USE OF PREDICTIVE MODELING TO IMPROVE MEASUREMENT OF WORKER SAFETY RISK IN GRAIN HANDLING

The project aims to use structural and stochastic modeling tools to measure relationships between weather, harvest, planting, and grain quality data to provide new insights into seasonal risk messages for those who handle grain.The first goal of the project is to establish and work with an advisory group of stakeholders to identify significant variables and assumptions of the scenarios to be modeled.The second research goal is to identify relevant data sets to construct and model appropriate scenarios, and interpret results.The third goal is to use model findings to interact with the advisory group to create a decision-making tool and messaging options designed to guide grain producers and handlers on managing safety hazards under a variety of post-harvest handling and storage scenarios.