Modelling the costs associated with high-moisture grain for mobile apps

Abstract

The companies that operate grain delivery locations use a variety of methods to discount grain that is delivered with high moisture levels which are often difficult for producers to determine. This project analyzed 24 grain discount schedules representing 34 locations within and near the state of Kentucky with the goal of determining the cost of delivering grain. Discounts represent a large portion of overall cost and were expressed in terms of price, percent or a combination of price and percent. All discount schedules were stepwise functions that were evaluated at the nearest tenth of a percent moisture. The step-wise functions can have constant or variable step widths and constant or variable intervals between steps. For the large number of discount schedules based on constant step widths and intervals, equations can be used to evaluate the expected discount, but the variable functions required the use of lookup tables to record the discount schedule. After establishing a method for recording and equations for evaluating the moisture discounts, these were combined with delivery and transportation cost models to provide a larger model to estimate costs associated with high moisture grain delivery to different locations. Establishing this model enabled the creation of a producer decision support tool. This tool was developed as a smart phone application which enabled automatic determination of location if used in the field during harvest and access to cloud-based mapping tools for evaluation of the transportation network for delivery to various grain delivery locations.