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Related Experiment Videos

Measurement uncertainty from physical sample preparation: estimation including systematic error.

Jennifer A Lyn1, Michael H Ramsey, Richard J Fussell

  • 1Centre for Environmental Research, School of Chemistry, Physics & Environmental Science, University of Sussex, Falmer, Brighton, UK BN1 9QJ.

The Analyst
|January 1, 2004
PubMed
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This study introduces a new method for estimating measurement uncertainty in chemical analysis, crucial for accurate pesticide residue testing in food. The approach quantifies variability from sampling, sample preparation, and analysis, revealing preparation

Area of Science:

  • Analytical Chemistry
  • Food Safety Analysis
  • Measurement Science

Background:

  • Accurate measurement uncertainty is vital for reliable food safety testing.
  • Traditional methods may not fully capture variability introduced during sample preparation.
  • Assessing the contribution of each step to overall uncertainty is crucial for method improvement.

Purpose of the Study:

  • To propose and validate a methodology for estimating measurement uncertainty in chemical analysis.
  • To assess the contribution of primary sampling, physical sample preparation, and chemical analysis to total uncertainty.
  • To apply the methodology to pesticide residue analysis in retail strawberry samples.

Main Methods:

  • Employed duplicated primary sampling, physical preparation, and chemical analyses in a hierarchical design.

Related Experiment Videos

  • Utilized robust analysis of variance (ANOVA) to estimate standard uncertainties for each step.
  • Applied the methodology to multi-residue pesticide analysis in strawberries using GC-MS.

    • Main Results:

    • Developed a robust ANOVA approach to quantify uncertainty components (sampling, preparation, analysis).
    • Sample preparation contributed up to 20% to total variability, with relative uncertainty up to 66% for specific analytes.
    • Sampling and analytical uncertainties were dominant at low analyte concentrations.

    Conclusions:

    • The proposed methodology effectively estimates measurement uncertainty, highlighting the significant impact of sample preparation.
    • A holistic approach to combining and expressing uncertainty, including systematic errors, is recommended.
    • This method provides a comprehensive assessment for improving accuracy in food analysis.