Representative sampling of large kernel lots III. General considerations on sampling heterogeneous foods

Part I reviewed the Theory of Sampling (TOS) as applied to quantitation of genetically-modified organisms (GMOs). Part II re-analyzed KeLDA data from a variographic analysis perspective and estimated Total Sampling Error (TSE) versus Total Analytical Error (TAE).Results from this analysis are here used as a basis for developing a general approach to optimization of kernel-sampling protocols that are fit for purpose (i.e. scaled with respect to the effective heterogeneity while simultaneously sufficiently accurate to detect critically low concentration levels). While TAE is significantly large for GMO quantitation, TSE can still be up two orders of magnitude larger, signifying that efforts to reduce GMO-analysis uncertainties should focus on improving or optimizing sampling plans and not on further refinements of analytical precision.For GMO testing based on the current labeling threshold (0.9%) of European Union regulations, KeLDA re-analysis results show that the number of increments needed (Q) for reliable characterization of lots with significant heterogeneities range between 42 (highly heterogeneous lots) and 17 (close to uniform materials). We outline how it is always possible to estimate TSE from a simple variographic experiment based on TOS’ process-sampling requirements. This approach is universal and can be carried over from the GMO case to all other (static or dynamic) sampling scenarios and materials dealing with impurities, contaminants, or trace concentrations, without any loss of generality. A proper basis for TOS-based process sampling is essential for any meaningful definition of “appropriate sampling plans” (i.e. sampling plans minimizing TSE as function of the specific heterogeneity of any given lot). If unit-operation costs for sampling and analysis are known, sampling plans can also be optimized with respect to overall costs.We discuss the degree to which the present results can be generalized regarding official monitoring and inspection of food and feed materials. What is presented here in effect constitutes a contribution towards a comprehensive, horizontal process-sampling standard for heterogeneous materials in general.

► Definition of salient characteristics of “fit-for-purpose” sampling plans.
► Minimum no. of increments to counteract maximum heterogeneity kernel lots is 42.
► GMO results can be generalized to other material types with similar lot heterogeneities.
► Characteristics of a general approach for process sampling plan optimization.