Measurement uncertainty for detection of visual impurities in granular feed and food materials in relation to the investigated amount of material

Abstract

The presence is regulated of visually detectable seeds from a selection of toxic plants and fungi mycelium bodies (sclerotia) in feed (Directive 2002/32/EC) and in food (Regulation (EC) 1881/2006). Homogenisation as typical for chemical analyses is not applicable, and dedicated approaches are needed for visual examination methods. Visual methods require two parameters to characterise measurement uncertainties for both unit counts and unit weights. A new approach is to divide approximately 2 kg of sample material into four subsamples of approximately 500 g and to separately examine the four subsamples for numbers and particle weights of seeds or sclerotia. This study is the first to produce datasets on inhomogeneity among subsamples of a sample for visually detectable undesirable substances. Analytical thresholds were calculated from a simulation model and bootstrap procedures based on our data. The analytical thresholds assuring a controlled false-negative rate of 5% for decisions in compliance with legal limits depend on the diversity of the unit counts and weights, the level of the legal limit and the amount of material examined initially in the step-wise approach, either one or two subsamples. A procedure is proposed for examination in practice where only two subsamples, or alternatively even only one subsample, would be examined. If the resulting level of contamination exceeds the relevant threshold additional subsamples need to be examined as well. In most of the investigated cases, analytical thresholds could be established for the examination of just one subsample (500 g) taken from a sample of 2 kg. However, for ergot sclerotia in food with a legal limit of 200 mg kg−1, at least two subsamples (1000 g) need to be examined in the first step. Other groups of visually detectable undesirable substances exist which need further attention

    Similar works

    Full text

    thumbnail-image

    Available Versions

    Last time updated on 31/12/2022
    Last time updated on 31/12/2022