Progress 10/01/23 to 09/30/24
Outputs
PROGRESS REPORT Objectives (from AD-416): 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) Approach (from AD-416): 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. Manuscript on CFD modeling of airflow in modified walnut drying bins compared to measured flow written and accepted for publication in journal Applied Engineering in Agriculture. Manuscript is product of collaboration with ARS Cotton Ginning Research: Las Cruces. ARS researchers at Dawson, Georgia successfully used time-lapse photography of peanuts to add information to other National Peanut Research Laboratory projects. Manuscript of with time-lapse results has been written and submitted. Proposal for early detection of fires in peanut warehouses won 18th Round of the Innovation Fund. Collaboration with University of Texas Arlington engineer has produced prototype early fire detection sensor units for testing in farmers⿿ stock peanut warehouses. Collaboration with USDA-ARS Cotton Production and Processing Research Unit produced Aerodyne Mobile Lab burn experiments that expanded number gases and volatiles that can be used as early fire indicators. Peanut hull strength measurements made of peanuts exposed to post harvest rainfall produced results that have been accepted for presentation at American Peanut Research and Education Society annual meeting for 2024. Hull strength measurements of peanuts from experimental varieties adding new data to ongoing research projects at National Peanut Research Laboratory and expanding knowledge of factors effecting peanut hull strength. Collaboration with USDA-ARS Southern Regional Research Center researchers to develop aflatoxin contamination forecast model for farmers⿿ stock peanuts stored in warehouses is advancing with National Peanut Research Laboratory providing data and peanut storage expertise to modeling specialists on team. Collaboration with ARS Cotton Ginning Research: Las Cruces Agricultural Research Engineer is advancing with experiments conducted to test new designs for modifications to enhance airflow in drying bins produced by modeling conducted at National Peanut Research Laboratory. Continuing collaboration with NASA-Langley to design a practical muffler for peanut dryers. ACCOMPLISHMENTS 01 Results of Aerodyne Mobile Lab. Results of Aerodyne Mobile Lab visit have shown carbon dioxide is a significant pre-fire and fire indicator. Early-fire-detection-system sensor suite has been expanded to include carbon dioxide. Addition of carbon dioxide to the system allows it to detect the first signs of biologically caused spontaneous fires due to the carbon dioxide produced by fungal infestation of damp peanuts and cottonseed. Addition of carbon dioxide sensors expands the early-fire detection system function to real time monitoring of agricultural warehouse storage performance. Experiments in conjunction with ARS Cotton Production and Processing Research Unit into detection of carbon dioxide increase from fungal infestation of stored farmers⿿ stock peanuts and cottonseed are at the equipment collection and assembly stage.
Impacts
(N/A)
Publications
- Mcintyre, J.S., Cook, H. 2023. Noise levels of a peanut dryer in an open shed with and without a muffler. Peanut Science. 50(1)P.22-28. https://doi. org/10.3146/0095-3679-501-PS22-13.
- Butts, C.L., Lamb, M.C., Zimmer, K., Santos, R., Hoisington, D., Adams, J., Cowart, D., Tillman, B., Kemerait, R.C., Marshall, J., Jackson, M., Davis, J., Sterling, S., Elder, J. 2023. U.S. peanut quality: Industry priorities to mitigate aflatoxin risk from farm to consumer. Peanut Science. 50(1), p.29-40. https://doi.org/10.3146/0095-3679-501-PS22-15.
- Bidese-Puhl, R., Butts, C.L., Rewis, M., Mcintyre, J.S., Morris, J., Branch, B., Bao, Y. 2023. An mmWave radar-based mass flow sensor using machine learning towards a peanut yield monitor. Computers and Electronics in Agriculture. 215: Article 108340. https://doi.org/10.1016/j.compag.2023. 108340.
- Faustinelli, P.C. 2023. In vitro peanut culture: from seed to seed. Current Protocols in Plant Biology. 3(11). Article e918. https://doi.org/ 10.1002/cpz1.918.
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Progress 10/01/22 to 09/30/23
Outputs
PROGRESS REPORT Objectives (from AD-416): 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) Approach (from AD-416): 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. We submitted a manuscript on noise produced by a peanut dryer in open shed with and without a muffler. We began collaboration with University of Texas Arlington engineer to develop field deployable sensors for early detection of fires in farmers⿿ stock peanut warehouses. In collaboration with USDA-ARS Cotton Production and Processing Research Unit to we investigated expanding early fire detection project to cotton product storage facilities. Peanut hull strength measurements made of peanuts exposed to post harvest rainfall and peanuts from experimental varieties adding new data to ongoing research projects at National Peanut Research Laboratory and expanding knowledge of factors effecting peanut hull strength. In collaboration with USDA-ARS Southern Regional Research Center researchers will develop aflatoxin contamination forecast model for farmers⿿ stock peanuts stored in warehouses. Collaboration with ARS Cotton Ginning Research: Las Cruces Agricultural Research Engineer we conducted research on modeling and improving airflow through walnuts during drying. We continue collaboration with NASA-Langley to design a practical muffler for peanut dryers.
Impacts
(N/A)
Publications
- Sorensen, R.B., Lamb, M.C., Butts, C.L. 2022. Corn yield response to irrigation level, crop rotation, and irrigation system. Journal of Crop Improvement. 36(5):701-716. https://doi.org/10.1080/15427528.2021.2005212.
- Sorensen, R.B., Lamb, M.C., Butts, C.L. 2022. Corn, cotton, and peanut response to row spacing, seeding rate, and irrigation system. Journal of Crop Improvement. (37)3:323-340. https://doi.org/10.1080/15427528.2022. 2093809.
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Progress 10/01/21 to 09/30/22
Outputs
PROGRESS REPORT Objectives (from AD-416): 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) Approach (from AD-416): 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. Manuscript completed on the use of Computational fluid dynamics (CFD) to model airflow through peanuts in drying trailer written, submitted, and published. Onsite tests of hopper trailer modified for drying peanuts was completed. Manuscript written, submitted, and published based on data. At stakeholders⿿ request, initiated collaboration with NASA-Langley to build and test a prototype dryer muffler. With addition of a universal testing machine, ARS scientists at Dawson, Georgia, conducted tests to measure hull strength of peanuts grown with different soil amendments in collaboration with University of Florida scientists. Received 5 years of peanut quality data through an Incoming Data Transfer Agreement and initiated collaborative work with the Partnership for Data Innovation to develop models to predict changes in quality during farmers stock storage.
Impacts
(N/A)
Publications
- Sorensen, R.B., Lamb, M.C., Butts, C.L. 2021. Corn yield as affected by row pattern, plant density, and irrigation system. Journal of Crop Improvement. https://doi.org/10.1080/15427528.2021.1980754.
- Patel, J.D., Wang, M.L., Dang, P.M., Butts, C.L., Lamb, M.C., Chen, C.Y. 2022. Insights into the genomic architecture of seed and pod quality traits in the U.S. peanut mini-core diversity panel. Plants. 11(7):837. https://doi.org/10.3390/plants11070837.
- Mcintyre, J.S., Butts, C.L., Read, Q.D. 2022. Computational fluid dynamics modeled air speed through in-shell peanuts in drying wagons compared to measured air speed. Applied Engineering in Agriculture. 38(3):489-508. https://doi.org/10.13031/aea.14771.
- Mcintyre, J.S., Turner, A.P., Teddy, B.E., Fogle, B., Butts, C.L., Kirk, K. R. 2022. Hopper-bottom semi-trailer modified for in-shell peanut drying: design, fabrication, and performance testing. Applied Engineering in Agriculture. 38(3):477-488. https://doi.org/10.13031/aea.14869.
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Progress 10/01/20 to 09/30/21
Outputs
PROGRESS REPORT Objectives (from AD-416): 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) Approach (from AD-416): 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. Record of Any Impact of Maximized Teleworking Requirement: The requirement of Maximized Telework due to COVID-19 had significant impact on research primarily due to the limited on-site work that could be conducted. However, ARS scientists at Dawson, Georgia, assigned to this project exhibited considerable flexibility by moving research that could be completed under maximized telework up in the planned schedule while delaying research that required significant on-site presence. The Area Office staff allowed for extenuating circumstances to complete other important research that arose from these changes in priority. The forced slow down did provide time for ARS scientists to catch up on analyzing and publishing accumulated data. The flexibility of stakeholders, research leaders, area office, and national program staff allowed scientists and technical support staff to respond and continue progress toward meeting our stated goals.
Impacts
(N/A)
Publications
- 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.
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