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Optimal management of molds in stored corn
Authors:Yigezu A Yigezu  Corinne E Alexander  Paul V Preckel  DE Maier  CP Woloshuk  LJ Mason  J Lawrence  DJ Moog
Institution:1. Department of Agricultural Economics, Purdue University, 403 West State Street, West Lafayette, IN 47907, USA;2. Department of Grain Science and Industry, Kansas State University, 201 Shellenberger Hall, Manhattan, KS 66506, USA;3. Department of Botany and Plant Pathology, Purdue University, 915 West State Street, West Lafayette, IN 47907, USA;4. Department of Entomology, Purdue University, 901 West State Street, West Lafayette, IN 479070, USA;5. Department of Agricultural and Biological Engineering, Purdue University, 225 South University Street, West Lafayette, IN 47907, USA
Abstract: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.
Keywords:Mold management  Stored corn  Expected profitability  Integrated pest management  Monitoring  Aeration  Stochastic dynamic programming
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