Traceability systems for food and feed ingredients have many factors that influence how effectively firms store, transport, refine, and process food products. Investment in food traceability systems can be a significant expense, but a robust system can efficiently isolate and remove contaminated products from the food chain, increasing consumer confidence. The traceability process is further complicated in the grain industry because grain is moved in bulk and cannot be individually marked with any of the current tracking devices such as barcodes, alphanumeric codes, or RFID (radio frequency identification) tags. The bulk movement of grain results in an undetermined amount of mixing and moving that occurs between lots of grain as it flows through storage and production systems. To better track and characterize this movement and mixing, several factors must be considered: grain type, moisture content, storage bin diameter and height, transportation type in and out, load-in location(s), load-out location(s), and flow rate. To improve the knowledge of grain behavior across the wide variety of scenarios in use in grain handling, research was conducted to simulate traceability and grain flow with a miniature scale model to quantify the extent of granular mixing within a given situation. The simulation will allow a statistical model to be constructed that gives food and feed handlers a tool for calculating the probability and associated error of mixture between grain lots while grain moves through the handling system in place at their facility.