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ARS Home » Southeast Area » Stoneville, Mississippi » Cotton Ginning Research » Research » Research Project #428300

Research Project: Cotton Ginning Research to Improve Processing Efficiency and Product Quality in the Saw-Ginning of Picker-Harvested Cotton

Location: Cotton Ginning Research

Project Number: 6066-41440-008-000-D
Project Type: In-House Appropriated

Start Date: Jun 1, 2015
End Date: May 31, 2020

1. Enable, from a technological standpoint, new commercial methods and processes to reduce energy use, labor costs, and environmental impact, while preserving cotton fiber and seed quality, during the saw-ginning of picker-harvested cotton. 1.A. Develop a fan speed control system for conveying fans used at gins to reduce energy inputs. 1.B. Develop improved systems for drying seed cotton to optimum moisture levels with reduced energy inputs. 1.C. Determine effect of higher than recommended processing rates on fiber quality and losses. 1.D. Develop Seed-Cotton Separator for Optimizing Fiber Quality. 1.E. Improve and evaluate air-bar lint cleaner. 2. Enable new commercial methods and machinery to improve product quality in the saw-ginning of picker-harvested cotton. 2.A. Develop machinery and processes to remove plastic contamination at the gin. 2.B. Determine causes of increased bark content of picker-harvested saw- ginned cotton. 2.C. Improve foreign matter removal by seed cotton cleaners, thus reducing the need for lint cleaning and associated fiber damage. 2.D. Apply high-speed roller ginning equipment for use with picked cotton in the humid region of the United States. 2.E. Develop intelligent system to identify and remove plastic particles in cotton fields and in gins. 3. Identify material properties that have a significant impact on fiber and seed quality during saw-ginning, and enable new or improved, commercial methods for measuring product moisture content and process mass flow rates during ginning. 3.A. Develop a mass flow rate sensor for seed cotton. 3.B. Improve seed cotton moisture content measurement during the ginning process. 3.C. Identify cotton properties or measurable process parameters indicative of fiber damage occurring in the gin stand. 3.D. Develop a system to measure the fiber removed by gin cleaning machinery.

A unmanned aerial vehicle (UAV) will be purchased. An imaging system will be coupled with UAV to take aerial images of cotton fields. Methods and algorithms to identify the plastic particles using the aerial images will be developed and evaluated. Development of an intelligent device which consists of UAV, imaging system, robotics will be explored to identify the plastic particles and remove the particle at the same time in situ. Sensor and control systems will be developed to detect and remove plastic objects during the ginning process. Seed-cotton separator will be designed and fabricated to separate the seed-cotton based on cotton quality. Using the seed-cotton separator, seed-cotton will be separated into two portions. One portion is high quality seed-cotton (HQSC) while the other is low quality seed-cotton (LQSC). Samples of HQSC and LQSC will be collected and ginned for analysis of fiber properties, including micronare, fiber length, and short fiber content. Fiber properties of HQSC will be compared to that of LQSC to find the effectiveness of the seed-cotton separator. The density of the HQSC and LQSC will be measured. The “throw-away” distance from a saw wheel in the separator will be measured. The saw wheel performance parameters will be optimized to achieve the desired separation based on cotton quality. More air-bars will be built so that multiple bars are able to be used in one lint cleaner. Improved air-bars will be installed on lint cleaner and tested with different air pressures supplied to the air-bar. Fiber properties of the lint from the air-bar lint cleaner will be compared to that from the traditional lint cleaner. Design of the air-bar lint cleaner for commercial products will be explored. Power measurements of individual gin stand components and fiber properties determined from HVI or AFI will be used to predict short fiber and nep content occurring due to different processing conditions, such as moisture and ginning rate. Samples will be ginned and electricity use will be monitored. Predictive models for fiber quality parameters, particularly short fiber and nep content, will be developed for each genotype based on energy data and moisture content. Measurement of fiber loss during cleaning is an important part of understanding the ginning process and control of that fiber loss may be related to other factors being studied. The proposed measurement system for the quantity of fiber lost from cleaning machinery includes a measurement of the proportion of material with cotton fiber color and a measurement of the total cleaner waste mass flow rate.