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Selecting the appropriate QuEChERS extraction method for pesticides in foods

Applications | 2018 | Thermo Fisher ScientificInstrumentation
Sample Preparation, Consumables
Industries
Food & Agriculture
Manufacturer
Thermo Fisher Scientific

Summary

Significance of the Topic


QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) sample preparation has become a cornerstone for multi-residue pesticide analysis in food matrices. By simplifying extraction and clean-up steps and maintaining high recoveries and reproducibility, QuEChERS addresses limitations of traditional methods that are often time-consuming, costly and labor-intensive.

Study Objectives and Overview


This application brief examines how to select the optimal QuEChERS extraction and clean-up protocol for various classes of pesticides and a range of food matrices. It provides guidance on matching extraction salts, dispersive SPE sorbents and sample scales to target analytes and matrix complexities.

Methodology


The approach begins with classifying pesticide analytes by their chemical sensitivity:
  • Acid-sensitive compounds (e.g., acephate, dimethoate) favor standard QuEChERS extraction (simple salts, clean baselines but lower recovery for base-sensitive analytes).
  • Base-sensitive analytes (e.g., folpet, captan) perform better with AOAC or buffered acetate protocols (sodium acetate enhances extraction but matrix removal may be less effective).
  • Analytes sensitive to both acid and base conditions may require a balanced European extraction protocol.
  • Planar pesticides (e.g., carbendazim, hexachlorobenzene) benefit from dual-layer SPE cartridges containing graphitized carbon black (GCB) and primary secondary amine (PSA) for improved recovery.
Clean-up sorbent selection is driven by matrix type:
  • General produce (apples, cucumber): MgSO4 + PSA to remove water, acids and sugars.
  • Fatty matrices (milk, cereals, fish): MgSO4 + PSA + C18 for additional lipid and sterol removal.
  • Pigmented produce (lettuce, carrot, wine): MgSO4 + PSA + C18 + GCB to eliminate pigments.
  • Highly pigmented samples (spinach, red peppers): Add Chlorofiltr™ for enhanced chlorophyll removal.
Sample and sorbent scales are recommended as follows:
  • 10 g sample with 4 g MgSO4 extraction salts.
  • 15 g sample with 6 g MgSO4 extraction salts.
  • For dispersive SPE tubes: 10 mL extract with 1.2 g MgSO4; 8 mL extract with 0.9 g MgSO4; 1 mL extract with 0.15 g MgSO4.

Instrumentation Used


The method employs Thermo Scientific™ HyperSep™ QuEChERS dispersive SPE products for extraction salt mixtures and clean-up sorbents.

Main Results and Discussion


By tailoring extraction protocols to analyte acid/base sensitivity and matrix composition, users can achieve cleaner baselines and higher recoveries across diverse pesticide chemistries. The study highlights that unbuffered QuEChERS excels for most acid-sensitive compounds, while buffered and dual-layer SPE formats are critical for base-sensitive or planar analytes. Sorbent combinations effectively mitigate co-extractives such as lipids, chlorophyll and pigments, preserving analytical performance.

Benefits and Practical Applications


  • Versatility across fruits, vegetables, dairy, cereals and wine.
  • Reduced solvent use and faster sample turnover.
  • High reproducibility and recovery supporting routine QA/QC and regulatory compliance.

Future Trends and Potential Applications


Emerging directions include:
  • Integration of QuEChERS with high-throughput LC-MS/MS workflows for trace-level screening.
  • Development of automated dispersive SPE formats for increased sample throughput.
  • Expansion into complex matrices such as nutraceuticals and environmental samples.

Conclusion


Optimizing QuEChERS extraction and clean-up protocols based on analyte and matrix characteristics ensures robust multi-residue pesticide analysis. The flexibility of HyperSep QuEChERS products supports a wide range of applications, enhancing efficiency and data quality in food safety laboratories.

Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.

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