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A procedural approach for the identification of sources of uncertainty associated with GM quantification and real-time quantitative PCR measurements

机译:一种用于识别与GM定量和实时定量PCR测量相关的不确定性来源的程序方法

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摘要

Estimation of measurement uncertainty is important as it provides objective evidence that an assay or instrument is ‘fit for purpose’, and is a requirement for accreditation to ISO17025. Technological developments within the bioanalytical laboratory have progressed rapidly in the past few years. However, the measurement science associated with these technologies has not yet fully matured. The provision of a full measurement uncertainty budget is often difficult because of a lack of standardised approaches and the constraints associated with time, finances and expertise. A procedural approach for the identification of factors that can account for measurement uncertainty in quantification of genetically modified (GM) ingredients using real-time quantitative PCR is presented here. This example illustrates an approach for the identification of factors that can be applied to related assays concerned with GM quantification, can be utilised as part of existing uncertainty approaches, and can provide the basis for making quantitative estimates of uncertainty that will contribute towards a full measurement uncertainty budget.
机译:测量不确定度的估计很重要,因为它提供了客观的证据证明一种测定或仪器“符合目的”,并且是获得ISO17025认证的要求。在过去的几年中,生物分析实验室的技术发展迅速。但是,与这些技术相关的测量科学尚未完全成熟。由于缺乏标准化的方法以及与时间,财务和专业知识相关的限制,通常难以提供完整的测量不确定性预算。本文介绍了一种程序化方法,可用于识别可以解释使用实时定量PCR进行转基因(GM)成分定量时测量不确定性的因素。本示例说明了一种识别因子的方法,该方法可应用于与GM定量有关的相关测定,可以用作现有不确定性方法的一部分,并且可以为进行不确定性的定量估计提供基础,该不确定性将有助于全面测量不确定性预算。

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