Optimization modeling analysis for grain harvesting management

Appropriate farm management practices can improve agricultural productivity and reduce grain losses. An optimization model, called BioGrain, was developed to maximize farmers’ profits by optimizing critical grain harvesting decisions including agricultural machinery selection and harvesting schedules. This model was applied to 18 representative farms of varied sizes in Illinois, Iowa, and Minnesota. Our optimization showed that understanding crop moisture dynamics is critical for maximizing profits at the farm scale. Our results highlight the tradeoffs between grain losses and drying costs when considering profit maximization. By optimizing harvesting dates and machinery size, large farms can reduce the grain loss rate to 10%, and small farms can achieve a 5% grain loss rate. Large farms outperformed small farms on unit profits despite their higher grain loss rate. The model considers both revenue and cost related factors in harvesting decisions and quantifies the tradeoffs among corn yield, drying, and equipment selection. The model can be used to provide decision support for individual farms in different regions considering their local crop and market information.