matrices (grape, rice, black tea). Method performance was benchmarked against standard dispersive SPE (d-SPE) QuEChERS clean-up following EU SANTE guidelines.

Methodology and instrumentation

Samples of grape, rice and tea were extracted using citrate- or acetate-buffered QuEChERS and centrifuged. Aliquots of supernatant underwent either manual d-SPE (MgSO4, PSA, C18 sorbents) or automated online μSPE clean-up on a TriPlus RSH autosampler with miniaturized Z-Sep/C18/CarbonX cartridges. The μSPE protocol comprised cartridge conditioning, sample loading and elution in ten minutes with acetonitrile/methanol-ammonium formate eluents. Cleaned extracts were separated on an Accucore AQ UHPLC column under a 15 min gradient of ammonium formate/formic acid in water and methanol, and detected by a TSQ Fortis triple quadrupole in scheduled SRM (195 transitions).

Key results and discussion

Online μSPE achieved superior removal of pigments and co-extractives compared to d-SPE, as confirmed by full-scan HRAM MS chromatograms and lower matrix effects (<20% for >90% of compounds). Linearity from 0.5 to 100 μg/kg was excellent (r2 > 0.99) using matrix-matched calibration. Recoveries of 70–120% with RSD <20% were attained for 96–98% of pesticides across matrices at 10, 50 and 100 μg/kg. LOQs of 10 μg/kg were achieved for the majority of analytes. Method robustness was demonstrated by stable fenpyroximate responses (±20%) over 200 consecutive injections without maintenance.

Benefits and practical applications

• Fully automated online clean-up reduces analyst time and human error.
• μSPE cartridges provide enhanced matrix removal and instrument protection.
• High throughput with overlapping sample prep and LC-MS/MS runs maximizes productivity.
• Reliable quantitation of broad pesticide panels in diverse food matrices.

Used instrumentation

• Thermo Scientific TriPlus RSH autosampler with μSPE capability
• Thermo Scientific Vanquish Horizon UHPLC system
• Thermo Scientific TSQ Fortis triple quadrupole MS with H-ESI
• Accucore AQ column (2.1×100 mm, 2.6 μm)

Future trends and potential applications

Integration of online μSPE with high-resolution MS, further miniaturization of sample prep and expanded library coverage will drive advances in food safety analysis. Automated workflows combined with AI-driven data processing promise deeper screening capabilities and faster turnaround. The approach can be extended to environmental, clinical and industrial matrices requiring trace-level multi-residue screening.

Conclusion

The automated online μSPE-LC-MS/MS method delivers a fast, robust and reproducible solution for multi-pesticide residue analysis in complex food matrices. It outperforms conventional d-SPE QuEChERS in matrix cleanup, recovery, precision and throughput, supporting routine high-capacity testing labs.

References

1. European Commission EU Pesticides Database (accessed 2019).
2. GB 2763-2019 Chinese National Food Safety Standard, Maximum Residue Limits for Pesticides in Food.
3. Anastassiades M. et al., J. Chromatogr. A, 2003, 1015, 163-184.
4. AOAC Method 2007.01, Acetonitrile Extraction and Partitioning for Pesticide Residues.
5. GB 23200.113-2018 Pesticide Residues by GC-MS/MS, China.
6. Morris B.D. and Schriner R.B., J. Agric. Food Chem., 2015, 63, 5107-5119.
7. EU SANTE/12682/2019 Guidance on Analytical Quality Control and Method Validation.