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ARS Home » Southeast Area » Athens, Georgia » U.S. National Poultry Research Center » Quality and Safety Assessment Research Unit » Research » Publications at this Location » Publication #286216
Title: An automated approach to peanut drying with real-time microwave monitoring of in-shell kernel moisture content

Author
item Lewis, Micah
item Trabelsi, Samir
item NELSON, STUART - Collaborator
item TOLLNER, ERNEST - University Of Georgia
item HAIDEKKER, MARK - University Of Georgia

Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/18/2013
Publication Date: 8/1/2013
Citation: Lewis, M.A., Trabelsi, S., Nelson, S.O., Tollner, E.W., Haidekker, M.A. 2013. An automated approach to peanut drying with real-time microwave monitoring of in-shell kernel moisture content. Applied Engineering in Agriculture. 29(4).

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 below 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 peanut pod. 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 paper, a quarter-scale drying system with automated control is discussed. 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 preceding the grading process. Kernel moisture is one of five parameters used to establish the grade for a specific lot of peanuts, and it is imperative that peanuts be dried to a kernel moisture content < 10.5% wet basis for grading and storage purposes. Today’s peanut drying processes utilize decision support software based on modeling and require substantial human interaction for moisture sampling. These conditions increase the likelihood of peanuts being overdried or underdried. This research addresses 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 peanut pods. The kernel moisture content and atmospheric conditions serve as 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 paper, a quarter-scale drying system with automated control is discussed. Results show promise for large-scale implementation and testing.