An Optimal Method for the Analysis of Pesticides in a Variety of Matrices

Significance of the Topic

Pesticide monitoring is vital due to the extensive use of over a thousand compounds in agriculture and the associated risks to food safety and the environment. Complex sample matrices such as oils, teas or produce can generate interferences that challenge accurate detection and quantitation.

Objectives and Study Overview

This study aimed to develop and validate an optimal gas chromatography–tandem mass spectrometry method using matrix-optimized multiple reaction monitoring transitions for 195 target pesticides across eight representative matrices. It leverages Agilent’s comprehensive MRM database to enhance selectivity and throughput.

Methodology

A quEChERS sample preparation protocol was applied to categories including high oil (olive oil), high pigment (black tea, spinach), high starch (rice), high water (cucumber), high sugar (honey), high acid (orange) and clean (onion). Analysts selected the top five MRM transitions per compound based on signal response, ion ratios and selectivity, then refined to the best three or four transitions for matrix-specific methods.

Used Instrumentation

Agilent 7890B GC fitted with a multimode inlet (ultra‐inert liner) and two HP-5ms UI columns (15 m×0.25 mm×0.25 μm) coupled by a purged ultimate union. Agilent 7010 triple quadrupole GC/MS with backflush functionality, operated with electron ionization at 70 eV, source 300 °C, transfer line 280 °C, quadrupole 150 °C, and collision cell with N2/He gas.

Main Results and Discussion

Calibration was linear (0.12–50 pg/μL) with R2 ≥ 0.990 for 90 % of pesticides. Limits of quantitation ≤1.5 pg/μL and repeatability (RSD) ≤30 % were achieved. Matrix interferences caused shifts in quantifier and qualifier ion abundances, but selecting matrix-optimized MRMs restored signal clarity and maintained time segment scheduling. A representative comparison in honey and spinach demonstrated minimal errors (<~1 %) using optimized transitions.

Benefits and Practical Applications of the Method

• Enhanced selectivity and confidence in compound identification across diverse matrices.
• Improved quantitation accuracy and method robustness under complex sample conditions.
• Streamlined method development using a large prevalidated MRM database.
• Increased laboratory throughput and reduced reanalysis due to interferences.

Future Trends and Opportunities

Agilent plans to expand the database with 7,800 additional matrix-optimized transitions. Future work may integrate machine learning for automated transition selection, extend coverage to new pesticide classes, and support high-throughput regulatory and QA/QC laboratories.

Conclusion

The combination of an advanced GC/MS platform and a matrix-optimized MRM database provides a powerful solution for routine multi-residue pesticide analysis in complex matrices, ensuring reliable detection at low part-per-billion levels.

References

Agilent Technologies MassHunter Pesticide & Environmental Pollutant MRM Database, Revision A.01.01.