Title: Evaluation of in-shell kernel moisture content monitoring with a microwave moisture meter during peanut drying Authors
Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: June 10, 2013
Publication Date: N/A
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. 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 of different moisture levels, dried under different ambient conditions, and 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: Present peanut drying processes lack the capability of kernel moisture content determination in real-time. Samples of peanut pods have to be taken from the drying trailer, cleaned and shelled in order to test for the kernel moisture content. 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 microwave moisture meter operates at 5.8 GHz at power levels of a few milliwatts. An automated quarter-scale drying system, using the microwave meter, was developed and tested successfully. The drying system utilizes the microwave meter in a dynamic setting, one in which the moisture content of the peanut pods and kernels is constantly changing. To evaluate the stability of the real-time kernel moisture content monitoring, peanut-drying trials were run with varying initial kernel moisture contents. During each trial, samples were extracted and shelled to conduct moisture tests by the reference oven drying method. Analysis of variance was performed, and standard errors of performance were evaluated to compare the kernel moisture content values predicted by the microwave moisture meter to those determined by the oven method. Results indicate that there were no significant differences between kernel moisture content determined by the microwave meter and by the oven method. Overall evaluation showed that the automated drying system, with microwave moisture meter, is an effective solution for real-time in-shell kernel moisture content monitoring during the drying process.