Modelling testing mechanism for mitigating genetically modified wheat contamination risks

Abstract

Recent discoveries of genetically modified (GM) wheat growing in farm fields across several U.S. states have renewed public worries about GM wheat contamination if GM wheat is commercialised. There would appear to be a need for research designed to identify reactive risk mitigation strategies to maintain the sustainability of grain supply chains (SCs) before any potential GM wheat contamination undermines their integrity. This research attempts to identify cost-effective testing strategies to mitigate the GM wheat contamination risks. We explicitly model the U.S. wheat supply chain in a realistic manner to embrace complexity inherent in the system. The specification of appropriate wheat handling strategies in the SC is formulated as system optimisation problems and solved using simulation. Once solved for a base scenario, sensitivity analysis is conducted on key variables that influence wheat varietal testing strategies.