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

Importance of the Topic

Routine monitoring of pesticide residues is critical for food safety and regulatory compliance. False positives and negatives in mass spectrometric analysis can undermine confidence in reported results and lead to costly investigative follow-ups.

Objectives and Study Overview

This study introduces an enhanced multiple-reaction monitoring (MRM) Spectrum Mode combined with library searching to improve specificity and reporting confidence in routine pesticide residue assays. The workflow was applied to quantify and identify 193 pesticides using 1,291 MRM transitions on a high-speed triple quadrupole LC-MS/MS platform and compared with a conventional 2-transition MRM method.

Methodology and Instrumentation

Sample Preparation

• Pesticide-spiked extracts from turmeric, plum, peppermint tea, parsnip, cherry, lime, pumpkin, tomato, potato, cumin, black pepper and Mucuna pruriens powder.
• QuEChERS-based extraction; direct injection in acetonitrile with water co-injection for improved early elution.

Liquid Chromatography

• UHPLC system: Shimadzu Nexera LC
• Column: HSS T3, 100 × 2.1 mm, 1.7 µm; 40 °C; 0.4 mL/min flow
• Mobile phases: 5 mmol/L ammonium formate with 0.004 % formic acid (A) and the same in methanol (B)
• Binary gradient: 35 % B at 1.5 min to 100 % B at 11.5 min; total run time 15 min
• Injection: 0.1 µL sample plus 30 µL water

Mass Spectrometry

• Triple quadrupole MS/MS with electrospray ionization (ESI+/-) and 5 ms polarity switching
• Dwell/pause times: 1 ms/3 ms per transition
• MRM Spectrum Mode: 1,291 transitions (1,229 in ESI+, 62 in ESI–) acquired in a single 15 min run

Key Results and Discussion

• MRM Spectrum Mode enabled acquisition of 6–12 qualifier transitions per pesticide, compared to 2–3 in conventional workflows.
• Library matching against reference spectra yielded similarity scores ≥99 for calibration levels from 0.010 to 0.200 mg/kg in multiple matrices.
• No compromise in limits of detection, linearity (R² > 0.999), repeatability or sensitivity despite high data density.
• High specificity reduced false positive/negative rates, illustrated by distinguishing isobaric compounds (e.g., desmedipham vs. phenmedipham) in complex matrices.

Benefits and Practical Applications

• Enhanced confidence in compound identification through library-searchable product ion spectra.
• Single-run quantitation and confirmation supporting regulatory requirements for retention time and ion ratio verification.
• High throughput capability allows routine screening of large pesticide panels without sacrificing data quality.
• Flexible application across diverse food and botanical matrices.

Future Trends and Potential Applications

• Expansion of spectral libraries to cover emerging contaminants and novel pesticides.
• Integration of machine learning algorithms for automated spectrum deconvolution and identification.
• Further multiplexing by combining MRM Spectrum Mode with high-resolution mass spectrometry.
• Standardization of library similarity scoring criteria across laboratories for harmonized reporting.

Conclusion

The adoption of MRM Spectrum Mode with library searching significantly enhances specificity and confidence in routine pesticide residue analysis. This approach maintains analytical performance metrics while reducing the risk of false results, supporting robust regulatory compliance and high-throughput laboratory operations.

Reference

1. Baker D, Titman C, Loftus N, Horner J. Applying ‘MRM Spectrum Mode’ and Library Searching for Enhanced Reporting Confidence in Routine Pesticide Residue Analysis. Shimadzu, Manchester, UK and Scientific Analysis Laboratories (SAL), Cambridge, UK.