Disseminating traceability in chemical measurement: Principles of a new EURACHEM/CITAC guide

Accreditation and Quality Assurance -     

Second edition of the EURACHEM Guide Quantifying Uncertainty in Analytical Measurement

Accreditation and Quality Assurance -     

Uncertainty from sampling in measurements of aflatoxins in animal feedingstuffs: application of the Eurachem/CITAC guidelines

The duplicate method for estimating uncertainty from measurement including sampling is presented in the Eurachem/CITAC guide. The applicability of this method as a tool for verifying sampling plans for mycotoxins was assessed in three case studies with aflatoxin B(1) in animal feedingstuffs. Aspects considered included strategies for obtaining samples from contaminated lots, assumptions about distributions, approaches for statistical analysis, log(10)-transformation of test data and applicability of uncertainty estimates. The results showed that when duplicate aggregate samples are formed by interpenetrating sampling, repeated measurements from a lot can be assumed to approximately follow a normal or lognormal distribution. Due to the large variation in toxin concentration between sampling targets and sometimes very large uncertainty arising from sampling and sample preparation (U(rel) ≥ 50%), estimation of uncertainty from log(10)-transformed data was found to be a more generally applicable approach than application of robust ANOVA.     

Uncertainty profiles for the validation of analytical methods

This article aims to expose a new global strategy for the validation of analytical methods and the estimation of measurement uncertainty. Our purpose is to allow to researchers in the field of analytical chemistry get access to a powerful tool for the evaluation of quantitative analytical procedures. Indeed, the proposed strategy facilitates analytical validation by providing a decision tool based on the uncertainty profile and the β-content tolerance interval. Equally important, this approach allows a good estimate of measurement uncertainty by using data validation and without recourse to other additional experiments.In the example below, we confirmed the applicability of this new strategy for the validation of a chromatographic bioanalytical method and the good estimate of the measurement uncertainty without referring to any extra effort and additional experiments. A comparative study with the SFSTP approach [1] showed that both strategies have selected the same calibration functions.The holistic character of the measurement uncertainty compared to the total error was influenced by our choice of profile uncertainty. Nevertheless, we think that the adoption of the uncertainty in the validation stage controls the risk of using the analytical method in routine phase.     

Uncertainty budget and validation of NAA using Reference Materials

Instrumental neutron activation analysis (INAA) has been used at the research reactor of the Institute of Nuclear Techniques for measuring different types of samples for many years. For standardization purposes, the single comparator method has been applied. Since the theoretical basis of NAA is well understood, the sources of uncertainty can be well estimated, detailed uncertainty calculations have been recently performed to meet the increasing demands for method validation. INAA was validated by the analyses of sets of reference materials (RM), selectivity was controlled, accuracy and precision of the method as well as linearity, detection limits and measuring ranges were determined. Under the conditions of QA/QC, NAA can meet the high demands of trace element analysis. This revised version was published online in August 2006 with corrections to the Cover Date.     

The 1993 ISO Guide to the Expression of Uncertainty in Measurement Applied to NAA

Principles of the expression of uncertainty in measurements are briefly reviewed and special aspects of the uncertainty quantification in NAA are discussed in detail regarding the relative and k ₀-standardization in both modes of the technique, i.e., INAA and RNAA. A survey of uncertainty sources is presented and calculation of the combined uncertainty is demonstrated by an example of manganese determination in biological material by RNAA.     

Extraction, interpretation and validation of information for comparing samples in metabolic LC/MS data sets

LC/MS is an analytical technique that, due to its high sensitivity, has become increasingly popular for the generation of metabolic signatures in biological samples and for the building of metabolic data bases. However, to be able to create robust and interpretable (transparent) multivariate models for the comparison of many samples, the data must fulfil certain specific criteria: (i) that each sample is characterized by the same number of variables, (ii) that each of these variables is represented across all observations, and (iii) that a variable in one sample has the same biological meaning or represents the same metabolite in all other samples. In addition, the obtained models must have the ability to make predictions of, e.g. related and independent samples characterized accordingly to the model samples. This method involves the construction of a representative data set, including automatic peak detection, alignment, setting of retention time windows, summing in the chromatographic dimension and data compression by means of alternating regression, where the relevant metabolic variation is retained for further modelling using multivariate analysis. This approach has the advantage of allowing the comparison of large numbers of samples based on their LC/MS metabolic profiles, but also of creating a means for the interpretation of the investigated biological system. This includes finding relevant systematic patterns among samples, identifying influential variables, verifying the findings in the raw data, and finally using the models for predictions. The presented strategy was here applied to a population study using urine samples from two cohorts, Shanxi (People's Republic of China) and Honolulu (USA). The results showed that the evaluation of the extracted information data using partial least square discriminant analysis (PLS-DA) provided a robust, predictive and transparent model for the metabolic differences between the two populations. The presented findings suggest that this is a general approach for data handling, analysis, and evaluation of large metabolic LC/MS data sets.     

Uncertainty in chemical analysis and validation of the analytical method: acid value determination in oils

Quantifying uncertainty in chemical analysis, according to EURACHEM document (1995), is based on known relationships between parameters of the analytical procedure and corresponding results of the analysis. This deterministic concept is different from the cybernetic approach to analytical method validation, where the whole analytical procedure is a "black box". In the latter case, analytical results only are the basis for statistical characterization of the method without any direct relationship with intermediate measurement results like weighings, volumes, instrument readings, or other parameters like molecular masses. This difference requires the harmonization of parameters to be validated and to be included in the uncertainty calculation. As an example, results of the uncertainty calculation and validation are discussed for a new method of acid value determination in oils by pH measurement without titration.     

Interpretation of geochemical data by the use of multivariate data analysis

Different strategies of multivariate data analysis are used to interpret a data base from geological samples. Cluster and correspondence analysis are applied to classify properly 34 chemical elements from 10 representative rock samples (volcanic series from Borovitsa, Rhodopa mountains, Bulgaria). Principal components analysis is also used as display method to visualize the relation between the variables and objects of interest. The multivariate data analysis applied makes it possible to interpret the origin and orogenesis of the samples.     

Practical digest for evaluating the uncertainty of analytical assays from validation data according to the LGC/VAM protocol

The estimation of the measurement uncertainty of analytical assays based on the LGC/VAM protocol from validation data is fully revisited and discussed in the light of the study of precision, trueness and robustness.     

Complementary use of inter-laboratory certification study data

The agreed purpose of an inter-laboratory certification study is to characterise a certified reference material (CRM). In addition to this, any (successful) certification study may also be utilised as a laboratory/method performance study by the participants. The intention of this note is to emphasise the complementary use of certification study data by the participants of the certification study and to explain the options involved. On this occasion, an apparent paradox arising in the interpretation of certification study data is resolved. The procedures for bias correction and estimation of bias-related uncertainty contributions discussed on this occasion are, however, generally applicable to normal CRM use. Received: 4 February 1999 / Revised: 16 July 1999 / Accepted: 21 July 1999     

Complementary use of inter-laboratory certification study data

The agreed purpose of an inter-laboratory certification study is to characterise a certified reference material (CRM). In addition to this, any (successful) certification study may also be utilised as a laboratory/method performance study by the participants. The intention of this note is to emphasise the complementary use of certification study data by the participants of the certification study and to explain the options involved. On this occasion, an apparent paradox arising in the interpretation of certification study data is resolved. The procedures for bias correction and estimation of bias-related uncertainty contributions discussed on this occasion are, however, generally applicable to normal CRM use. Received: 4 February 1999 / Revised: 16 July 1999 / Accepted: 21 July 1999