Determination of Over 300 Pesticides in Cumin Powder

Importance of the Topic

The analysis of pesticide residues in spices is critical for food safety and regulatory compliance worldwide. Spices such as cumin can accumulate a broad range of pesticide contaminants due to agricultural practices. Reliable multiresidue analysis ensures consumer protection, supports international trade, and helps laboratories meet stringent limits set by agencies such as the EU and Codex Alimentarius.

Study Objectives and Overview

This work aimed to develop and validate a unified workflow for detecting over 300 pesticide compounds in cumin powder. Key goals included:

• Efficient extraction of both polar and nonpolar pesticides.
• Selective removal of matrix interferences from complex spice material.
• Accurate quantitation by LC/MS/MS and GC/MS/MS.
• Assessment of method performance metrics: recovery, precision, matrix effects, calibration linearity, and limits of quantitation.

Methodology and Instrumentation

Sample preparation combined QuEChERS extraction with a novel passthrough cleanup:

1. Weigh 2 g of cumin powder; spike with native and isotopically labeled standards.
2. Add water and acetonitrile (1% acetic acid), shake and centrifuge.
3. Apply supernatant to Agilent Captiva EMR–LPD cartridge for selective matrix removal.
4. Dry with MgSO₄, centrifuge, then dilute 5× for LC/MS/MS or inject directly for GC/MS/MS.

Instrument platforms:

• LC/MS/MS: Agilent 1290 Infinity II LC coupled to 6490 triple quadrupole with Jet Stream ESI, using a ZORBAX Eclipse Plus C18 column and gradient of ammonium formate/ammonium fluoride in water and ACN.
• GC/MS/MS: Agilent 8890 GC with 7000E triple quadrupole, HP-5ms UI columns in mid-column backflush, multimode inlet, dynamic MRM acquisition.

Main Results and Discussion

Matrix cleanup performance:

• Captiva EMR–LPD removed approximately 60% of co-extractives, improving extract clarity compared to traditional dSPE.
• Visual inspection and GC total ion chromatograms confirmed reduced background noise.

Recovery and precision:

• LC-amenable pesticides (126 compounds): >95% of targets achieved 70 – 120% recovery, and >97% showed RSD < 20% at 10 and 100 ng/g spiking levels.
• GC-amenable pesticides (201 compounds): similar performance trends with high reproducibility.

Matrix effects and calibration:

• Over 80% of LC targets exhibited matrix effects within 60 – 130%.
• Matrix-matched calibration from 2.5 – 2,500 ng/g (0.5 – 500 ng/mL extract) yielded R² > 0.99 for 90.5% of pesticides.

Benefits and Practical Applications

The proposed method offers:

• Simplified workflow with fewer manual steps and improved throughput.
• High recovery and precision across a large multiresidue panel.
• Reduced solvent use and waste compared to conventional cleanup.
• Applicability in routine regulatory and QA/QC laboratories.

Future Trends and Opportunities

Advances may include:

• Automation of extraction and cleanup to further increase throughput.
• Integration of high-resolution mass spectrometry for broadened analyte coverage.
• Expansion to simultaneous analysis of mycotoxins and other emerging contaminants.
• Use of machine learning for data processing and interference identification.

Conclusion

A combined QuEChERS and Captiva EMR–LPD passthrough cleanup approach effectively enables the simultaneous analysis of over 300 pesticides in challenging cumin matrices by LC/MS/MS and GC/MS/MS. The method demonstrates strong performance in terms of recovery, precision, matrix effects, and calibration linearity, making it well-suited for high-throughput, regulatory compliance testing.

References

1. European Commission SANTE/11312/2021: Analytical Quality Control and Method Validation Procedures for Pesticide Residues in Food and Feed.
2. Lacina et al., J. Chromatogr. A 2012, 1262, 8–18.
3. Parmar et al., J. Sci. Food Agric. 2022, 102, 1782–1811.
4. Zhao & Andrianova, Agilent Technologies Application Note 5994-5630EN, 2023.
5. Zhao & Andrianova, Agilent Technologies Application Note 5994-5671EN, 2023.
6. Andrianova & Zhao, Agilent Technologies Application Note 5994-4965EN, 2022.
7. Zhao, Agilent Technologies Application Note 5994-4767EN, 2022.