Development of an Eighth-scale Grain Drying System with Real-time Microwave Monitoring of Moisture Content

After being harvested, cereal grain and oilseed are stored and dried in large cylindrical storage bins. Drying is necessary to prevent spoilage and degradation; however, because of the significant depth of material in the drying bin, a common problem in grain and oilseed drying is overdrying the bottom layer while trying to dry the top layer. This is due to insufficient knowledge of moisture throughout the bin. In some cases, an operator is limited to probing reachable locations to determine moisture content. However, this does not lend to observing the dynamics of moisture content within the bin continuously, and the lower layers of grain or seed within the bin are susceptible to being overdried. Temperature and/or moisture cables to monitor conditions throughout the bin are more widely used. These sensors use a correlation between grain moisture content and temperature and relative humidity. However, error in moisture content determination increases greatly at high relative humidity and/or temperature. By using a microwave moisture sensor operating at 5.8 GHz, developed within USDA ARS, the moisture content of the cereal grain or oilseed can be measured continuously, providing real-time moisture content with 12-s resolution. An automated, eighth-scale grain drying system was developed utilizing temperature and relative humidity sensors at different heights within the grain bin and the microwave moisture sensor to observe drying parameters and moisture migration as the grain or seed dried. Grain and seed moisture content was determined in real-time with a standard error of calibration of = 0.54% moisture content when compared to the reference oven-drying method. Overall evaluation showed that the automated grain drying system is an effective solution for real-time monitoring of moisture content and other parameters during drying. Keywords: Dielectric properties, Grain drying bin, Moisture content, Microwave sensing, Real-time monitoring, Sensors.