Software for the Computation of Detection Efficiency and of Coincidence Summing Effects Including Neutron Self-Shielding

The GESPECOR software, initially developed for the computation of efficiency of HPGe detectors in environmental -ray spectrometry, was applied to NAA. The software is useful for the computation of efficiency and of self-attenuation and coincidence-summing corrections for common experimental conditions. A new source subroutine was implemented in GESPECOR for solving the more complex case of non-uniform sources. In this way neutron self-shielding in the activation of samples of large volume is taken into account. The dependence of the detection efficiency on the flux distribution is discussed.     

Overall calibration procedure via a statistically based matrix-comprehensive approach in the stir bar sorptive extraction-thermal desorption-gas chromatography-mass spectrometry analysis of pesticide residues in fruit-based soft drinks

Stir bar sorptive extraction (SBSE)-thermal desorption (TD) procedure combined with gas chromatography mass spectrometry (GC-MS) and the statistical variance component model (VCM) is applied to the determination of semi-volatile compounds including organochlorine and organophosphorus pesticides in various synthetic and real fruit-based soft drink matrices. When the matrix effects are corrected using isotopically labelled or non labelled internal standard, but matrix/calibration run-induced deviations are still present in the measurements, the adoption of a variance component model (VCM) in the quantitative analysis of various matrices via an overall calibration curve is successful. The method produces an overall calibration straight line for any analyte accounting for the uncertainty due to all the sources of uncertainty, namely matrix-induced deviations, calibration runs performed at different times, measurement errors. Small increases in the detection limits and in uncertainty in the concentration values obtained in the inverse regression face favourably the decrease in times and costs for routine analyses.     

Verification of uncertainty budgets

The quality of analytical results is expressed by their uncertainty, as it is estimated on the basis of an uncertainty budget; little effort is, however, often spent on ascertaining the quality of the uncertainty budget. The uncertainty budget is based on circumstantial or historical data, and therefore it is essential that the applicability of the overall uncertainty budget to actual measurement results be verified on the basis of current experimental data. This should be carried out by replicate analysis of samples taken in accordance with the definition of the measurand, but representing the full range of matrices and concentrations for which the budget is assumed to be valid. In this way the assumptions made in the uncertainty budget can be experimentally verified, both as regards sources of variability that are assumed negligible, and dominant uncertainty components. Agreement between observed and expected variability is tested by means of the T-test, which follows a chi-square distribution with a number of degrees of freedom determined by the number of replicates. Significant deviations between predicted and observed variability may be caused by a variety of effects, and examples will be presented; both underestimation and overestimation may occur, each leading to correcting the influence of uncertainty components according to their influence on the variability of experimental results. Some uncertainty components can be verified only with a very small number of degrees of freedom, because their influence requires samples taken at long intervals, e.g., the acquisition of a new calibrant. It is therefore recommended to include verification of the uncertainty budget in the continuous QA/QC monitoring; this will eventually lead to a test also for such rarely occurring effects.     

Comparison of strategies to quantify uncertainty of lead measurements in biological tissue at mg kg<Superscript>–1</Superscript> level

The expression of measurement uncertainty in analytical chemistry still presents some difficulties. According to the various guides and standards, several approaches are possible. This paper present two referenced approaches applied to the determination of Pb in a biological tissue at the mg kg^–1 level. Estimations were achieved, either from inter-laboratory precision data, or from the uncertainty propagation equation applied to the measurements of a single laboratory. When comparing final values, for an average concentration of about 2.0 mg kg^–1, expanded uncertainties range from ±0.05 mg kg^–1 up to ±0.31 mg kg^–1, i.e. by a factor of 6. Obviously, both approaches of estimating uncertainty do not cover the same sources of uncertainty and it is interesting to try to understand better these discrepancies in order to try to define realistic guidelines for analysts. Moreover the experimental results of the study are given where a wide number of techniques is applied. Received: 5 May 2002 Accepted: 17 June 2002 Correspondence to M. Feinberg     

用ISO《测量不确定度表达指南》评估ICP-AES法测定不确定度

用国际通用的方法评估出ICP－AES法测定不确定度，考虑不确定度的主要来源包括仪器的精密度、标准物质标称值的不确定度以及制备溶液过程中引起的不确定度，推导出各种传播系数表达式，计算出各种不确定度分量并将其合成，并以测定钢铁中磷含量为例，提供了计算过程所需的各参数的采集和计算方法，所用的方法同样适用于以线性回归标准曲线法获得测定结果不确定度的评估。     

离子色谱法测定地下水中硝酸盐氮含量的不确定度评定

采用不确定度连续传递模式,讨论了不同回归方式对离子色谱法测定岩溶地下水中硝酸根分析结果不确定度评定的差异.结果表明：（1）测定结果的不确定度主要来源于标准溶液配制过程引入的不确定度、校准曲线拟合及回归过程产生的不确定度和仪器测定过程引入的不确定度三部分;（2）不同校准曲线回归方式对测定结果的不确定度评定在不同测量水平上有不同的影响,当地下水中硝酸根含量越低,差异越大.此外,对不确定度评定过程中的各个分量进行量化,通过合成得到硝酸根测定结果的不确定度评定模型.     

Measurement uncertainty as a tool for evaluating the ‘grey zone’ to reduce the false negatives in immunochemical screening of blood donors for infectious diseases

The risk of misclassifying infected individuals as healthy constitutes a crucial challenge when screening blood donors by means of immunoassays. This risk is especially challenging when the numerical results are close to the clinical decision level, i.e. in the ‘grey zone’. The concept of using measurement uncertainty for evaluating the ‘grey zone’ has previously not been systematically applied in this context. This article explains methods, models and empirical (top-down) approaches for the calculation of measurement uncertainty using results from a blood bank according to the internationally accepted GUM principles, focusing on uncertainty sources in the analytical phase. Of the different approaches available, the intralaboratory empirical approaches are emphasised since modelling (bottom-up) approaches are impracticable due to the lack of reliable model equations for immunoassays. Different methods are applied to estimate the measurement uncertainty for the Abbott Prism^® HCV immunoassay. The expanded uncertainty obtained at the clinical decision level from the intralaboratory empirical approach was 36 %. The estimated uncertainty was used to set acceptance and rejection zones following the procedure set in the Eurachem guideline, emphasising the need to minimise the occurrence of false negatives.     

Alternative calculation of measurement uncertainty with global approach in food microbiology

Calculation of measurement uncertainty is a requirement for all laboratories accredited to ISO/IEC 17025 including those carrying out microbiological analyses. Today, calculation of measurement uncertainty in microbiological analyses using precision data according to global approach principles is widely recognized by the microbiologists due to difficulties in quantification of individual uncertainty sources. In food microbiology, precision data obtained from different samples usually show over-dispersion, and the use of over-dispersed data may result in large variance. The current ISO standard on measurement uncertainty in food microbiology proposes the use of log-transformed precision data to overcome this problem. This paper proposes an alternative procedure to calculate the measurement uncertainty in food microbiology using non-logarithmic precision data. The calculations used in this procedure based on relative range of duplicate analyses can be applied to intra-laboratory reproducibility data obtained from microbiological analyses of which duplicate results show relatively low variation.     

Measurement uncertainty in analytical methods in which trueness is assessed from recovery assays

We propose a new procedure for estimating the uncertainty in quantitative routine analysis. This procedure uses the information generated when the trueness of the analytical method is assessed from recovery assays. In this paper, we assess trueness by estimating proportional bias (in terms of recovery) and constant bias separately. The advantage of the procedure is that little extra work needs to be done to estimate the measurement uncertainty associated to routine samples. This uncertainty is considered to be correct whenever the samples used in the recovery assays are representative of the future routine samples (in terms of matrix and analyte concentration). Moreover, these samples should be analysed by varying all the factors that can affect the analytical method. If they are analysed in this fashion, the precision estimates generated in the recovery assays take into account the variability of the routine samples and also all the sources of variability of the analytical method. Other terms related to the sample heterogeneity, sample pretreatments or factors not representatively varied in the recovery assays should only be subsequently included when necessary. The ideas presented are applied to calculate the uncertainty of results obtained when analysing sulphides in wine by HS-SPME-GC.     

Models to estimate overall analytical measurements uncertainty: assumptions, comparisons and applications

Evaluation of analytical results reliability is of core importance as crucial decisions are taken with them. From the various methodologies to evaluate the fitness of purpose of analytical methods, overall measurement uncertainty estimation is more and more applied. Overall measurement uncertainty allows to combine simultaneously the remaining systematic influences to the random sources of uncertainty and allows assessing the reliability of results generated by analytical methods. However there are various interpretations on how to estimate overall measurement uncertainty, and thus various models for estimating it. Each model together with its assumptions has great impacts on the risks to abusively declare that analytical methods are suitable for their intended purpose. This review paper aims at (i) summarizing the various models used to estimate overall measurement uncertainty, (ii) provide their pros and cons, (iii) review the main areas of application and (iv) as a conclusion provide some recommendations when evaluating overall measurement uncertainty.     

Uncertainty sources in UV-Vis spectrophotometric measurement

An overview is given of the most important uncertainty sources that affect analytical UV-Vis spectrophotometric measurements. Altogether, eight uncertainty sources are discussed that are expected to have influence in chemical analysis. It is demonstrated that the well-known intrinsic (or “physical”) sources of uncertainty that originate from the instrument itself (repeatability of spectrophotometer reading, spectrophotometer drift, stray light, etc.) often have significantly lower contributions to the combined uncertainty of the result than the “chemical” sources of uncertainty that originate from the object under study (interference from the constituents of the matrix, decomposition of the photometric complex, etc.). Although selectivity of a photometric procedure is often considered more a validation topic than an uncertainty topic, it is very often important to include it also in the uncertainty budget.Usually the most difficult part of uncertainty estimation of a chemical measurement result is to evaluate the magnitude of the actual uncertainty components, especially the chemical ones. For most of the uncertainty sources discussed in this paper, approaches for their evaluation are given. A generic uncertainty budget for absorbance is presented. Electronic Supplementary Material Supplementary material is available for this article at     

Empirical versus modelling approaches to the estimation of measurement uncertainty caused by primary sampling

Measurement uncertainty is a vital issue within analytical science. There are strong arguments that primary sampling should be considered the first and perhaps the most influential step in the measurement process. Increasingly, analytical laboratories are required to report measurement results to clients together with estimates of the uncertainty. Furthermore, these estimates can be used when pursuing regulation enforcement to decide whether a measured analyte concentration is above a threshold value. With its recognised importance in analytical measurement, the question arises of 'what is the most appropriate method to estimate the measurement uncertainty?'. Two broad methods for uncertainty estimation are identified, the modelling method and the empirical method. In modelling, the estimation of uncertainty involves the identification, quantification and summation (as variances) of each potential source of uncertainty. This approach has been applied to purely analytical systems, but becomes increasingly problematic in identifying all of such sources when it is applied to primary sampling. Applications of this methodology to sampling often utilise long-established theoretical models of sampling and adopt the assumption that a 'correct' sampling protocol will ensure a representative sample. The empirical approach to uncertainty estimation involves replicated measurements from either inter-organisational trials and/or internal method validation and quality control. A more simple method involves duplicating sampling and analysis, by one organisation, for a small proportion of the total number of samples. This has proven to be a suitable alternative to these often expensive and time-consuming trials, in routine surveillance and one-off surveys, especially where heterogeneity is the main source of uncertainty. A case study of aflatoxins in pistachio nuts is used to broadly demonstrate the strengths and weakness of the two methods of uncertainty estimation. The estimate of sampling uncertainty made using the modelling approach (136%, at 68% confidence) is six times larger than that found using the empirical approach (22.5%). The difficulty in establishing reliable estimates for the input variable for the modelling approach is thought to be the main cause of the discrepancy. The empirical approach to uncertainty estimation, with the automatic inclusion of sampling within the uncertainty statement, is recognised as generally the most practical procedure, providing the more reliable estimates. The modelling approach is also shown to have a useful role, especially in choosing strategies to change the sampling uncertainty, when required.     

Method validation and measurement uncertainty evaluation for measurement of mass concentration of organic acids in fermentation broths by using ion chromatography

In the present paper, a methodology for method validation and measurement uncertainty evaluation for the measurement of mass concentration of organic acids in fermentation broths was developed. Acetic acid was selected as a representative of organic acids. A detailed procedure for in-house method validation based on simple experimental design and consistent statistics is presented. In addition, a step-by-step illustration of ??Bottom-Up?? approach for measurement uncertainty evaluation of acetic acid in fermentation broths is also provided. The major sources of uncertainty of the result of measurement were identified and the combined uncertainty was calculated. Our analytical protocol allowed us to quantify acetic acid in fermentation broths in mass concentrations up to 75?g?L^?1 with satisfactory recovery (102.3%) and repeatability lower than 2%. We also estimated within-laboratory reproducibility over 3-month period, which was 2.3%. We proved that the method was selective for the measurement of mass concentration of acetic acid in fermentation broths. Measurement uncertainty of results was evaluated to be 6.2% with 95% confidence level. After validation and measurement uncertainty evaluation steps, results obtained showed that the method can be applied to efficiently monitor fermentation processes.     

Uncertainty in liquid chromatographic analysis of pharmaceutical product: influence of various uncertainty sources

An ISO GUM measurement uncertainty estimation procedure was developed for a liquid-chromatographic drug quality control method-assay of simvastatin in drug formulation. In quantification of uncertainty components several practical approaches for including difficult-to-estimate uncertainty sources (such as uncertainty due to peak integration, uncertainty due to nonlinearity of the calibration curve, etc.) have been presented. Detailed analysis of contributions of the various uncertainty sources was carried out. The results were calculated based on different definitions of the measurand and it was demonstrated that unequivocal definition of the measurand is essential in order to get rigorous uncertainty estimate. Two different calibration methods - single-point (1P) and five-point (5P) - were used and the obtained uncertainties and uncertainty budgets were compared. Results calculated using 1P and 5P calibrations agree very well. The uncertainty estimate for 1P is only slightly larger than with 5P calibration.     

微波消解火焰原子吸收法测定火龙果中铁的不确定度评定

对微波消解火焰原子吸收法测定火龙果中铁含量的不确定度进行评估.建立相应的不确定度数学模型，根据测试过程分析不确定度来源有7个方面，计算各不确定度分量，得到火龙果中铁含量测定结果是X=（1.308±0.281）mg/100 g（k=2）.测量过程不确定度的主要来源是样品溶液测量、样品空白及样品溶液定容等3个方面，其中，标准曲线制作和工作曲线拟合引起的不确定度最大.不确定度评定结果可为水果等营养元素检测方面提供参考，避免或减少一些不必要检测误差，使测试结果更加准确.     

Use of thin collodion films to prevent recoil-ion contamination of alpha-spectrometry detectors

Recoil ions from alpha-particle emission can contaminate surface-barrier detection systems. This contamination results in increased measurement uncertainty, and may require the replacement of expensive detectors. Disposable thin Collodion films are easily prepared and effectively retard the recoil ions when either directly applied to the surface of alpha-sources or as catcher foils between the source and the detector. The thin films are particularly effective for relatively low-level sources, but can sustain structural damage when exposed to high levels of recoil ions (tens of thousands per second) over extended periods of time.     

ICP-AES测定糖果中铅质量分数的不确定度评定

建立了电感耦合等离子体发射光谱(ICP-AES)测定糖果中铅的相应数学模型, 对数学模型中各个参数进行不确定度来源分析, 分别对A类不确定度或B类不确定度进行评定. 对各不确定度分量合成和扩展, 得到铅质量分数的不确定度. 结果表明: 标准溶液的配制、标准曲线拟合线性方程及样品溶液的定容是不确定度的主要来源.     

Activity determination without tracers in high-resolution alpha-particle spectrometry

High-resolution alpha spectrometry was applied for the activity determination of 10 reference sources containing different amounts of ²³⁸Pu, ²³⁹Pu, ²⁴⁰Pu and ²⁴²Pu. They were analyzed as blind sources using a novel spectrum analysis tool ADAM. The information needed in the spectrum unfolding was taken only from the spectrum under investigation, and no tracers were applied. Therefore, a Monte Carlo program AASI was used to compute geometrical detection efficiency of the measurement setup. All reported activities corresponded to those of the reference sources within expanded uncertainty. The developed tools can be used for the activity determination in nondestructive alpha spectrometry or when the radionuclide composition does not change during the sample processing.     

ICP-AES法测定蔬菜、水果中锌含量的不确定度评定

不确定度[1-3]在我国各行业的应用发展不均衡,在蔬菜、水果检测方法的评定方面鲜有报道。ICP作为一种灵敏度高、快速、高效的检测手段在食品、环保及其它领域得到了广泛的应用,其检测结果不确定度的评定较为重要。本文以ICP法测定番茄中的锌为例,对ICP法测定蔬菜、水果中重金属