Analysis of 510 Pesticides in Black Pepper

Importance of the topic

The global use of black pepper in food production has led to widespread application of hundreds of pesticides, raising concerns over food safety and regulatory compliance. Black pepper is a challenging matrix for analysis due to its low moisture, high pigment, and complex co-extractives. An efficient, sensitive, and robust multiresidue method is essential for reliable quantitation of pesticide residues at levels that comply with international maximum residue limits (MRLs).

Objectives and study overview

This application note describes the development and validation of a comprehensive workflow to quantify 510 pesticide residues in black pepper. The goals were to:

• Implement a streamlined sample preparation combining QuEChERS EN extraction and sequential Captiva EMR cleanup cartridges.
• Couple this cleanup with high-performance LC/MS/MS in dynamic multiple reaction monitoring (dMRM) mode.
• Demonstrate method performance according to SANTE/11312/2021 guidelines for linearity, sensitivity, recovery, precision, and matrix effects.

Used methodology and procedure

The protocol begins with 0.5 g of ground dry pepper spiked or blank, followed by QuEChERS EN extraction with acetonitrile and acetic acid. After centrifugation, a measured aliquot is mixed with water/formic acid and passed sequentially through Captiva EMR–GPD (dry pigment cleanup) and EMR–GPF (fresh pigment cleanup) cartridges under controlled pressure. The eluent is dried and reconstituted, introducing a 22× dilution factor. Matrix-matched calibration standards at 0.25–100 μg/L ensure accurate quantitation.

Použitá instrumentace

• Agilent 1290 Infinity II LC system with ZORBAX Rapid Resolution HD Eclipse Plus C18 column
• Agilent 6470B triple quadrupole LC/MS with Jet Stream electrospray ion source operated in dMRM mode
• Agilent Bond Elut QuEChERS EN extraction kit, Captiva EMR–GPD and EMR–GPF cartridges
• Agilent PPM-48 positive pressure manifold, Geno/Grinder, Eppendorf centrifuge

Main results and discussion

The sequential EMR cleanup removed 47% of dried co-extractives and reduced LC/MS background by 39%, outperforming traditional dSPE methods. Over 85% of 510 analytes displayed calibration linearity (R²≥0.99) across the range from LOD to 50 or 100 μg/L. Method LODs were ≤1 μg/L for 97% of targets, meeting or exceeding EU MRL requirements. Recovery studies at 10 μg/kg (corresponding to ~0.45 μg/L) showed 75% of compounds within 40–120% recovery with RSDr ≤20%. Intra- and inter-batch precision demonstrated RSDr ≤20% for 80% of analytes and RSDiR ≤20% for 78% across two batches.

Benefits and practical applications

• Significant reduction of matrix effects enabling reliable quantitation in complex matrices.
• High throughput and simplified workflow avoiding multiple dSPE steps.
• Compatibility with routine QA/QC laboratories for regulatory compliance.
• Minimized instrument maintenance due to cleaner extracts.

Future trends and potential uses

The sequential EMR approach can be extended to other high-pigment or lipid-rich matrices such as spices, nuts, and processed foods. Advances in sorbent materials and automation may further reduce sample handling time. Integration with high-resolution MS could expand target lists and improve non-target screening capabilities.

Conclusion

This validated workflow combines QuEChERS extraction with Captiva EMR sequential cleanup and LC/MS/MS detection, delivering sensitive, accurate, and reproducible quantitation of 510 pesticides in black pepper. It meets stringent regulatory standards and offers a streamlined, robust solution for high-throughput pesticide residue analysis.

References

1. SANTE/11312/2021: Quality Control and Method Validation Procedures for Pesticide Residues Analysis in Food and Feed.
2. Agilent application note: Quantitative Analysis of Multiresidue Pesticides in Food Matrices Using Agilent 6470 LC/MS, 2022.
3. Agilent application note: Comprehensive LC/MS/MS Workflow of Pesticide Residues in Food, 2020.
4. EU Pesticides Database (v.2.2), 2022.