GC/MSD Pesticide Screening in Strawberries at Tolerance Levels Using Library Searching of Deconvoluted Spectra

Importance of the Topic

The presence of pesticide residues and environmental pollutants in fruits raises health and regulatory concerns. Strawberries, with their complex matrix, challenge analytical methods due to coeluting compounds. Reliable, non-targeted screening ensures consumer safety and compliance with tolerance limits.

Objectives and Study Overview

This work demonstrates a two-step workflow using an Agilent 8890 GC and 5977 GC/MSD system to screen over 1,000 pesticides in strawberries. The first step employs MassHunter Unknowns Analysis software for automated spectral deconvolution and library searching. Locally sourced strawberry samples were extracted and analyzed to evaluate detection capability at or below US EPA tolerance levels.

Instrumentation Used

• Agilent 8890 GC with fast oven and 8890 PSD module for controlled carrier gas flow
• Midcolumn backflush via Purged Ultimate Union to remove high-boiling matrix residues
• Multimode inlet configured for pulsed hot splitless injection with Ultra Inert low-pressure drop liner
• Two 15 m J&W HP-5ms Ultra Inert columns in series, retention-time locked to the pesticide library
• Agilent 5977 MSD with Inert Extractor EI source
• Agilent MassHunter Quantitative 10 Unknowns Analysis software
• RTL pesticide library (>1,000 compounds) and NIST 17 spectral library with RI calibration

Methodology

Samples underwent QuEChERS extraction: homogenization in liquid nitrogen, acetonitrile extraction, salt partitioning, and dispersive SPE cleanup. GC conditions included a 2 µL pulsed splitless injection at 50 psi, a 43.5 min temperature program with two ramps, and midcolumn backflush. MSD acquisition scanned 45–550 amu after a 4 min solvent delay. Automated spectral deconvolution isolated component spectra for library matching.

Main Results and Discussion

Automated deconvolution effectively removed matrix interferences, yielding high library match scores (LMS) and retention time agreement within 0.1 min. Screening against the RTL library identified over 20 pesticide residues, all confirmed at or below US EPA tolerances. Subsequent NIST 17 searches validated key hits and revealed additional compounds. Estimated detection limits ranged from 100 to 2,000 ppb, demonstrating sufficient sensitivity for regulatory compliance.

Benefits and Practical Applications

• Non-targeted approach detects hundreds of pesticides without preselection
• Automated deconvolution and retention time locking reduce false positives
• Midcolumn backflush extends column life and reduces maintenance
• Workflow compatibility with GC/MS/MS and GC/Q-TOF enables confirmatory analyses

Future Trends and Potential Uses

Integration of high-resolution MS and real-time data processing will advance non-targeted screening. Expanded and curated spectral libraries, machine learning for pattern recognition, and automated workflows promise faster, more accurate identification. Extending this approach to diverse food and environmental matrices will enhance comprehensive safety monitoring.

Conclusion

The Agilent 8890 GC and 5977 GC/MSD system, paired with MassHunter Unknowns Analysis, provides a robust, sensitive protocol for comprehensive pesticide screening in strawberries. Pulsed splitless injection, midcolumn backflush, and retention time locking enable reliable deconvolution and identification at or below regulatory tolerance levels, supporting routine food safety testing.

References

1. Westland J, Stevens J. An Optimal Method for the Analysis of Pesticides in a Variety of Matrices. Agilent Technologies Application Note 5991-7303EN, 2017.
2. Chen K, Nieto S, Stevens J. GC/Q-TOF MS Surveillance of Pesticides in Food. Agilent Technologies Application Note 5991-7691EN, 2017.
3. Andrianova A, Westland J, Quimby B. Quantitation of Pesticides in Strawberries at Tolerance Levels Established by the US EPA Using Agilent 8890/7000D and 8890/7010B Triple Quadrupole GC/MS Systems. Agilent Technologies Application Note 5994-0799EN, 2019.
4. US EPA. Index to Pesticide Chemical Names, Part 180 Tolerance Information, and Food and Feed Commodities. December 2012.
5. USDA AMS S&T MPD. Pesticide Data Program (PDP) Database Search Application – User Guide. January 2019.