Applying ‘MRM Spectrum Mode’ and Library Searching for Enhanced Reporting Confdence in Routine Pesticide Residue Analysis

Importance of the topic

Routine pesticide residue analysis demands high specificity and confidence to avoid false positive and false negative reporting. Traditional methods monitoring only 2–3 fragment ions can fail in complex matrices. Expanding multiple-reaction monitoring (MRM) to capture a broader set of fragment ions and adopting library searching improves compound verification and regulatory compliance.

Study objectives and overview

This work evaluates an enhanced ‘‘MRM Spectrum mode’’ workflow that acquires up to 10 fragment-ion transitions per pesticide and generates library-searchable spectra. The method was applied to the quantitation and confirmation of 193 pesticides using 1,291 MRM transitions. Performance was compared against a conventional approach using only 2 MRM transitions per analyte.

Methodology and instrumentation

Sample preparation employed established QuEChERS extraction of diverse commodity matrices (turmeric, plum, peppermint, parsnip, cherry, lime, pumpkin, tomato, potato). Final extracts in acetonitrile were co-injected with water to sharpen early peaks.

• UHPLC: Shimadzu Nexera system, HSS T3 column (100×2.1 mm, 1.7 µm), 40 °C, 0.4 mL/min.
• Mobile phase A/B: 5 mmol/L ammonium formate, 0.004 % formic acid (in water/methanol).
• Gradient: 35 % B (1.5 min) to 100 % B (11.5 min), re-equilibration to 3 % B by 13.01 min.
• Injection: 0.1 µL sample + 30 µL water.
• MS/MS: Triple quadrupole with ESI ±, polarity switch 5 ms, source 350 °C/300 °C/150 °C, gas flows 3/10/10 L/min.
• MRM Spectrum mode: 1,291 transitions (average 7–10 per compound), dwell 3 ms, pause 1 ms.
• Conventional method: 386 transitions (2 per compound), same timing.

Key results and discussion

MRM Spectrum mode achieved equivalent sensitivity, linearity, and repeatability to the conventional method despite a >3× increase in transitions. Examples include:

• Linuron: 9 transitions improved specificity with no loss of signal quality.
• Demeton-S-methyl sulphone: Library similarity scores ≥99 across matrices (tomato, cumin, pepper, potato, peppermint tea, turmeric).
• Desmedipham vs. phenmedipham: Distinct MRM spectra resolved co-eluting isomers and eliminated false positives.
• Carbendazim: Up to 12 fragment ions generated at various collision energies; calibration (0.010–0.200 mg/kg) yielded R² > 0.999 and library scores ≥98.

Benefits and practical applications

The MRM Spectrum workflow offers:

• Enhanced reporting confidence through library-matched spectra.
• Reduced false positives and negatives in complex matrices.
• Regulatory compliance with improved identification criteria beyond retention time and ion ratios.
• High throughput enabled by fast polarity switching and automated library searching.

Future trends and potential applications

Continued development may focus on:

• Expanding spectral libraries to cover emerging and degraded pesticide products.
• Integrating high-resolution MS for hybrid workflows.
• Applying machine-learning algorithms for automated spectral interpretation.
• Adapting the approach to other contaminant classes in food and environmental monitoring.

Conclusion

The enhanced MRM Spectrum mode combines broad fragment-ion acquisition with library searching to deliver reliable, high-confidence multi-residue pesticide analysis. It outperforms conventional MRM methods without sacrificing sensitivity or robustness, making it a valuable strategy for routine QA/QC laboratories seeking improved accuracy and reporting confidence.