Sample quality criteria.

The concept of Sample Quality Criteria (SQC) is the initial step in the scientific approach to representative sampling. It includes the establishment of sampling objectives, Decision Unit (DU), and confidence. Once fully defined, these criteria serve as input, in addition to material properties, to the Theory of Sampling for developing a representative sampling protocol. The first component of the SQC establishes these questions: What is the analyte(s) of concern? What is the concentration level of interest of the analyte(s)? How will inference(s) be made from the analytical data to the DU? The second component of the SQC establishes the DU, i.e., the scale at which decisions are to be made. On a large scale, a DU could be a ship or rail car; examples for small-scale DUs are individual beans, seeds, or kernels. A well-defined DU is critical because it defines the spatial and temporal boundaries of sample collection. SQC are not limited to a single DU; they can also include multiple DUs. The third SQC component, the confidence, establishes the desired probability that a correct inference (decision) can be made. The confidence level should typically correlate to the potential consequences of an incorrect decision (e.g., health or economic). The magnitude of combined errors in the sampling, sample processing and analytical protocols determines the likelihood of an incorrect decision. Thus, controlling error to a greater extent increases the probability of a correct decision. The required confidence level directly affects the sampling effort and QC measures.

Critical practicalities in sampling for mycotoxins in feed.

The presence of mycotoxins, in particular aflatoxin B1 , can cause significant health problems as well as severe economic loss, and are therefore regulated with respect to maximum acceptable concentration for various feed- and foodstuffs. International regulatory authorities have recognized the importance of representative sampling, and sampling guidelines that only partly comply with the Theory of Sampling have been formulated. Practical guidance regarding sampling, including correct design and operation of sampling devices and explanations on how to develop sufficient sampling protocols are lacking in current guidelines. These are critical practicalities of main importance, especially when dealing with trace concentrations and/or concentrations that are irregularly distributed, as for mycotoxins. Heterogeneity characterization, which is necessary to be able develop valid sampling protocols or validation assessments of existing sampling operations, is currently not mentioned in the existing guidelines. This paper explains all critical practicalities with respect to sampling of mycotoxins for 1-D and 3-0 feed decision units. Correct design and use of sampling and mass reduction devices, as well as structural guidelines for correctly designing experimental heterogeneity characterizations are presented, allowing evaluation of sampling representativeness and determination of optimal number of increments per composite sample. Practical examples are given on how to extract information from variographic analysis and replication experiments, based on an extensive field trials performed to determine aflatoxin levels in various feed components.

Theory of sampling: four critical success factors before analysis.

Food and feed materials characterization, risk assessment, and safety evaluations can only be ensured if QC measures are based on valid analytical data, stemming from representative samples. The Theory of Sampling (TOS) is the only comprehensive theoretical framework that fully defines all requirements to ensure sampling correctness and representativity, and to provide the guiding principles for sampling in practice. TOS also defines the concept of material heterogeneity and its impact on the sampling process, including the effects from all potential sampling errors. TOS's primary task is to eliminate bias-generating errors and to minimize sampling variability. Quantitative measures are provided to characterize material heterogeneity, on which an optimal sampling strategy should be based. Four critical success factors preceding analysis to ensure a representative sampling process are presented here.