Start Date: May 01, 2011
End Date: Apr 30, 2016
Our previous research with sensors that use relative humidity and temperature to predict grain equilibrium moisture content (EMC) has shown that they require equilibrium conditions to exist between the grain and interstitial air for accurate measurements. The OPI-Integris grain monitoring system includes in-bin, multi-point sensors for relative humidity and temperature to predict grain EMC. Previous collaboration between ARS and OPI-Integris used this system to monitor rice aeration with some success. Research is needed to determine the accuracy of this method during non-aeration periods when the grain is equilibrating with air conditions. Grain monitoring cables create increased point loads on roofs during bin loading and unloading. Cables with sensors attached may create greater forces on the roof than conventional cables. Research is needed to determine the magnitude of roof forces with these cables. Either corn or sorghum at 18% moisture content will be loaded into three bins at the Center for Grain and Animal Health Research (CGAHR) for drying with computer controlled low-temperature drying systems. The control system will monitor ambient temperature and relative humidity and grain EMC at multiple points in the drying bins using temperature and relative humidity sensors. The fans and heaters will be operated using the grain conditioning program, Integris Pro. The grain will be regularly probed to sample grain near moisture sensors for validation of readings and modeling. The moisture content of samples will be determined by oven drying and with a moisture meter. EMC curves will be determined for the tested corn and compared to published data. The Integris Pro Model will be used for prediction of end moisture and temperature conditions. Samples will be taken from the corn before it is dried and during storage after drying. These samples will be infested with maize weevils and held in an environmental chamber at optimum temperature and humidity for insect development. Progeny production in different lots of corn will be compared. The Insector System will be used to monitor insect populations during storage, examine bin-cooling patterns and different depths of the corn, and estimate when corn is most likely to become infested during the spring months following initial storage. Data will be integrated into Expert Systems for grain storage.