Progress 10/01/23 to 09/30/24
Outputs
PROGRESS REPORT Objectives (from AD-416): OBJECTIVE 1: Develop commercially viable methods and technologies for use before ginning that reduce harvest costs, preserve fiber/seed quality, enhance the utilization of production/harvest/gin data, and prevent/ minimize contamination of upland cotton. Subobjective 1A: Assessing the influence of seed cotton storage in round modules on lint and seed quality. Subobjective 1B: Improving the cleanliness and quality of stripper- harvested cotton through improved field cleaning systems. Subobjective 1C: Development of equipment to detect and remove contaminants from cotton during the harvesting process. OBJECTIVE 2: Enable commercially preferred technologies/methods/ strategies for use in ginning upland cotton that improve cleanliness of seed cotton and lint, detect/remove contamination, preserve fiber quality, and reduce financial costs. Subobjective 2A: Development of equipment to detect and remove contaminants from cotton in the harvest and ginning processes. Subobjective 2B: Improving cotton fiber length distribution through novel lint cleaner design. OBJECTIVE 3: Develop commercially viable post-ginning technologies/ techniques that enhance the storage and utilization of upland cotton products/coproducts/byproducts and reduce the environmental footprint of cotton production/processing. Subobjective 3A: Development of a commercially viable mechanical cottonseed delinting system to remove cotton linters and produce planting quality seed, without the use of chemicals. Subobjective 3B: Reducing particulate emissions from cotton ginning through improved pollution abatement device design using computational fluid dynamics (CFD) and laboratory testing. Subobjective 3C: Develop and evaluate the use of cotton plant constituents and other natural fibers in the manufacture of composite materials. Approach (from AD-416): This five-year project plan addresses critical pre-ginning, ginning and post-ginning issues facing cotton producers and processors in the United States. Our plan of work is based on an interactive research approach which is focused on the development of processes and systems for preserving cotton quality during infield storage and ginning, removing foreign material and contaminants from seed cotton during harvesting and ginning, reducing particulate emissions from ag operations, reducing the environmental impact of acid cottonseed delinting, and increasing the value of cotton byproducts though composite materials. The research plan detailed herein addresses the development of new technologies, methods, and strategies for reducing the economic and environmental costs of cotton harvest, ginning, and post-gin processing of upland cotton and cotton by-products. Commercial viability of the research is a key component of any problem solution. Objective 1: Field scale experiments were conducted in Mississippi and Texas to investigate the relationship between the change in fiber and seed quality parameters as a function of seed cotton moisture content at harvest and storage period length. The accuracy of several non-reference method devices that measure seed cotton moisture content was evaluated and several devices performed well under field conditions compared to the oven-based reference method. Data on round modules formed from both machine picked and stripped cotton was collected. The modules were ginned at cooperating commercial gins near the growing locations in Texas and Mississippi and quality analyses were conducted on samples of seed and lint collected during the ginning process. Limited data on high moisture content modules were obtained in 2024 and only minor effects on leaf grade and fiber color were observed. Additional experiments to document the change in fiber and seed quality as a function of harvest moisture content and storage duration are ongoing. Scientific presentations to stakeholder groups have been given to report the results of this work. A new field cleaner was designed and implemented on commercial state-of- the-art cotton strippers. The new machine exhibits improved cleaning efficiency and decreased seed cotton loss compared to prior models. Experiments to optimize the cleaning performance and seed cotton loss of the new machine were carried out under laboratory and field conditions and the resulting saw speed and grid bar settings have been communicated to the research partner through presentations and technical reports for implementation on new year model harvesters. Additional work to further enhance the cleaning performance of the new field cleaner was carried out through the design and testing of an active laydown cylinder. The novel laydown cylinder restrains the flow of cotton to maximize the engagement of seed cotton on the top saw cylinder while actively passing the excess flow of seed cotton directly to the second saw. Experiments were conducted to document the performance of the new laydown cylinder and provide control models for balancing material flow between the top two saw cylinders. Additional experiments are underway to document the effect of the new flow balancing system on cleaning performance and seed cotton loss. Protocols for evaluating the presence of plastic contamination immediately in front of a harvester have been developed. A design for the mechanical exclusion of plastic contamination has been developed and fabricated. This equipment is designed to be utilized in conjunction with a smart machine-vision system to provide detection, which will then provide the signal to actuate the mechanical exclusion system. The smart machine-vision sensor has been designed and fabricated. Work is ongoing on the development of the machine vision software, which is the heart of the detection system. Traditional machine learning classifiers are being assessed for their potential use in detecting plastic contamination and show promise. In parallel, deep learning models are being assessed for this purpose because of their significant promise for use in uncontrolled lighting environments where traditional machine vision algorithms struggle. Recent developments have produced several deep learning models that appear promising. In particular, a new artificial intelligence paradigm for image classification has been found to be particularly effective: the Vision Transformer (an image classification implementation of the large-language models). This new approach is providing lighting- independent classification of plastic, a critically important milestone for use in outdoor environments such as on harvesters. Plans are underway to test these new models in the upcoming harvest season. Scientific presentations have reported on the new models and algorithms. Objective 2: Plastic contamination detection and removal systems have been designed and fabricated, and several commercial trials have been conducted. Testing and evaluation of the system were completed in laboratory studies using a cut-down extractor feeder with commercial- scale cross-sectional geometry. Further studies have commenced to explore practical utilization in commercial cotton gins. Initial test results have been successful for several of the primary sources of plastic contamination that the industry struggles with, specifically plastic that comprises more than 85% of contamination found at the USDA - Agricultural Marketing Service classing offices. The research revealed a significant impediment to the adoption of the technology due to a lack of skilled personnel available to run the system. To address this issue, additional work was conducted on the development of an auto-calibration system that will eliminate the need for personnel to monitor and periodically adjust the calibration of the detection system due to changing cotton conditions. The work appears promising when benchmarked against previously obtained commercial field data. Several high-speed AI models have been developed to support the auto-calibration system. Given the promise of this approach, further testing is planned in commercial field trials. Scientific presentations have reported on the new models and algorithms. Air-type lint cleaners are commonly used after the gin stand to remove heavy foreign matter such as seed coats, seed meats, and other vegetative material from ginned lint before it is processed by more aggressive saw- type lint cleaners. A novel multi-stage air-type lint cleaner was developed and tested for use in processing small samples from breeding and agronomic development research. Elements of the design of the multi- stage air-type lint cleaner have been included in a U.S. patent and the performance of the machine was documented and the results communicated to the research partner through technical presentations and reports. Additional work to scale up the design for use under commercial ginning conditions is underway. Objective 3: The 8-ft prototype mechanical delinter was installed in a commercial cotton gin in New Mexico and organic Pima cottonseed was processed through the unit over a 4-day period. The processed Pima seed was from one of the cotton gin⿿s customers who farms both conventional and organic cotton. The delinted organic Pima cottonseed was planted this year (2024) and will be ginned in the 2024-2025 ginning season. Computational fluid dynamic (CFD) simulation software was developed to study particulate-laden air streams. Experimental testing showed that typical air flows in baffle-type pre-separators exhibit turbulent flow as the dominant flow regime. Consequently, the simulation model was developed to include turbulent flow models with two-way interaction between the particulates and the air stream. However, recent advances in CFD have greatly improved the accuracy of turbulent separating flows via Large-Eddy Simulation (LES) models. Given these significantly improved turbulence models, it was deemed important to redevelop the CFD models to leverage this new technology. While the original turbulence model simulations suggested potential for using an additional skimmer plate in the baffle-type pre-separator to enhance cleaning efficiency, this new, more accurate approach calls this into question. The LES CFD model uncovered previously unappreciated pulse flow mechanisms that suggest significant modifications will be needed to adapt the current physical design to more optimally capture the transition particles, as well as anticipated modifications to the currently accepted guidance for air flow and mass-loadings through the pre-separator. To test the new, improved model, the prototype will be reworked to reflect the insights gained. The next step is to conduct experimental validation tests. Currently, designs are being reviewed, and plans are underway for evaluating the experimental test unit. Seven lignin coated cellulose nanocrystal composite samples were produced and tested at a university partner⿿s location. The samples evaluated various treatments of ultrasonic amplitude and duration for dispersion of the ligno-cellulosic nanocrystals (L-CNC) in a polyethylene-based solution to improve morphology and mechanical properties of bio-based materials made from L-CNC. Results showed the highest amplitude with the longest time interval produced a 300% improvement in observed properties compared to the other treatments. Artificial Intelligence (AI)/Machine Learning (ML) Several AI and machine learning models have been developed to support a fully automated Plastic Detection and Inspection System used to help mitigate plastic contamination in cotton gins. The AI models are custom Vision Transformer models (extensions of Large Language Models applied to images) and the machine learning models are several custom image classifiers and an image texture analyzer utilizing optical flow methodology. These models provide real time classification of images to detect plastic and reject false positives caused by transient events (e.g. gin personnel placing their hands, arms, and various colored objects into camera view). A recent validation study of over 6,500 images produced promising results, with a combined AI-machine-vision model exhibiting greater than 98% accuracy in the proper identification of plastic and rejecting 99% of false positives. AI technology has enabled breakthroughs in performance which eliminate the need for expensive manual calibration techniques that required expert gin personnel to perform. Manual calibration of the detection systems requiring expensive expert labor was a formidable barrier to adoption by the ginning industry that has been completely removed by the new automated calibration technique built on AI. The graphical processing units required to perform AI model development were located from external sources. ACCOMPLISHMENTS 01 A round cotton module rotating wheel-loader work tool for reducing plastic contamination. Plastic contamination in U.S. grown cotton has increased with the adoption of new harvesters that form cylindrical or ⿿round modules of seed cotton wrapped in multi-layer plastic film. The increase in plastic contamination is estimated to cost the U.S. cotton industry approximately $750 million annually. Research has shown that much of the plastic contamination originates from segments of the plastic wrap that inadvertently remain in the cotton after the wrap is manually cut and removed from the modules. It is often the case that the wrap is cut at an inappropriate location which causes small pieces of the inner wrap layer to remain in the cotton. To address this issue, ARS researchers at Lubbock, Texas, developed a new hydraulically actuated work tool for use on wheel loaders that rotates round cotton modules into proper position for manual wrap cutting. In automatic positioning mode, the system controls the rotational position of round modules by sensing the location of radio frequency identification tags embedded in the plastic module wrap. Use of this system was shown to reduce the incidence of plastic contamination by 50% at a cooperating commercial ginning facility.
Impacts
(N/A)
Publications
- Bajwa, D., Holt, G.A., Stark, N., Bajwa, S., Chanda, S., Quadir, M. 2023. Nano boron oxide and zinc oxide doped lignin containing cellulose nanocrystals improve the thermal, mechanical and flammability properties of high-density poly (ethylene). Polymers. 16(1). https://doi.org/10.3390/ polym16010036.
- Pelletier, M.G., Wanjura, J.D., Wakefield, J.R., Holt, G.A., Kothari, N. 2023. Cotton gin stand machine-vision inspection and removal system for plastic contamination: Hand intrusion sensor design. AgriEngineering. 6(1). https://doi.org/10.3390/agriengineering6010001.
- Armijo, C.B., Delhom, C.D., Whitelock, D.P., Tumuluru, J., Yeater, K.M., Rowe, C., Wanjura, J.D., Sui, R., Holt, G.A., Martin, V.B., Kothari, N. 2023. Evaluation of alternative-design cotton gin lint cleaning machines on fiber length uniformity index. AgriEngineering. 5(4):2123-2138. https:// doi.org/10.3390/agriengineering5040130.
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Progress 10/01/22 to 09/30/23
Outputs
PROGRESS REPORT Objectives (from AD-416): OBJECTIVE 1: Develop commercially viable methods and technologies for use before ginning that reduce harvest costs, preserve fiber/seed quality, enhance the utilization of production/harvest/gin data, and prevent/ minimize contamination of upland cotton. Subobjective 1A: Assessing the influence of seed cotton storage in round modules on lint and seed quality. Subobjective 1B: Improving the cleanliness and quality of stripper- harvested cotton through improved field cleaning systems. Subobjective 1C: Development of equipment to detect and remove contaminants from cotton during the harvesting process. OBJECTIVE 2: Enable commercially preferred technologies/methods/ strategies for use in ginning upland cotton that improve cleanliness of seed cotton and lint, detect/remove contamination, preserve fiber quality, and reduce financial costs. Subobjective 2A: Development of equipment to detect and remove contaminants from cotton in the harvest and ginning processes. Subobjective 2B: Improving cotton fiber length distribution through novel lint cleaner design. OBJECTIVE 3: Develop commercially viable post-ginning technologies/ techniques that enhance the storage and utilization of upland cotton products/coproducts/byproducts and reduce the environmental footprint of cotton production/processing. Subobjective 3A: Development of a commercially viable mechanical cottonseed delinting system to remove cotton linters and produce planting quality seed, without the use of chemicals. Subobjective 3B: Reducing particulate emissions from cotton ginning through improved pollution abatement device design using computational fluid dynamics (CFD) and laboratory testing. Subobjective 3C: Develop and evaluate the use of cotton plant constituents and other natural fibers in the manufacture of composite materials. Approach (from AD-416): This five-year project plan addresses critical pre-ginning, ginning and post-ginning issues facing cotton producers and processors in the United States. Our plan of work is based on an interactive research approach which is focused on the development of processes and systems for preserving cotton quality during infield storage and ginning, removing foreign material and contaminants from seed cotton during harvesting and ginning, reducing particulate emissions from ag operations, reducing the environmental impact of acid cottonseed delinting, and increasing the value of cotton byproducts though composite materials. The research plan detailed herein addresses the development of new technologies, methods, and strategies for reducing the economic and environmental costs of cotton harvest, ginning, and post-gin processing of upland cotton and cotton by-products. Commercial viability of the research is a key component of any problem solution. Objective 1: A preliminary field experiment to document the change in fiber and seed quality for cotton stored in round modules as a function of harvest moisture content and storage duration was conducted. The protocol was developed for a full-scale field test that included four moisture content ranges and six storage duration periods. However, the experiment was cut down in scope this year due to the lack of cotton available for the test. Seed cotton in the modules was picker harvested with moisture content ranging from about 13% to over 20%. The cotton was harvested with high moisture levels to affect expected changes in fiber quality during storage. The modules were stored for 55 days before they were ginned. Samples collected before and after storage indicated increases in fiber yellowness and decreases in fiber reflectance ⿿ both which indicate degradation in color grade. Other fiber properties exhibited negative changes during the storage period and additional analysis of the data is ongoing to determine the overall effect of the observed storage conditions on the economic value of the cotton. This preliminary test pointed out areas in the protocol that need to be modified before large-scale experiments can be conducted. Two large scale field locations near Lubbock, Texas, and Stoneville, Mississippi, have been planted to cotton and will be used to carry out this investigation in the upcoming harvesting season. A new field cleaner was designed and implemented on commercial state-of- the-art cotton strippers. The new machine exhibits improved cleaning efficiency and decreased seed cotton loss compared to prior models. Additional experiments with the new field cleaner to optimize saw speeds and cleaning grid spacing around each saw were conducted and analysis of the data is ongoing. In a separate effort, development work was carried out to evaluate new techniques to balance the material flow between the upper and lower saw cylinders in efforts to further improve cleaning efficiency and throughput capacity. These tests yielded insight into new areas for design improvement to improve the application and retention of seed cotton on the primary cleaning saw. New designs for an active laydown cylinder were developed and modifications to the machine are underway for laboratory evaluation of these concepts. Protocols for evaluating the presence of plastic contamination immediately in front of a harvester were developed. A design for mechanical exclusion of plastic contamination was developed and fabricated. This equipment is designed to be utilized in conjunction with a smart machine-vision system to provide detection, which will then provide the signal to actuate the mechanical exclusion system. The smart machine-vision sensor has been designed and fabricated. Work is ongoing on the development of the machine vision software that is the heart of the detection system. Traditional machine learning classifiers are being assessed for their potential use in detection of plastic contamination and show promise. In parallel, deep learning models are being assessed for this purpose because of their significant promise for use in uncontrolled lighting environments where traditional machine vision algorithms struggle. Recent developments have produced several deep learning models that appear promising. Plans are underway to test these new models in the upcoming harvest season. Scientific presentations have reported on the new models and algorithms. Objective 2: Plastic contamination detection and removal systems have been designed and fabricated. Testing and evaluation of the system is on- going in laboratory studies on a cut-down extractor feeder with commercial scale cross-sectional geometry. Initial test results have been successful for several of the primary sources of plastic contamination that the industry struggles with (plastic that comprises more than 85% of contamination found at the USDA - Agricultural Marketing Service classing offices). Additional work on machine-vision classifier exploration is continuing for alternative classification algorithms for more challenging plastic contamination colors such as black and clear. The research revealed a significant impediment to adoption of the technology due to a lack of skilled personnel available to run the system. To address this issue, additional work was conducted on the development of an auto- calibration system that will eliminate the need for personnel to monitor and periodically adjust the calibration of the detection system, due to changing cotton conditions. The initial work appears promising when benchmarked against previously obtained commercial field data. Given the promise of the approach, further testing is planned in upcoming commercial field trials. Scientific presentations have reported on the new models and algorithms. Air-type lint cleaners are commonly used after the gin stand to remove heavy foreign matter such as seed coats, seed meats, and other vegetative material from ginned lint before it is processed by more aggressive saw- type lint cleaners. A novel multi-stage air-type lint cleaner was developed and tested for use in processing small samples from breeding and agronomic development research. This machine is more efficient at removing foreign matter from ginned lint than its single-stage counterparts, but its main advantage is that it does not break fibers and degrade the fiber length distribution. A large-scale prototype of the multi-stage air-type lint cleaner is under development for testing under commercial ginning conditions. Objective 3: Modifications to the prototype cottonseed preconditioning system have started after the arrival of the much-awaited parts from last year which were delayed due to supply chain issues. In addition, the 8-ft mechanical cottonseed delinter was taken to a commercial cotton gin where it is being installed for evaluation during the upcoming ginning season. Also, a commercial seed company requested a copy of our computer aided design drawings of the mechanical delinter in order to build a similar unit themselves. Computational fluid dynamic simulation software was developed to study particulate laden air streams. Experimental testing shows that typical air flows in baffle type pre-separators exhibit turbulent flow as the dominant flow regime. As such, the simulation model was developed to include turbulent flow models with 2-way interaction between the particulates and the air stream. Simulations revealed potential for use of an additional skimmer plate in the baffle-type pre-separator to enhance cleaning efficiency of the system. To test the model, a baffle- type pre-separator system has been fabricated. The next step is to conduct experimental validation tests. Currently, designs are being reviewed and plans are underway for testing of the experimental test unit. Five thermoplastic composite samples were produced and tested with replication at a university partner⿿s location. The samples evaluated various levels of Zinc and Boron oxide additions to the blends to improve flammability issues commonly associated with thermoplastic composites. ACCOMPLISHMENTS 01 Launch of a transformative scientific journal, AgriEngineering. This new peer-reviewed journal allows not just traditional scientific research papers but also methods papers, a first in the field of Agricultural Engineering. Methods papers provide essential "how-to" guides for specific technologies and experiments, accelerating technology transfer and the overall pace of scientific discovery. By enabling the sharing of these methodologies, significant barriers to entry have been removed for research groups venturing into new areas, reducing duplicate efforts, and promoting greater innovation and efficiency within the agricultural engineering community. AgriEngineering, launched in 2019, has now matured to the point where it is SCOPUS indexed, has a CITE-Score of 4.6, and an Impact-Factor of 2.8.
Impacts
(N/A)
Publications
- Sayeed, M., Turner, C., Kelly, B., Wanjura, J.D., Smith, W., Schumann, M., Hequet, E. 2023. A new method to calculate cotton fiber length uniformity using the HVI fibrogram. Agronomy Journal. 13(5). https://doi.org/10.3390/ agronomy13051326.
- Hardin, R.G., Barnes, E.M., Delhom, C.D., Wanjura, J.D., Ward, J.K. 2022. Internet of things: cotton production and processing. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2022.107294.
- Funk, P.A., Thomas, J.W., Yeater, K.M., Kothari, N., Armijo, C.B., Whitelock, D.P., Wanjura, J.D., Delhom, C.D. 2022. Gin saw thickness impact on lint turnout, lint value, and seed damage. Applied Engineering in Agriculture. 38(4):645-650. https://doi.org/10.13031/aea.15171.
- Delhom, C.D., Wanjura, J.D., Hequet, E.F. 2022. Cotton fiber elongation ⿿ a review. Journal of Textile Institute. Article 2157940. https://doi.org/ 10.1080/00405000.2022.2157940.
- Delhom, C.D., Wanjura, J.D., Pelletier, M.G., Holt, G.A., Hequet, E.F. 2023. Investigation into a practical approach and application of cotton fiber elongation. Journal of Cotton Research. 6. Article 2. https://doi. org/10.1186/s42397-023-00139-w.
- Pelletier, M.G., Wanjura, J.D., Kothari, N., Holt, G.A. 2023. Cotton gin stand machine-vision inspection and removal system for plastic contamination: Auto-calibration design. AgriEngineering. 3(3). https://doi. org/10.3390/agriengineering3030033.
- Delhom, C.D., Van Der Sluijs, M.J., Wanjura, J.D., Thomas, J.W. 2023. Evaluation of practices to unwrap round cotton modules. Journal of Cotton Science. 27:90-101. https://doi.org/10.56454/IPOU8527.
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Progress 10/01/21 to 09/30/22
Outputs
PROGRESS REPORT Objectives (from AD-416): OBJECTIVE 1: Develop commercially viable methods and technologies for use before ginning that reduce harvest costs, preserve fiber/seed quality, enhance the utilization of production/harvest/gin data, and prevent/ minimize contamination of upland cotton. Subobjective 1A: Assessing the influence of seed cotton storage in round modules on lint and seed quality. Subobjective 1B: Improving the cleanliness and quality of stripper- harvested cotton through improved field cleaning systems. Subobjective 1C: Development of equipment to detect and remove contaminants from cotton during the harvesting process. OBJECTIVE 2: Enable commercially preferred technologies/methods/ strategies for use in ginning upland cotton that improve cleanliness of seed cotton and lint, detect/remove contamination, preserve fiber quality, and reduce financial costs. Subobjective 2A: Development of equipment to detect and remove contaminants from cotton in the harvest and ginning processes. Subobjective 2B: Improving cotton fiber length distribution through novel lint cleaner design. OBJECTIVE 3: Develop commercially viable post-ginning technologies/ techniques that enhance the storage and utilization of upland cotton products/coproducts/byproducts and reduce the environmental footprint of cotton production/processing. Subobjective 3A: Development of a commercially viable mechanical cottonseed delinting system to remove cotton linters and produce planting quality seed, without the use of chemicals. Subobjective 3B: Reducing particulate emissions from cotton ginning through improved pollution abatement device design using computational fluid dynamics (CFD) and laboratory testing. Subobjective 3C: Develop and evaluate the use of cotton plant constituents and other natural fibers in the manufacture of composite materials. Approach (from AD-416): This five-year project plan addresses critical pre-ginning, ginning and post-ginning issues facing cotton producers and processors in the United States. Our plan of work is based on an interactive research approach which is focused on the development of processes and systems for preserving cotton quality during infield storage and ginning, removing foreign material and contaminants from seed cotton during harvesting and ginning, reducing particulate emissions from ag operations, reducing the environmental impact of acid cottonseed delinting, and increasing the value of cotton byproducts though composite materials. The research plan detailed herein addresses the development of new technologies, methods, and strategies for reducing the economic and environmental costs of cotton harvest, ginning, and post-gin processing of upland cotton and cotton by-products. Commercial viability of the research is a key component of any problem solution. Objective 1: Protocols for evaluating the effect of seed cotton moisture content of cotton stored in plastic wrapped cylindrical modules (round modules) were developed to enable research activities occurring at commercial ginning facilities and under more tightly controlled laboratory conditions. Module moisture content data was collected at a commercial ginning facility in Texas using hand-held seed cotton moisture measurement probes and a system mounted on an articulated wheel loader that measured moisture content when modules were engaged during handling at the gin. The moisture sensor data was compared to reference moisture measurements determined using the standard gravimetric oven-based procedure. Approximately 112 round modules were measured during the experiment and the cotton in the modules was dry with reference moisture content averaging 7.4% with 0.4% standard deviation. The maximum moisture content measured in the modules was 9.2% and was not high enough to produce any detectable effect on post-storage fiber quality. Additional experiments are planned to evaluate post-storage quality of lint and seed for seed cotton with higher moisture content levels stored in round modules. A new field cleaner design was developed and implemented on new cotton strippers manufactured in 2022 and later. The new field cleaner exhibits improved processing capacity and greater cleaning efficiency compared to the field cleaner used on earlier harvesters. This new field cleaner technology has enabled the development of stripper harvesters that can harvest up to 150% more area per field-pass compared to earlier models. Additional work to optimize the cleaning performance of the new field cleaner is underway using novel techniques to better balance material flow rates between the two primary cleaning saw cylinders and increase the amount of saw cylinder surface used to engage and clean cotton. Protocols for evaluating the presence of plastic contamination immediately in front of a harvester were developed. A design for mechanical exclusion of plastic contamination was developed and fabricated. This equipment is designed to be utilized in conjunction with a smart machine vision system to provide plastic detection, which will then provide the signal to actuate the mechanical exclusion system. The smart machine-vision sensor has been designed and fabricated. Work is ongoing on the development of the machine vision software that is the heart of the detection system. Traditional machine learning classifiers are being assessed for their potential use in detection of plastic contamination and show promise. In parallel, deep learning models are being assessed for this purpose because of their significant promise for use in uncontrolled lighting environments where traditional machine vision algorithms struggle. Objective 2: Plastic contamination detection and removal systems have been designed and fabricated. Testing and evaluation of the system is on- going in laboratory studies on a cut-down extractor feeder with commercial scale cross-sectional geometry. Initial test results have been successful for several of the primary sources of plastic contamination that the industry struggles with (plastic that comprises > 85% of contamination found at the USDA Agricultural Marketing Service classing offices). Additional work on machine vision classifier exploration is continuing for alternative classification algorithms for more challenging plastic contamination colors such as black and clear. A multi-stage air-type lint cleaner was designed and evaluated for use in batch processing of small cotton samples. The lint cleaner maintained length distribution characteristics better than the more aggressive saw- type lint cleaner used in the experiment. Additional work to scale up the air-type lint cleaner for evaluation under commercial throughput conditions is underway. The multi-stage air-type lint cleaner was evaluated for use in removing plastic contaminants from ginned lint. While the air-type lint cleaner was effective at removing small amounts of plastic from the lint, the seed cotton cleaners were identified as the most efficient cleaners for removal of the contaminants. Plastic incorporated in seed cotton is typically larger in size and not as entangled in the lint fiber as it is after the gin stand and lint cleaners. The saws and close-tolerance cleaning elements used in gin stands and saw-type lint cleaners tend to shred plastic into small pieces and entangle it in the lint making it much more difficult to remove. Objective 3: Evaluation of the prototype preconditioning system continued on-site at a cooperators commercial facility. Testing revealed the need to replace hydraulic motors with electrical motors and a gear ratio low enough to provide the needed torque while meeting the optimal speeds encountered during testing of the lab-scale version. The system was brought back to the ARS facility to make needed changes and to order the necessary equipment. Currently, we are waiting for supply chain issues to resolve to get the necessary motors, sprockets, variable speed drives, and motors to resume evaluation of the system. Computational fluid dynamic simulation software was developed to study particulate laden air streams. Experimental testing shows that typical air flows in baffle type pre-separators exhibit turbulent flow as the dominant flow regime. As such, the simulation model was developed to include turbulent simulation models with 2-way interaction between the particulates and the air stream. Simulations revealed potential for use of an additional skimmer plate to the baffle-type pre-separator to enhance cleaning separation of the system. The next step is to conduct experimental validation tests, currently designs are being reviewed and plans are underway for construction and fabrication of experimental test units. Planning of the fiber blending process occurred with a university cooperator. Currently, the initial evaluation is scheduled to begin once students return to school in the fall. At present, five biomass materials are being considered for different blending processes: cotton linters, cotton carpel/sticks, wheat straw, industrial bast fibers, and corn stover. Other biomass substrates may be added based on availability. The blending process will evaluate the blends in 25% increments with no more than three biomasses used in any one blend.
Impacts
(N/A)
Publications
- Wang, T., Hardin, R.G., Ward, J.K., Wanjura, J.D., Barnes, E.M. 2021. A smart cotton module tracking and monitoring system for handling logistics and cover damage. Computers and Electronics in Agriculture. 193. https:// doi.org/10.1016/j.compag.2021.106620.
- Wanjura, J.D., Pelletier, M.G., Holt, G.A. 2021. A module feeder inspection system for plastic contamination ⿿ updated system design. Journal of Cotton Science. 25:213⿿221.
- Wanjura, J.D., Pelletier, M.G., Holt, G.A., Barnes, E.M., Wigdahl, J.S., Doron, N. 2021. An integrated plastic contamination monitoring system for cotton module feeders. AgriEngineering. 3(4):907-923.
- Funk, P.A., Thomas, J.W., Yeater, K.M., Armijo, C.B., Whitelock, D.P., Wanjura, J.D., Delhom, C.D. 2022. Saw thickness impact on cotton gin energy consumption. Applied Engineering in Agriculture. 38(1):15-21. https:///doi.org/10.13031/aea.14535.
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Progress 10/01/20 to 09/30/21
Outputs
PROGRESS REPORT Objectives (from AD-416): OBJECTIVE 1: Develop commercially viable methods and technologies for use before ginning that reduce harvest costs, preserve fiber/seed quality, enhance the utilization of production/harvest/gin data, and prevent/ minimize contamination of upland cotton. Subobjective 1A: Assessing the influence of seed cotton storage in round modules on lint and seed quality. Subobjective 1B: Improving the cleanliness and quality of stripper- harvested cotton through improved field cleaning systems. Subobjective 1C: Development of equipment to detect and remove contaminants from cotton during the harvesting process. OBJECTIVE 2: Enable commercially preferred technologies/methods/ strategies for use in ginning upland cotton that improve cleanliness of seed cotton and lint, detect/remove contamination, preserve fiber quality, and reduce financial costs. Subobjective 2A: Development of equipment to detect and remove contaminants from cotton in the harvest and ginning processes. Subobjective 2B: Improving cotton fiber length distribution through novel lint cleaner design. OBJECTIVE 3: Develop commercially viable post-ginning technologies/ techniques that enhance the storage and utilization of upland cotton products/coproducts/byproducts and reduce the environmental footprint of cotton production/processing. Subobjective 3A: Development of a commercially viable mechanical cottonseed delinting system to remove cotton linters and produce planting quality seed, without the use of chemicals. Subobjective 3B: Reducing particulate emissions from cotton ginning through improved pollution abatement device design using computational fluid dynamics (CFD) and laboratory testing. Subobjective 3C: Develop and evaluate the use of cotton plant constituents and other natural fibers in the manufacture of composite materials. Approach (from AD-416): This five-year project plan addresses critical pre-ginning, ginning and post-ginning issues facing cotton producers and processors in the United States. Our plan of work is based on an interactive research approach which is focused on the development of processes and systems for preserving cotton quality during infield storage and ginning, removing foreign material and contaminants from seed cotton during harvesting and ginning, reducing particulate emissions from ag operations, reducing the environmental impact of acid cottonseed delinting, and increasing the value of cotton byproducts though composite materials. The research plan detailed herein addresses the development of new technologies, methods, and strategies for reducing the economic and environmental costs of cotton harvest, ginning, and post-gin processing of upland cotton and cotton by-products. Commercial viability of the research is a key component of any problem solution. Objective 1, Subobjective 1A: A review of the existing literature related to moisture content and foreign matter effects on post-storage cotton fiber and seed quality was conducted. The available literature focused on seed cotton storage in storage houses, ricks, trailers, and rectangular modules. Limited published information is available on seed cotton storage in plastic wrapped cylindrical modules, and that which is available, did not investigate the effects of high initial moisture content on post-storage lint and seed quality. The information obtained from the literature review was used to develop a protocol for evaluating the effects of seed cotton moisture content on the quality of cotton fiber and seed after storage in cylindrical modules. Protocols have been developed to investigate these effects under small-scale laboratory and large-scale commercial conditions. Cooperative research in the United States and Australia has been planned. Subobjective 1B: Testing was conducted to simulate the operation of a new field cleaner design under laboratory conditions using a current production-model field cleaner. The performance observed under laboratory conditions indicated substantial improvements in foreign matter removal efficiency while reducing the amount of seed cotton loss relative to the current production-model machine. The simulation experiments led to the design and construction of several prototype field cleaners that were installed and tested on cotton strippers under field conditions. Experiments were designed and conducted under field conditions to evaluate the performance of the new field cleaner relative to the current production-model machine. The results of the field experiments indicated an improvement of cleaning efficiency of 20% over the current field cleaner design with equal or slightly less seed cotton loss. Subobjective 1C: One of the key impediments in the development of a machine-vision classifier for outdoor use is that natural outdoor lighting is continuously variable and ranges from a color temperature of 3,000 Kelvin (K) to 30,000 K. This lighting variation has a significant detrimental impact on the ability for a classifier to detect objects. Further it is known that the human visual system is much more adept at being able to detect objects of interest against like colored backgrounds. In efforts to develop a lighting independent classifier, a literature review was conducted on machine vision algorithms designed for color agnostic detection of objects using texture metrics. The classifiers under consideration have shown the ability to provide classification based upon use of different characterizations of texture variation. The most promising approaches that were found in the literature are adaptive thresholding, Gabor filter banks, pixel-local entropy (disorder) metrics, and deep-learning convolutional-neural-networks (CNN) models. Experiments were planned and are underway to test various texture-based classifiers for use in detection of plastic contamination against like colored backgrounds as well as when plastic is embedded in cotton, similar to the situations that occur during harvest and ginning. Objective 2, Subobjective 2A: A literature review was conducted on machine-vision classifier algorithms that could be used to detect plastic contamination in cotton. Literature has also been searched for extraction methods that have potential for use in removing embedded plastic from freshly harvested seed-cotton. The most promising of the approaches suggested by the literature are high-speed robotics and pneumatic ejection using blow-off nozzles and air-knives. Based upon the most promising approaches suggested in the literature, experiments have been designed, software was written to test classification algorithms, and laboratory testing has begun to examine performance efficiency for machine-vision algorithms and plastic contamination extraction methods. Subobjective 2B: Lint cleaning using saw-type lint cleaners is an aggressive process that leads to fiber breakage and reduced staple length. The cleaning mechanism used by air-type lint cleaners has been shown to be a much gentler method of removing foreign material from cotton fiber although much less efficient than the mechanism used by saw-type lint cleaners. A multi-stage air type lint cleaner prototype was designed and tested under small scale conditions. Testing results of the prototype machine indicated that combining up to three stages of air lint cleaning removed significantly more foreign material than only one stage alone while having minimal to no effect on fiber length characteristics. Additional development is planned to scale up the prototype for testing under commercial ginning conditions. Objective 3, Subobjective 3A: The mechanical cotton seed delinting system was evaluated, and the results have been presented at stakeholder meetings and conferences. Testing of the prototype system revealed a balance between higher conveyor speeds and seed damage. The higher speeds improved residual lint removal but also resulted in higher visible mechanical damage (VMD) to the cottonseed. Likewise, the addition of ⿿kickers (strips of wire brush inserted between the auger flights of the conveyor) improved lint removal but also increased VMD. It is believed that a balance between VMD and maximum lint removal can be achieved with some additional adjustments of the distance between auger flights and the brushes along the bottom of the conveyor. These and a few other items will be evaluated in future testing as soon as all staff is able to return to the offices/lab. Subobjective 3B: Baffle type pre-separators are used in cotton gin particulate matter abatement systems to balance air flows and reduce the loading rate of large foreign material from multiple cleaning system lines before final control devices (cyclones) are implemented. Reducing the loading rate of large foreign material from pneumatic lines conveying trash from various cleaning processes in the gin reduces wear on more expensive final control devices. A literature review revealed minimal published work on the design and predicted performance of baffle-type pre- separators and no work was found that discussed potential design improvements to enhance collection efficiency for particulate matter. Computational fluid dynamics modeling of a baffle type pre-separator was conducted and indicated that the use of an internal skimmer plate positioned along the back wall of a device may help increase collection efficiency for small diameter particles while maintaining the ability for a pre-separator to remove large foreign material from the air stream. The positioning of this plate is a critical design element and additional modeling and testing is needed to refine and confirm these results. Testing on a prototype baffle-type pre-separator has been planned. Subobjective 3C: Review and evaluation of natural fibers was completed with assistance from a cooperator from Montana State University. The review revealed that the best option is for fibers to be layered onto existing composites if they are being added after the composite has been formed due to the cost associated with modifications needed for insertion of fibers. Ideally, fibers should be incorporated into a composite matrix ahead of time when manufacturing but when adding fibers to improve physio- mechanical properties, overlaying onto the composite is currently the most viable alternative. The next question is which fiber or fiber blend would be the most efficacious to improve the desired physio-mechanical property being sought. Record of Any Impact of Maximized Teleworking Requirement: The maximized telework posture resulted in the delay or cancellation of several research projects. Travel for installation of technology we developed into commercial cotton and cottonseed processing facilities was cancelled due to the maximized telework posture. As a research unit, we have had to select which projects we will not be able to accomplish this year and notify our collaborators and those providing soft funds. Most of our research requires the use of the lab⿿s full-size cotton gin and fabrication shop along with all support staff. The use of the facilities and personnel were unavailable because of maximized telework. ACCOMPLISHMENTS 01 A new field cleaner to enable the next generation of cotton harvesters. Stripper-type cotton harvesters are used to harvest about 7 to 10 million bales, or half of the cotton crop produced in the U.S. annually. Recent design changes to incorporate the capability to form seed cotton modules on the harvester have increased the purchase cost of stripper harvesters from about $250,000 to around $800,000. To allow stripper harvesting to remain as an economically viable option for U.S. cotton growers, increased machine purchase costs must be offset by increased harvest productivity and reduced harvest-time labor and supplemental equipment requirements. In response to the need for greater harvest productivity, ARS engineers in Lubbock, Texas worked with engineers at John Deere under a cooperative research and development agreement (CRADA) to develop and evaluate the performance of a new field cleaner for use on stripper harvesters. The new machine increased material processing capacity by 25% while improving cleaning efficiency by 20%. In addition to meeting new processing capacity goals, the new machine increased the value of cotton harvested by over $5 per bale compared to the current production model machine resulting in an expected $35 to $50 million of additional annual revenue for U.S. cotton growers.
Impacts
(N/A)
Publications
- Van Der Sluijs, M.H., Wanjura, J.D., Boman, R.K., Holt, G.A., Pelletier, M. G. 2021. Assessing the influence of spindle harvester drum arrangement on fiber quality and yield. Journal of Cotton Science. 24:229-237.
- Pelletier, M.G., Holt, G.A., Wanjura, J.D. 2021. Cotton gin stand machine- vision inspection and removal system for plastic contamination: software design. AgriEngineering. 3(3):494-518. https://doi.org/10.3390/ agriengineering3030033.
- Barnes, E.M., Morgan, G., Hake, K., Devine, J., Kurtz, R., Ibendahl, G., Sharda, A., Rains, G., Snider, J., Maja, J., Thomason, A., Lu, Y., Gharakhani, H., Griffin, J., Kimura, E., Hardin, R., Raper, T., Sierra, Y., Fue, K., Pelletier, M.G., Wanjura, J.D., Holt, G.A. 2021. Opportunities for robotic systems and automation in cotton production. AgriEngineering. 3(2):339-362. https://doi.org/10.3390/agriengineering3020023.
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Progress 10/01/19 to 09/30/20
Outputs
Progress Report Objectives (from AD-416): OBJECTIVE 1: Develop commercially viable methods and technologies for use before ginning that reduce harvest costs, preserve fiber/seed quality, enhance the utilization of production/harvest/gin data, and prevent/ minimize contamination of upland cotton. Subobjective 1A: Assessing the influence of seed cotton storage in round modules on lint and seed quality. Subobjective 1B: Improving the cleanliness and quality of stripper- harvested cotton through improved field cleaning systems. Subobjective 1C: Development of equipment to detect and remove contaminants from cotton during the harvesting process. OBJECTIVE 2: Enable commercially preferred technologies/methods/ strategies for use in ginning upland cotton that improve cleanliness of seed cotton and lint, detect/remove contamination, preserve fiber quality, and reduce financial costs. Subobjective 2A: Development of equipment to detect and remove contaminants from cotton in the harvest and ginning processes. Subobjective 2B: Improving cotton fiber length distribution through novel lint cleaner design. OBJECTIVE 3: Develop commercially viable post-ginning technologies/ techniques that enhance the storage and utilization of upland cotton products/coproducts/byproducts and reduce the environmental footprint of cotton production/processing. Subobjective 3A: Development of a commercially viable mechanical cottonseed delinting system to remove cotton linters and produce planting quality seed, without the use of chemicals. Subobjective 3B: Reducing particulate emissions from cotton ginning through improved pollution abatement device design using computational fluid dynamics (CFD) and laboratory testing. Subobjective 3C: Develop and evaluate the use of cotton plant constituents and other natural fibers in the manufacture of composite materials. Approach (from AD-416): This five-year project plan addresses critical pre-ginning, ginning and post-ginning issues facing cotton producers and processors in the United States. Our plan of work is based on an interactive research approach which is focused on the development of processes and systems for preserving cotton quality during infield storage and ginning, removing foreign material and contaminants from seed cotton during harvesting and ginning, reducing particulate emissions from ag operations, reducing the environmental impact of acid cottonseed delinting, and increasing the value of cotton byproducts though composite materials. The research plan detailed herein addresses the development of new technologies, methods, and strategies for reducing the economic and environmental costs of cotton harvest, ginning, and post-gin processing of upland cotton and cotton by-products. Commercial viability of the research is a key component of any problem solution. Objective 1, Subobjective 1A: New chemical free methods of defoliating cotton were investigated under laboratory and field conditions. The most effective non-chemical method for cotton defoliation was the use of directed propane flames to heat the base of cotton plants to the point where the water/nutrient transport process is disrupted. This method provided both defoliation and regrowth control. Findings of this work were documented in a peer-reviewed journal article. Subobjective 1B: Technology for identifying contaminants for use both in the field and in the ginning process was developed. Efforts to integrate this technology to control a system for preventing contaminant entry into row units on cotton harvesters is underway. Subobjective 1C: Field testing to evaluate microwave-based yield monitor errors as a function of crop characteristics was completed. Data analysis is complete. Subobjective 1D: A novel system for measuring the weight of harvested seed cotton in basket type cotton harvesters was developed and tested. Field testing of the system is complete. Additional work using this system was conducted in cooperation with Texas A&M University to integrate the weight measurement system into the first self-calibrating cotton yield monitor. Data from the prototype self-calibrating yield monitor was collected and results were reported to stakeholders. Subobjective 1E: Additional data were collected comparing the cleaning efficiency and seed cotton loss between a production model field cleaner and a prototype field cleaner with improved cleaning and processing capacity. The new data confirm earlier findings that showed substantial improvements in seed cotton cleanliness from the prototype machine compared to the production model field cleaner. The cleaning efficiency improved from 27% with the production model machine to over 48% with the prototype field cleaner. Lint turnout increased from 28.9% to 31.8% for the production model and prototype field cleaners, respectively. Data from the large-scale field trials were summarized and presented to an industry partner. Objective 2, Subobjective 2A: A field feasibility study was conducted to evaluate the potential for utilization of the unit�s previously developed swept-frequency microwave-moisture sensing methodologies. The project was completed with the publication of a peer-reviewed journal article covering the development and results of experimental tests. Subobjective 2B: A prototype delinting system was designed and built for installation and testing in a commercial cottonseed delinting facility but due to COVID-19, installation and testing have been postponed for a year. Subobjective 2C: Testing was performed using cotton cellulosic materials to produce cellulosic nanocrystals (CNC�s). Subobjective 2D: Testing was conducted to document ginning rate, seed residual lint, lint turnout, and fiber quality as a function of powered roll insert size and seed cotton lot size. Data analysis is complete, and the results have been communicated to the industry partner. The design of the ginning system was transferred to a commercial gin machinery manufacturer for production and sale to public and private breeding programs and agronomic service companies. Subobjective 2E: A machine vision system was developed to identify colored plastic contaminants in flowing seed cotton. The system was tested with pink and yellow plastic material which are the most common colors commercially to protect round cotton modules. The system also detects black plastic material commonly used as bed covering material in vegetable production. The finding of this work were reported to industry stakeholders and the technology has been transferred. Subobjective 2F: Experimental tests were conducted on removal of plastic utilizing high-voltage electro-static attraction. Results of these tests provided evidence that the approach wasn�t practical, leading researchers to investigate alternative methods. Subobjective 2G: A system was designed and installed on a cotton stripper harvester that prevents contaminants from entering the harvesting units of the machine. The system was field tested using manual control and results indicate that the system prevented approximately 85% of the plastic contaminants placed in the field from entering the harvester. These findings were summarized in a report to stakeholders and additional work is underway to integrate machine vision techniques into an automated control system. Objective 3: The trash piles from seven Texas cotton gins were sampled to measure the mass of particulate matter (PM) per ton of trash pile material. Each sample was subjected to a sieving analysis to collect the PM less than 106 micrometers. Subsequently, particle size distribution analyses were conducted on the PM less than 106 micrometers with particle analyzer systems. Particle density analysis was also conducted on each sample. The data were used to calculate PM content estimates for the trash piles at each gin location in terms of total PM, PM10 (particulate matter less than 10 micrometers in aerodynamic diameter), and PM2.5 (particulate matter less than 2.5 micrometers in aerodynamic diameter). Trash pile emission factor estimates have been developed and reported to stakeholders.
Impacts
(N/A)
Publications
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