Location: National Peanut Research Laboratory2021 Annual Report
Objective 1: Resolve underlying issues with commercial drying systems to decrease energy consumption, drying time, labor, and increase product uniformity. [NP306, C1, PS1A] Objective 2: Develop commercial management systems that enable improved aeration and headspace ventilation in farmers’ stock peanut storage to reduce post-harvest losses due to over drying, mold growth, aflatoxin contamination, and insect infestation. [NP306, C1, PS1A] Subobjective 2A. Develop decision support system to evaluate and manage farmers’ stock warehouses. Subobjective 2B. Develop instrumentation for early detection of fire in farmers’ stock warehouse. Objective 3: Develop innovative commercially-relevant peanut drying and handling systems to improve drying uniformity, aeration, and headspace ventilation in farmers’ stock that reduces/eliminates improper drying, mold growth, aflatoxin contamination, and insect infestation; and develop effective RNAi field delivery systems for peanuts. (NP 306; C1, PS 1A)
The post-harvest processing between the farm gate and the peanut product manufacturer can be broken down into several distinct unit operations. Two of these unit operations, drying at the first point of sale and bulk farmers’ stock storage prior to shelling have primary objectives of reducing and maintaining the peanut kernel moisture content at levels safe for storage, further processing, and handling. Advanced engineering modeling will be used to simulate the airflow and drying uniformity in existing drying systems and bulk farmers’ stock warehouses. The models will be used to design and guide construction and testing of prototype drying and aeration systems to improve product uniformity and storability. Existing data from commercial storage facilities and simulation models will guide the development of decision support systems for segregating and storing farmers’ stock peanuts and minimize deterioration during storage due to mold growth, increased aflatoxin contamination, and insect infestation. Laboratory experiments will determine the products of smoldering combustion of peanuts and sensors to detect those products selected or designed for the purpose of early fire detection in farmers’ stock warehouses. Molecules that induce RNA interference (RNAi) to interrupt the pre-harvest production of aflatoxin are under development in another research project. Conventional spraying, electrostatic spraying, and non-contact injection will be investigated as effective methods of delivering the RNAi molecules to the peanut plant.
Groundwork for a collaboration with engineers at Dawson, Georgia, and the ARS Partnership for Data Innovation has been prepared to utilize commercial farmers’ stock peanut storage data to model the potential increase in accumulation of aflatoxin during storage. Data Transfer Agreements with at least one commercial sheller are being prepared for use in developing and validating the models. Computational Fluid Dynamics software simulates fluid flow according to prescribed physical parameters and was used by engineers to design modifications for a hopper-bottom semi-trailer for drying peanuts. ARS engineers at Dawson, Georgia in collaboration with Clemson University engineers, fabricated and tested the hopper-bottom semi-trailer for drying peanuts during the 2020 peanut harvest at a peanut buying facility in South Carolina. ARS engineers conducted studies in collaboration with the United States Forest Service and United States EPA to measure the airborne composition of the products of smoldering in-shell peanuts at the United States Forest Service’s Fire Science Laboratory in Missoula, Montana. Data analysis is underway.
Butts, C.L., Dean, L.L., Hendrix, K., Arias De Ares, R.S., Sorensen, R.B., Lamb, M.C. 2021. Hermetic storage of shelled peanut using the purdue improved crop storage bags. Peanut Science. 48(1):22-32. https://doi.org/10.3146/PS20-31.1.
Butts, C.L., Sorensen, R.B., Lamb, M.C. 2020. Irrigator Pro: progression of a peanut irrigation scheduling decision support system. Applied Engineering in Agriculture. 36(5): 785-795. https://doi.org/10.13031/aea.13909.