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 Cotton Production and Processing Research: Lubbock, TX
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ARS Home Plains Area Lubbock, Texas Cropping Systems Research Laboratory Cotton Production and Processing Research Research





- Wanjura, John
- Holt, Gregory
- Pelletier, Mathew
- 2023
- 2022
- 2021
- 2020
- Publications
- Product Quality and New Uses (306)

Research Project: Enhancing the Profitability and Sustainability of Upland Cotton, Cottonseed, and Agricultural Byproducts through Improvements in Pre-Ginning, Ginning, and Post-Ginning Processes **Location:
                            Cotton Production and Processing Research** 2022 Annual Report **Objectives**
                                

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**
                                

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. **Progress Report**
                                

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. **Accomplishments** **Review 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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