Measurement uncertainty from physical sample preparation: estimation including systematic error.
A methodology is proposed, which employs duplicated primary sampling and subsequent duplicated physical preparation coupled with duplicated chemical analyses. Sample preparation duplicates should be prepared under conditions that represent normal variability in routine laboratory practice. The proposed methodology requires duplicated chemical analysis on a minimum of two of the sample preparation duplicates. Data produced from the hierarchical design is treated with robust analysis of variance (ANOVA) to generate uncertainty estimates, as standard uncertainties ('u' expressed as standard deviation), for primary sampling (ssamp), physical sample preparation (sprep) and chemical analysis (sanal). The ANOVA results allow the contribution of the sample preparation process to the overall uncertainty to be assessed. This methodology has been applied for the first time to a case study of pesticide residues in retail strawberry samples. Duplicated sample preparation was performed under ambient conditions on two consecutive days. Multi-residue analysis (quantification by GC-MS) was undertaken for a range of incurred pesticide residues including those suspected of being susceptible to loss during sample preparation procedures. Sampling and analytical uncertainties dominated at low analyte concentrations. The sample preparation process contributed up to 20% to the total variability and had a relative uncertainty (Uprep%) of up to 66% (for bupirimate at 95% confidence). Estimates of systematic errors during physical sample preparation were also made using spike recovery experiments. Four options for the estimation of measurement uncertainty are discussed, which both include and exclude systematic error arising from sample preparation and chemical analysis. A holistic approach to the combination and subsequent expression of uncertainty is advised.
Lyn
Jennifer A
JA
Centre for Environmental Research, School of Chemistry, Physics & Environmental Science, University of Sussex, Falmer, Brighton, UK BN1 9QJ.
Ramsey
Michael H
MH
Fussell
Richard J
RJ
Wood
Roger
R
D002138:Calibration; D003627:Data Interpretation, Statistical; D005506:Food Contamination / Q000032:analysis*; D005638:Fruit / Q000737:chemistry*; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods; D010573:Pesticide Residues / Q000032:analysis*; D012494:Sampling Studies; D012680:Sensitivity and Specificity; D035501:Uncertainty
D010573:Pesticide Residues