Practical and Valid Guidelines for Realistic Estimation of Measurement Uncertainty in Pesticide Multi-Residue Analysis*

Transcription

1 Practical and Valid Guidelines for Realistic Estimation of Measurement Uncertainty in Pesticide Multi-Residue Analysis* Antonio Valverde Pesticide Residue Research Group University of Almería * This presentation is an extract of the following publication: Antonio Valverde. Practical and Valid Guidelines for Realistic Estimation of Measurement Uncertainty in Pesticide Multi-Residue Analysis. In Multi-residue Methods for Pesticide Trace Analysis in Foods, H. Heizen, L. Nollet & A.R. Fernandez-Alba (Eds.), CRC Press (Taylor & Francis Group), Boca Raton, Florida, 016 (in press).

2 Practical and Valid Guidelines for Realistic Estimation of Measurement Uncertainty in Pesticide Multi-Residue Analysis - Introduction - Measurement Uncertainty and Confidence in a Test Result - Bottom-up and Top-down Evaluations - EURACHEM and CODEX Guidelines - CODEX Guidelines Amendment Sample Preparation (homogeneity) Uncertainty Component - Use of Uncertainty for Compliance Decisions

3 GUM Fundamentals GUM (BIPM, IEC, IFCC, ISO, IUPAC, OIML) Guide to the Expression of Uncertainty in Measurement (ISO, Geneva, Reprinted 1995 Reissued as ISO Guide 98-3, 008) A parameter associated with the result of a measurement, that characterises the dispersion of the values that could reasonably be attributted to the measurand - Uncertainty is seen from a positive point of view. - A realistic uncertainty statement always improve the quality of the result. - Transparent, simple and standardised procedure for evaluation / expression. - Type A and Type B evaluations (do not use random and systematic errors!). - Combined Standard Uncertainty (u c ) / Expanded Uncertainty (U).

4 This parameter may be: Measurement Uncertainty A standard deviation (combined standard uncertainty u c ) The width of a confidence interval (expanded uncertainty U ) U = k. u c (usualy, 95% confidence with k = ) If the dispersion attributed to the measurand is a NORMAL DISTRIBUTION: (U = k x u c ) Expanded Uncertainty (U) Standard Uncertainty (u c ) (k = ) ~ 95 % Reported Result

5 Reporting a Result with its Uncertainty Result with a previously fixed level of confidence Result = Value expanded uncertainty (k = ; 95%) A Realistic Pesticide Residue Test Result mg/kg (k = ; 95%) from 0.55 to 1.15 mg/kg! The estimated uncertainty must be realistic and reliable for the intended purpose, if not the result has no value!!! 0.85 ± 0.01 mg/kg

6 Reporting a Result 1.4 Value with Precision (without uncertainty evaluation) with Uncertainty evaluation K = (95%) 1. mg kg

7 Quality of ( Confidence in) the Result Standard Uncertainty (u c ) 0.85 mg/kg (~.5%) just the Value ± 0.10 mg/kg (~ 50%) 0.85 ± 0.30 mg/kg (95%) previously fixed Confidence Level Reported Result with precision ± 0.10 mg/kg with expanded uncertainty, k= (U = k x u c )

8 Uncertainty Analytical Measurement Guidelines EURACHEM / CITAC Guide CG 4 (QUAM:01.P1) Quantifying Uncertainty in Analytical Measurement (3 rd Edition, 01) NORDTEST Technical Report TR537 Handbook for Calculation of Measurement Uncertainty in Environmental Laboratories (003) EUROLAB Technical Report No. 1/00 Measurement Uncertainty in Testing (00) EUROLAB Technical Report No. 1/006 Guide to the Evaluation of Measurement Uncertainty for Quantitative Test Results (006) EUROLAB Technical Report No. 1/007 Measurement Uncertainty Revisited: Alternative Approaches to Uncertainty Evaluation (007)

9 Guidelines - Codex Alimentarius Specific Guidelines for Pesticide Residue Analysis (Codex Committee on Pesticide Residues - CCPR) CAC/GL Guidelines on Estimation of Uncertainty of Results CCPR 43 rd Session (Beijing, P.R. China, 4-9 April 011) Amendment 011 Introduction of an ANNEX with some examples on practical aproaches for the estimation of uncertainty of results in pesticide residue tests (CX/PR 11/43/10)

10 EUROLAB road map for uncertainty estimation approaches (modified for Multiresidue Analysis of Pesticides) Default-Fixed Fit-For-Pourpose Value Scientific judgements previous experience Horwitz Equation concentration -dependent bottom-up top-down

11 ISO/IEC 1705: Technical requirements 5.4. Test methods and method validation Estimation of uncertainty of measurement Testing laboratories shall have and shall apply procedures for estimating uncertainty of measurement. In certain cases the nature of the test method may preclude rigorous, metrologically and statistically valid, calculation of uncertainty of measurement No doubt, pesticide multi-residue analysis is one of these cases!!!

12 EURACHEM/CITAC Guide CG 4 (QUAM:01.P1) Quantifying Uncertainty in Analytical Measurement (3 rd Edition, 01) Example A4 Uncertainty Estimation from In-House Validation Studies Determination of Organophosphorous Pesticides in Bread Obtaining an overall uncertainty estimate by evaluation of a representative selection of typical pesticides on a wide variety of matrices and levels representing the overall scope of the method!!!

13 Homogenise Organophosphorus Pesticides Analysis Antonio Valverde Measurand: P op I ref I op c Rec ref V m op sample F hom F I (mg/kg) Extraction Clean-Up Bulk Up GC Determination Prepare Calibration Standard GC Calibration P op : Level of pesticide in the sample (mg kg -1 ) I op : Peak intensity of the sample extract c ref : Mass concentration of the reference standard (µg ml -1 ) V op : Final volume of the extract (ml) I ref : Peak intensity of the reference standard Rec: Recovery m sample : Mass of the investigated sub-sample (g) F hom : Correction factor for sample inhomogeneity F I : Correction factor for intermediate precision RESULT

14 CAC/GL Antonio Valverde Measurement Uncertainty of the Laboratory Standard Deviation ( S L ) or Relative Standard Deviation (CV L ) (SP) Sample Preparation CV SP Analytical step (A) Extracción Extraction CV A Clean-up GC LC NPD - FPD - PFPD - ECD MS UV/DAD Fluorescencia

15 Guidelines - Codex Alimentarius CAC/GL Guidelines on Estimation of Uncertainty of Results - Sampling (CV S ) - Sample Preparation (CV SP ) - Analytical step (CV A ) - Laboratory (CV L ) EURACHEM / CITAC Guide CG 4 (QUAM:01.P1) CV SP CV A u c = u hom + u rep + u bias

16 CAC/GL Amendment 011 (Annex) 3 Intra-Laboratory Validation/QC/PTs Data u = (u Rw + u bias ) 1/ Relative intra-laboratory reproducibility SD (QC) ( (bias) /n) 1/ a (u bias ) PT Root Mean Square of relative PTs bias & u (C ref ) PT b (u bias ) QC No-correction Root Mean Square of relative QC bias & u (C ref ) QC c (u bias ) QC Mean Rec. Correction u (Mean Rec.) QC & u (C ref ) QC u Rw / n 1/

17 CAC/GL Amendment 011 (Annex) 1 Default-Fixed Value (50% / EU) Concentration-Dependent Formula (HORWITZ) C (kg/kg) U = k. RSD R

18 CAC/GL (Annex) Reporting a Result of 0.40 mg/kg Expanded K = (95%) U = 37% HORWITZ U = 50% Default-Fixed (EU) U = 40% U = 50% U = 31% u = (u Rw + u bias ) 1/ (u bias ) PT 13.5% (u bias ) QC No-correction 0% (u bias ) QC Rec. Correction 4% Standard mg kg Internal QC Recovery data (3 months) n = 14; Mean Rec = 86%; RSD = u Rw = 15%

19 Practical and Valid Guidelines for Realistic Estimation of Measurement Uncertainty in Pesticide Multi-Residue Analysis of Pesticides - Introduction - Measurement Uncertainty and Confidence in a Test Result - Bottom-up and Top-down Evaluations - EURACHEM and CODEX Guidelines - CODEX Guidelines Amendment Sample Preparation (homogeneity) Uncertainty Component - Use on Uncertainty for Compliance Decisions

20 Sample Preparation (homogeneity) Uncertainty Component CAC/GL Guidelines on Estimation of Uncertainty of Results - Sampling (CV S ) - Sample Preparation (CV SP ) - Analytical step (CV A ) - Laboratory (CV L ) Usualy, not included in the uncertainty evaluations!!! EURACHEM / CITAC Guide CG 4 (QUAM:01.P1) CV SP CV A u c = u hom + u rep + u bias

21 Sample Preparation (homogeneity) Uncertainty Component Usualy, not included in the uncertainty evaluations (3) (4) (6) (7) (8) CV A (1) () CV L CV SP SP L CV C V - C V A (1) () The uncertainty resulting from the procedures applied to a laboratory sample to obtain the test portion may be an important component of the combined uncertainty of the laboratory

22

23 Many thanks for your attention!