Modelling a two-dimensional spatial distribution of mycotoxin concentration inbulk commodities to design effective and efficient sample selection strategies

摘要

Mycotoxins in agricultural commodities are a hazard to human and animal health.Their heterogeneous spatial distribution in bulk storage or transport makes itparticularly difficult to design effective and efficient sampling plans. Therehas been considerable emphasis on identifying the different sources ofuncertainty associated with mycotoxin concentration estimations, but much lesson identifying the effect of the spatial location of the sampling points. Thisstudy used a two-dimensional statistical modelling approach to produce detailedinformation on appropriate sampling strategies for surveillance of mycotoxins inraw food commodities. The emphasis was on deoxynivalenol (DON) and ochratoxin A(OTA) in large lots of grain in storage or bulk transport. The aim was tosimulate a range of plausible distributions of mycotoxins in grain from a set ofparameters characterising the distributions. For this purpose, a model wasdeveloped to generate data sets which were repeatedly sampled to investigate theeffect that sampling strategy and the number of incremental samples has ondetermining the statistical properties of mycotoxin concentration. Resultsshowed that, for most sample sizes, a regular grid proved to be more consistentand accurate in the estimation of the mean concentration of DON, which suggeststhat regular sampling strategies should be preferred to random sampling, wherepossible. For both strategies, the accuracy of the estimation of the meanconcentration increased significantly up to sample sizes of 40-60 (depending onthe simulation). The effect of sample size was small when it exceeded 60 points,which suggests that the maximum sample size required is of this order. Similarconclusions about the sample size apply to OTA, although the difference betweenregular and random sampling was small and probably negligible for most samplesizes.