Automating Preparation of Matrix-Matched Standards for Pesticide Residue Analysis Using the Andrew+ Pipetting Robot

Importance of the Topic

The accurate quantification of pesticide residues in food matrices is critical for regulatory compliance and consumer safety. Matrix effects in multi-residue analyses can compromise sensitivity and accuracy when using LC-MS/MS or GC-MS/MS. Preparing calibration standards in a blank extract of the sample matrix (matrix-matched calibration) mitigates these effects but is labor intensive and prone to human error and repetitive strain injury. Automating this step enhances data quality, throughput, and traceability while reducing analyst workload.

Objectives and Study Overview

This study evaluates the performance of the Andrew+ Pipetting Robot controlled by the cloud-native OneLab Software Platform for fully automating the preparation of matrix-matched standards for pesticide residue analysis. A comparative assessment against manual pipetting by an experienced analyst was conducted, focusing on calibration graph quality, preparation time, and operational consistency.

Methodology and Instrumentation

A QuEChERS extract of apple was spiked with 20 representative pesticides at five concentration levels. Standards were prepared in duplicate into water/acetonitrile (9:1) to match mobile phase conditions. The automated workflow was designed in OneLab, with solvent-specific aspiration speeds and air-cushion settings for organic solvents to prevent dripping. The Andrew+ Pipetting Robot executed the protocol unattended. Resulting standards were analyzed by LC-MS/MS using a typical UPLC–MS/MS method and bracketed calibration.

Used Instrumentation

• Andrew+ Pipetting Robot with Domino accessories and electronic pipettes
• OneLab Software Platform for protocol design and traceability
• ACQUITY UPLC I-Class PLUS System
• Xevo TQ-XS Triple Quadrupole Mass Spectrometer
• MassLynx MS Software and TargetLynx for data processing

Key Results and Discussion

Calibration curves generated from automated and manual preparations exhibited similar coefficients of determination (r2): 0.998 for automated vs. 0.996 for manual. Automated standards showed reduced residuals, particularly at low concentration levels, indicating improved fit and quantification accuracy. The robot completed preparation of six concentration levels in duplicate in under 14 minutes, compared to over 35 minutes manually. Automation also ensured full traceability through script recording and minimized the risk of pipetting errors.

Benefits and Practical Applications

• Fully unattended preparation in less than 14 minutes
• Minimal training required to design and execute protocols
• High accuracy and precision in pipetting results
• Reduction of repetitive strain injury risk
• Improved traceability and error avoidance
• Freed analyst time for higher-value tasks

Future Trends and Opportunities

• Evaluation of accuracy and precision across broader solvent and commodity matrices
• Integration with laboratory information management systems (LIMS) for end-to-end data management
• Expansion of automated workflows to include sample cleanup and derivatization steps
• Incorporation of artificial intelligence for dynamic protocol optimization

Conclusion

The automated preparation of matrix-matched standards using the Andrew+ Pipetting Robot and OneLab Software delivers comparable or improved calibration performance relative to manual pipetting. Significant time savings, enhanced traceability, and reduced human error make this approach a valuable enhancement to routine pesticide residue analysis workflows.

References

1. EURL-FV. Validation of MRM Pesticides from the Working Document SANCO/12745/2013 using Three Multiresidue Methods (QuEChERS, Swedish ethyl acetate, and Dutch mini-Luke). 2019.
2. Ross E, Meruva NM, Skinner N. Improving Method Reproducibility and Efficiency in Food Testing: How Can Liquid Handling Automation Help? Waters White Paper. August 2021.
3. 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.