AUTOMATING PREPARATION OF MATRIX-MATCHED CALIBRANTS

Significance of the Topic

The reliable preparation of matrix-matched calibrants is critical in quantitative pesticide residue analysis to ensure accurate results, minimize human error, and protect analyst safety.

Objectives and Study Overview

This study compares conventional manual pipetting with two automated approaches for preparing matrix-matched calibration standards: the Andrew+ pipetting robot and the SM-FTN Auto-Addition function on the ACQUITY UPLC Sample Manager. The goal is to evaluate improvements in accuracy, precision, time savings, and error reduction.

Methodology and Instrumentation

Two automation workflows were implemented:

• Andrew+ pipetting robot integrated with OneLab software for step-by-step experimental control and custom settings.
• SM-FTN Auto-Addition feature on the ACQUITY UPLC Sample Manager for automated mixing of multiple aliquots prior to UPLC-MS/MS injection.

Manual serial dilutions were performed in parallel for benchmark comparison.

Main Results and Discussion

Calibration curves generated by both methods showed excellent linearity (r2 = 0.999 for Andrew+ and r2 = 0.995 for manual pipetting). Key observations:

• Andrew+ robot achieved four-fold faster preparation than manual pipetting with reduced residual variance.
• Precision and reproducibility were superior in the automated approach, with lower relative standard deviations across most analytes.
• Auto-Addition mixing improved chromatographic peak shapes by introducing initial mobile phase during injection, enhancing solvent compatibility.

Benefits and Practical Applications

Automating calibrant preparation delivers:

• Significant reduction in hands-on time and repetitive strain risk.
• Minimized human error and improved data consistency.
• Enhanced laboratory productivity by reallocating analyst effort to critical tasks.

Future Trends and Opportunities

Ongoing advances may include integration of multi-solvent handling, real-time quality checks within automation platforms, and expanded workflows for diverse matrices. Coupling robotics with intelligent software will further streamline high-throughput laboratories and regulatory compliance.

Conclusion

The automated workflows using Andrew+ pipetting robot and SM-FTN Auto-Addition demonstrated comparable or superior performance to manual pipetting, delivering faster turnaround, higher reproducibility, and reduced error risk, thereby optimizing pesticide residue quantification.

References

1. Shah D, Wood J, Fujimoto G, McCall E, Hird S, Hancock P. Multiresidue Method for the Quantification of Pesticides in Fruits, Vegetables, Cereals and Black Tea using UPLC-MS/MS. Waters Application Note 720006886en. February 2021.
2. Trudeau M, Skinner N. Demonstration of LC-MS Nitrosamine Impurity Quantification Performance using Automated Sample Preparation with the Andrew+ Pipetting Robot. Waters Application Note 720007134en. January 2021.
3. Shah D, McCall E, Cleland G. Single LC-MS/MS Method for Confirmation and Quantification of Over 400 Pesticides in a Complex Matrix Without Compromising Data Quality. Waters Application Note 720005559en. January 2016.