Integrating Microwave Sensors Within a Distributed Network to Monitor Peanut Drying Parameters in Real-Time

Highlights Microwave sensors provided nondestructive, in-shell kernel moisture content determination in real-time. Monitoring systems measured relative humidity and temperature of the drying and exhaust air in real-time. In-shell kernel moisture content was determined with a standard error of calibration (SEC) =0.42% moisture content. Data were stored locally and monitored remotely via IoT with 12-second resolution. ABSTRACT. After peanuts are harvested, they remain in-shell as they go through postharvest processes. A representative sample has to be cleaned of all foreign material and shelled for kernel moisture content determination with the official moisture meter. Such limitations prohibit real-time determination of kernel moisture content during drying. Peanuts must be dried down to =10.49% kernel moisture content for grading purposes. Presently, there is no commercially available moisture sensor for in-shell kernel moisture content determination, and it would be extremely helpful to monitor moisture content at different locations during drying. A microwave moisture sensor, developed within USDA ARS, has demonstrated the utility of nondestructive, instantaneous kernel moisture content determination without having to shell the peanut, both in static applications as a benchtop sensor and in dynamic applications as a real-time monitoring sensor during drying. The microwave sensor operates at 5.8 GHz and uses low-intensity microwaves to measure the dielectric properties, which were correlated to kernel moisture content, providing a method of real-time determination of in-shell kernel moisture content. Triplicate monitoring systems were assembled with two RH sensors, three temperature sensors, and the microwave sensor to monitor peanut drying parameters in real-time with 12-s resolution. In-shell kernel moisture content was determined with a standard error of calibration (SEC) of =0.42% kernel moisture content. Data from all sensors was available for monitoring in real-time through ThingSpeak, an open-source IoT platform. Keywords: Dielectric properties, Distributed network, Internet of things, Microwave sensing, Peanut drying, Real-time monitoring.