Application of binomial and multinomial probability statistics to the sampling design process of a global grain tracing and recall system

Small, coded, pill sized tracers embedded in grains are proposed as a method to store a historical record of grains and retrieve coded information for grain traceability. This study aimed to develop and validate a statistical sampling procedure to securely collect sample sizes (kg) and number of tracers since the sampling accuracy is critical in the proposed traceability system for capturing information and data related to grain lots to trace the grain back through the route in a grain supply chain. The statistical results and observations showed similar concentrations and insignificant segregation of tracers in bin and truck operations. The number of tracers required for identification of grain sources fell within the confidence intervals and sample sizes (kg) estimated by statistical probability methods. Truck sampling appeared more feasible in collecting the secure number of tracers over bin sampling. The designed sampling process was empirically proven to be practically applicable and provide better scientific assurance of sampling accuracy, which may reduce economic risks and their consequent costs caused by unfavorable sampling in the propose traceability system.