Advantages of Reversed Sandwich Injection for Pesticide Residue Analysis

Importance of Topic

Accurate measurement of pesticide residues in diverse food commodities is vital for consumer safety and regulatory compliance. Matrix effects in complex samples like oils, teas, leafy greens, and honey can bias results, requiring laborious preparation of matrix-matched calibration standards. The reversed sandwich injection technique streamlines this process by automating the introduction of sample, matrix, and internal standard in a single syringe draw, improving quantitation, reducing manual effort, and minimizing errors.

Goals and Overview of the Study

This work evaluates the Agilent 7693A ALS Reversed 3-Layer Switch sandwich injection for trace pesticide analysis in four representative food matrices: extra virgin olive oil, black loose leaf tea, fresh spinach leaves, and organic honey. Objectives included comparing injection orders, assessing calibration linearity, precision, and sensitivity, and demonstrating how automated layering can replace traditional matrix-matched standard preparation.

Methodology and Instrumentation

• Sample Preparation
  • QuEChERS extraction tailored to each matrix
  • Dispersive SPE cleanup using EN salts and specific dSPE sorbents
• Sandwich Injection
  • Reversed 3-Layer Switch mode (L3: matrix, L1: analyte sample, L2: internal standard)
  • Total injected volume 3.6 µL with 0.2 µL air gaps
• Chromatography and Detection
  • Agilent 7890B GC with Multimode Inlet, splitless ultra-inert liner, backflushing via a purged ultimate union
  • Agilent 7010A Triple Quadrupole GC/MS in dynamic MRM mode
  • Helium carrier gas at 1 mL/min, oven temperature program ramping from 60 °C to 310 °C

Main Results and Discussion

• Injection Order Impact
  • Drawing the matrix as the bottom layer (last aspirated) yielded higher area responses across most pesticides compared to when it was the top layer.
  • Enhanced coating of active inlet sites by matrix reduced analyte adsorption and improved signal linearity.
• Calibration Performance
  • Over 85 % of 50+ target pesticides in each matrix achieved R² ≥ 0.991 across 1.25–62.5 ppb.
  • Precision at 1.25 ppb showed %RSD ≤ 30 % for all compounds; many were below 10 % when matrix was bottom layer.
  • Limit of quantitation (LOQ) ≤ 0.1 ppb for 85 % of pesticides.

Benefits and Practical Use of the Method

• Eliminates the need for multiple matrix-matched calibration preparations.
• Reduces sample handling time, reagent consumption, and potential for human error.
• Flexibility to include internal standards, derivatizing agents, or protectants directly in the injection sequence.
• Simplifies routine workflows and increases laboratory throughput.

Future Trends and Potential Uses

• Integration with high-throughput robotic systems for large-scale monitoring programs.
• Application to other analyte classes (veterinary drugs, environmental pollutants) requiring matrix-matched quantitation.
• Further refinement of injection layering strategies to accommodate complex multistep chemistries.
• Combination with next-generation high-resolution MS for simultaneous targeted and non-targeted screening.

Conclusion

The Agilent 7693A ALS Reversed 3-Layer Switch sandwich injection significantly enhances the quantitative analysis of trace pesticides in diverse food matrices. By automating matrix-sample-ISTD layering, the method delivers robust calibration, superior precision, sub-ppb LOQs, and streamlined workflows, making it a powerful tool for regulatory labs and research settings.

References

• Zhao L, Szelewski M. Analysis of Fruit and Vegetable Pesticides by GC/MS/MS Using Agilent Inert Flow Path. Agilent Technologies Application Note 5991-3234EN (2013).
• Wylie P. Using Sandwich Injections to Add Matrix, Internal Standards and/or Analyte Protectants for GC/Q-TOF Analysis of Pesticides. Agilent Presentation O-29 at NACRW (2016).
• Anastassiades M, Lehotay SJ, Stajnbaher D, Schenck FJ. J. AOAC Int. 86:412–431 (2003).
• Lehotay SJ, Mastovská K, Lightfield AR. J. AOAC Int. 88:615–629 (2005).
• Westland J, Stevens J. An Optimal Method for the Analysis of Pesticides in a Variety of Matrices. Agilent Technologies Application Note 5991-7303EN (2016).