Design of Experiment (DoE) and GERSTEL MultiPurpose Sampler (MPS): a match made in heaven

Significance of the topic

Design of Experiment (DoE) integrated with automated sample preparation addresses critical challenges in analytical chemistry by enabling simultaneous variation of multiple factors, reducing experimental efforts, and improving method robustness. When applied to derivatisation workflows, such as fatty acid conversion to picolinyl esters, DoE accelerates optimization and yields reliable structural information for complex mixtures.

Objectives and study overview

The study aimed to develop and optimize an automated workflow for picolinyl derivatisation of fatty acids using a GERSTEL MultiPurpose Sampler (MPS) and GC-MS. Key goals included identifying significant process variables, establishing optimum conditions, and evaluating method precision and reproducibility.

Methodology and experimental design

Three DoE phases were applied:

• Scoping (pilot trials): Four factors (reagent volume, mixing speed, temperature, time) tested at low, center, and high levels to assess variability and linearity.
• Screening (full factorial design): A 2⁴ design plus three center points (19 runs) identified temperature as the most significant factor influencing derivatisation yield.
• Optimization (central composite design): A response surface approach refined factor settings, revealing quadratic effects and defining an optimal operating region.

Instrumentation used

• Autosampler: GERSTEL MPS xt Dual Rail with 10 µL and 250 µL syringes
• Modules: Agitator, MultiPosition Vortexer, MultiPosition Evaporation station, Anatune CF-200 Robotic Centrifuge
• GC-MS: Agilent 7890B GC coupled to 5975C MSD, HP-35MS column (30 m × 0.25 mm × 0.25 µm), pulsed splitless injection, EI ion source

Key results and discussion

Scoping trials demonstrated significant response variation across factor levels with acceptable variability (≤20% RSD). Screening identified temperature as the primary driver, while response surface profiling optimized all factors for multiple fatty acid analytes. Six replicate injections over two days yielded repeatability (2–20% RSD) and reproducibility (6–24% RSD).

Benefits and practical applications

• Resource efficiency: fewer experiments and shorter development times.
• Enhanced precision: systematic factor evaluation reduces variability.
• Structural elucidation: picolinyl esters provide detailed mass spectral information on double bonds and branching.
• Automation: minimized operator bias and improved throughput via online PrepAhead scheduling.

Future trends and applications

Emerging opportunities include integration of DoE-driven automation with high-throughput screening, coupling to advanced MS detectors, real-time data analytics for adaptive experimentation, and broader use in quality control and metabolomics.

Conclusion

The combination of DoE and a fully automated GERSTEL MPS-GC-MS platform enables a robust, time-effective workflow for fatty acid picolinyl derivatisation. This approach yields high-quality structural data and reproducible results, streamlining method development in industrial and research laboratories.

References

Not applicable.