University of Veterinary Medicine, Institute of Animal Nutrition, Veterinärplatz 1, 1210 Vienna, Austria.
Analyst. 2011 Oct 7;136(19):4059-69. doi: 10.1039/c1an15124j. Epub 2011 Aug 11.
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.
《Eurachem/CITAC 指南中包含测量(包括采样)不确定度的重复方法》提出了这种方法。本方法作为验证真菌毒素采样计划的工具,在 3 个动物饲料中黄曲霉毒素 B(1)的案例研究中进行了评估。所考虑的方面包括从污染批次中获取样品的策略、关于分布的假设、统计分析方法、测试数据的对数转换以及不确定度估计的适用性。结果表明,当通过相互渗透采样形成重复的混合样品时,可以假定来自一批的重复测量值近似遵循正态或对数正态分布。由于采样目标之间的毒素浓度差异很大,并且有时由于采样和样品制备引起的不确定性非常大(U(rel) ≥ 50%),发现基于对数转换数据的不确定度估计比稳健方差分析的应用更具有普遍适用性。