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Experimental approaches for the estimation of uncertainty in analysis of trace inorganic contaminants in foodstuffs by ICP-MS

机译:ICP-MS估算食品中痕量无机污染物的不确定度的实验方法

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摘要

Total Diet Studies to estimate dietary exposure to food contaminants need to evaluate laboratory measurements data variance. In this process it is critical that data from analytical methods are reliable to correctly scrutinize and compare values over time and between countries. In Europe it is widely recognized that the evaluation of measurement uncertainty is an important parameter when assessing the sources of analytical data variability. Two approaches are considered to estimate uncertainty in analytical measurement. Arsenic, Lead, Chromium and Cadmium, content in several food matrix determined by Inductively Coupled Mass Spectrometry (ICP-MS) microwave digestion assisted, are used as examples. The aim of the present research work is to compare both approaches accepted by Eurolab and GUM: Mathematical modeling to assess uncertainty components based on a classical model (bottom up) and an empirical method (top down), based on either experimental data obtained from a single laboratory validation data or inter-laboratory data from Proficiency Testing schemes. Relative expanded uncertainty calculated by both approaches agree when U (%) <20%. These values are concordant with RSD_R reported in collaborative studies of EN 15763 (2009), which were assumed as target uncertainty. The top down approach described is simple and easy to use when compared with the mathematical modeling approach providing considerable benefits to those who assess data produced by several laboratories.
机译:全面饮食研究需要估计饮食中食物污染物的暴露量,因此需要评估实验室测量数据的差异。在此过程中,至关重要的是,分析方法的数据必须可靠,以正确检查和比较一段时间内以及国家之间的价值。在欧洲,众所周知,在评估分析数据变异性的来源时,测量不确定度的评估是重要的参数。考虑了两种方法来估计分析测量中的不确定性。例如,通过电感耦合质谱(ICP-MS)微波消解辅助测定的几种食物基质中的砷,铅,铬和镉的含量为例。本研究工作的目的是比较Eurolab和GUM接受的两种方法:基于经典模型(自下而上)和经验方法(自上而下)的数学建模,以评估不确定性成分,并基于从来自能力验证计划的单个实验室验证数据或实验室间数据。当U(%)<20%时,两种方法计算出的相对扩展不确定性一致。这些值与EN 15763(2009)的协作研究中报告的RSD_R一致,被认为是目标不确定性。与数学建模方法相比,所描述的自上而下的方法简单易用,为那些评估多个实验室产生的数据的人员提供了巨大的收益。

著录项

  • 来源
    《Food Chemistry》 |2013年第1期|604-611|共8页
  • 作者单位

    Department of Food Safety and Nutrition, National Institute of Health Dr. Ricardo]orge (INSA), Av. Padre Cruz, 1649-016 Lisbon, Portugal;

    Department of Food Safety and Nutrition, National Institute of Health Dr. Ricardo]orge (INSA), Av. Padre Cruz, 1649-016 Lisbon, Portugal;

    UNIDEMI, Departamento de Engenharia Mecanica e Industrial, Faculdade de Ciencias e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal;

    Institute of Food Research (IFR), Norwich NR4 7UA, United Kingdom;

    Department of Food Safety and Nutrition, National Institute of Health Dr. Ricardo]orge (INSA), Av. Padre Cruz, 1649-016 Lisbon, Portugal;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Uncertainty evaluation; Experimental approaches; Food consumption; Comparability of data; Food chemical contaminants;

    机译:不确定度评估;实验方法;食物消耗;数据可比性;食品化学污染物;

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