Article ID: | iaor20111644 |
Volume: | 98 |
Issue: | 3 |
Start Page Number: | 220 |
End Page Number: | 227 |
Publication Date: | Oct 2008 |
Journal: | Agricultural Systems |
Authors: | Yigezu Yigezu A, Alexander Corinne E, Preckel Paul V, Maier D E, Woloshuk C P, Mason L J, Lawrence J, Moog D J |
Keywords: | programming: probabilistic, programming: dynamic, inventory: storage |
Long term storage of corn is becoming more common due to the recent increase in the demand for corn by ethanol plants. Infection of maize kernels by toxigenic fungi remains a challenging storage problem despite decades of research. Experts in storage management propose the use of a combination of preventive and monitoring‐based responsive strategies in response to mold risks. In this paper, a stochastic dynamic programming model is solved to determine the expected profitability and optimal combination, timing, and intensity of the proposed mold management strategies using farmers’ existing infrastructure. The results show that even with relatively high monitoring costs, maintaining high quality grain using a monitoring‐based optimal mold management strategy costs less than the benefit it fetches. The current typical practice by Indiana farmers of aerating the grain until the end of December and doing nothing thereafter bears a high risk of economic losses if grain is to be stored until later during the summer. Generally, the optimal mold management strategy depends on monitoring the biophysical conditions of the grain and the time period under consideration. If the in‐bin temperature is high and less than 5% of kernels are mold damaged, then aerating when the outside temperature is at least 3°C less than the in‐bin temperature and continuing to store the grain is the optimal strategy.