Submitted to: Southeastcon, IEEE
Publication Type: Proceedings
Publication Acceptance Date: 1/24/2013
Publication Date: 4/4/2013
Citation: Lewis, M.A., Trabelsi, S., Nelson, S.O. 2013. Automation of peanut drying with a sensor network including an in-shell kernel moisture sensor. Southeastcon, IEEE. p.136-142.
Interpretive Summary: Peanut drying is an essential task that takes place at peanut buying stations and shelling plants, preceding the grading process. Although peanuts are left in windrows to dry naturally before being harvested with combines, they arrive at buying stations considerably high in moisture content. Therefore, it is imperative for peanuts to be dried to less than 10.5% kernel moisture content for grading and storage purposes. To facilitate the drying process, peanuts are loaded into drying wagons. Then, dryers using propane or natural gas fuels are connected to the wagons through canvas ducts, and heated air is blown into the airspace below the bed of peanuts. The air is forced up through the peanuts to decrease their moisture content. Peanuts are dried in this fashion until they are expected to have less than 10.5% moisture content. Then, a representative sample of peanuts is extracted from the wagon and taken to be graded. While being graded, if the kernel moisture content is determined to be more than 10.5%, the sample is marked with a label, “NO SALE”, and the corresponding lot of peanuts has to be taken back to the drying shed and further dried. Modern peanut drying processes utilize decision support software based on modeling and require substantial human interaction for moisture sampling. The samples must be taken, shelled and cleaned before testing for kernel moisture content with current moisture meters. The kernel moisture content is the main parameter of interest in the drying process, and it is the only parameter, besides temperature, that the drying system is working to control. However, since it is difficult to obtain, the control for kernel moisture content is often indirect and misguided. These procedures increase the likelihood of peanuts being overdried or underdried. This research addressed the need for an automated controller with real-time, in-shell kernel moisture content determination capabilities. An automatic control system was developed by using a microwave moisture meter, developed within USDA, ARS. The moisture content of the peanut kernel can be determined without having to shell the pod peanuts. The kernel moisture content and atmospheric conditions serve as continuous inputs to the controller, and thus, air temperature and drying time are controlled automatically. Such implementation reduces overdrying and underdrying, preserves quality of peanuts, and minimizes energy consumption through efficient control of the heater. In this research, a quarter-scale drying system with automated control was tested for drying pod peanuts. Results showed that the automated drying system with the microwave kernel moisture sensor is an effective solution for real-time kernel moisture content monitoring during the drying process. Results show promise for large-scale implementation. When implemented commercially, such control systems would save significant labor and energy costs while improving product quality for the peanut industry and consumers.
Technical Abstract: Peanut drying is an essential task in the processing and handling of peanuts. Peanuts leave the fields with kernel moisture contents > 20% wet basis and need to be dried to < 10.5% w.b. for grading and storage purposes. Current peanut drying processes utilize decision support software based on modeling and require substantial human interaction to adjust dryer settings based on atmospheric conditions and obtain kernel moisture content while drying. These conditions increase the likelihood of peanuts being overdried or underdried. Therefore, this research addressed the need for a drying system with real-time monitoring of atmospheric conditions and in-shell kernel moisture content, and dryer control capabilities. By using a microwave moisture meter, developed within USDA ARS, the moisture content of the peanut kernel can be determined without having to shell the peanut pods. The kernel moisture content, ambient air temperature and relative humidity, peanut bed temperature and heated-air temperature were monitored by the sensor network and served as inputs to the controller. Thus, temperature of the heated air and drying time were controlled automatically. The sensor network consisted of five sensors, and monitoring and feedback control were facilitated by a microcontroller. Such implementation would reduce overdrying and underdrying, preserve peanut quality, and minimize energy consumption through more efficient control of the heater. This manuscript discusses a quarter-scale drying system with automated control.