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Is measurement uncertainty from sampling related to analyte concentration?
Stephen L R Ellison1, Michael H Ramsey2, Paul Lawrance1
1LGC Limited, Queens Road, Teddington, Middlesex TW11 0LY, UK. s.ellison@lgcgroup.com.
Analytical Methods : Advancing Methods and Applications
|January 18, 2025
Summary
Sampling variability in foodstuffs generally follows a predictable pattern, similar to the Horwitz relationship. This finding helps estimate measurement uncertainty in food analysis more accurately.
Area of Science:
- Food Science
- Analytical Chemistry
- Metrology
Background:
- Accurate measurement is crucial in food analysis.
- Sampling variability significantly contributes to overall measurement uncertainty.
- Understanding this contribution is key to reliable food safety and quality assessments.
Purpose of the Study:
- To assess the contribution of sampling to measurement uncertainty in foodstuffs.
- To investigate a consistent relationship between analyte levels and sampling variability.
- To compare different data processing methods for sampling uncertainty.
Main Methods:
- Literature review combined with experimental determination of sampling variability.
- Utilized the duplicate method for assessing sampling and analytical variability.
- Conducted experimental sampling on retail foodstuffs, obtaining 101 variance estimates.
Main Results:
- Demonstrated a Horwitz-like relationship for sampling variance across the food sector.
- This relationship allows estimation of between-sample standard deviation within an order of magnitude.
- Log-transformation had minor effects; robust statistical methods had unpredictable effects on sampling variance.
Conclusions:
- Sampling uncertainty in food analysis exhibits predictable patterns.
- The established relationship aids in more accurate uncertainty estimation.
- Careful consideration of statistical methods is needed for robust sampling variance assessment.
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