DEVELOPMENT AND VALIDATION OF MULTI-RESIDUE PESTICIDES METHOD FOR ROUTINE ANALYSIS OF FOOD SAMPLES USING UPLC-MS/MS

Significance of the Topic

Routine monitoring of pesticide residues in food is essential to ensure compliance with Maximum Residue Limits set by regulatory authorities and to protect consumer health. Multi residue methods enable simultaneous detection of diverse analytes in complex matrices, increasing laboratory throughput and cost effectiveness.

Study Objectives and Overview

This study aimed to develop and validate a high throughput UPLC MS MS method for multi residue pesticide analysis in food commodities including high moisture vegetables and high starch matrices. Key objectives included assessment of sensitivity, linearity, limit of quantification, precision, matrix effects, and robustness in accordance with relevant guidelines.

Methodology and Instrumentation

Sample Preparation

• CEN QuEChERS extraction using acetonitrile and dispersive SPE cleanup for vegetables and rice
• Matrix matched standards prepared at various concentration levels for calibration and validation

Instrumental Setup

• UPLC system ACQUITY UPLC I Class PLUS with HSS T3 column at 45 ºC, injection volume 3 µl, run time 19 min
• Mass spectrometer Xevo TQ S cronos with electrospray ionization in positive and negative modes and rapid polarity switching
• Mobile phases consisting of 5 mM ammonium formate with formic acid in water and 50 50 acetonitrile methanol

Main Results and Discussion

The method achieved excellent linearity with correlation coefficients above 0.99 across representative pesticides. Limits of quantification were at or below the default MRL of 0.01 mg kg in both cucumber and rice matrices. Matrix effects remained within 20% for over 80% of compounds after matrix matched calibration. Repeatability and within lab reproducibility were below 20% RSD across multiple days. Robustness testing demonstrated system stability over more than 200 injections without user intervention.

Practical Benefits and Applications

• Meets regulatory guidelines for routine official control and due diligence testing
• Reduces sample turnaround time with high throughput capability
• Applicable to a broad range of food matrices and pesticide chemistries

Future Trends and Opportunities

Advances in high resolution mass spectrometry and automated sample preparation will further enhance multi residue analysis workflows. Integration with digital data processing and machine learning algorithms may improve compound identification and quantification in challenging matrices.

Conclusion

The validated UPLC MS MS method provides reliable, sensitive, and robust multi residue pesticide analysis suitable for routine food safety and quality control laboratories. Its performance aligns with international standards and supports efficient compliance monitoring.

References

No external references were provided in the source document.