Modeling Non‐GM Segregation Strategies at the Grain Elevator

ABSTRACT Background and Objective As new opportunities arise for non‐genetically modified (non‐GM) products in grain markets, segregation becomes crucial but challenging in commodity‐friendly infrastructures such as grain elevators. This study developed probabilistic models using Monte Carlo simulations to evaluate three segregation strategies (dedication, spatial, and temporal) at grain elevators. The aim was to identify practices, decisions, and facility configurations that characterize successful non‐GM segregation by meeting adventitious presence (AP) tolerance limits: 0.9%, 1.5%, 3%, and 5% in different working scenarios. Findings The probabilistic models revealed that all segregation scenarios met the 5% tolerance limit, but not the 0.9%, 1.5%, and 3% limits. Only 3 out of 18 scenarios could achieve a 0.9% limit when the facility was dedicated to handling non‐GM grain. Concurrent handling of GM and non‐GM grain in facilities with configurations like one pit–one leg or two pit–one leg could meet 3% and 5% limits through temporal segregation with cleaning between loads. Spatial segregation in facilities with multiple lines was effective for 1.5%, 3%, and 5%, but was ineffective for a 0.9% limit. The 99% feasible tolerance limits in all scenarios ranged between 0.28% and 2.40%. Conclusions The models found dedication and spatial segregation to be the best‐suited strategies for non‐GM segregation. However, in facilities where spatial segregation was not possible, temporal segregation with cleaning between loads was effective for tolerance levels above 3%. Significance and Novelty The models offer valuable insights into the effectiveness of different segregation strategies and facility configurations for non‐GM grain handling. It demonstrates the usefulness of a probabilistic model to simulate different scenarios and choose optimal combinations for business needs and tolerance limits.