Location: Cotton Quality and Innovation Research
2023 Annual Report
Objectives
The U.S. cotton industry has a number of current problems, including plastic contamination of modules, bales and finished products, increasing competition from man-made fibers, and the need to improve the sustainability of the industry. Over the next five years, we will work to develop methods to remove contaminants from fiber, improve industry sustainability through increased efficiency in the movement of bales from field to market, reduce energy consumption during processing, address concerns about micro-fiber generation, and improve the understanding of length and nep content in cotton to better compete with man-made fibers.
Objective 1: Develop on-bale and seed-cotton fiber quality measurements to provide real-time feedback to ginners and warehouses on fiber quality.
Sub-Objective 1A: Develop and implement methods to measure color and leaf grade on cotton bales as they are produced.
Sub-Objective 1B: Develop and implement methods to utilize the fiber maturity of seed cotton to improve the fiber quality of ginned lint.
Objective 2: Develop methods to detect and remove contaminants from ginned cotton fiber during commercial processing.
Sub-Objective 2A: Perform fate analyses on plastic contaminants during textile processing.
Sub-Objective 2B: Implement machine modifications to improve removal of plastic contaminants during processing.
Sub-Objective 2C: Develop a low-cost contamination detection and removal system.
Sub-Objective 2D: Use blending and processing parameter changes to improve the processing of cotton samples that have been contaminated with entomological sugars.
Objective 3: Develop methods to better measure fiber length distributions and nep content.
Sub-Objective 3A: Implement a capacitance measurement for producing a more accurate fibrogram from a cotton beard.
Sub-Objective 3B: Develop techniques to extract nep data from a fiber bundle.
Objective 4: Reduce the energy used in the post-ginning commercial processing of cotton.
Sub-Objective 4A: Study fiber-seed attachment force at a practical scale and identify cultivar-attachment force relationships.
Sub-Objective 4B: Identify fiber quality parameters that affect fiber frictional characteristics.
Objective 5: Identify links between fiber properties, textile construction, and micro-fiber generation during the lifecycle of commercial cotton products.
Sub-Objective 5A: Construct a device to monitor micro-fibers produced during dry abrasion of fabrics.
Sub-Objective 5B: Understand the roles of fiber quality, yarn construction and fabric construction in micro-fiber generation during abrasion.
Approach
The U.S. cotton industry faces several problems, including contamination, competition from man-made fibers, and the need to improve sustainability. These problems will be addressed by developing methods to remove contaminants, improving the movement of bales from field to market, developing a better understanding of cotton fiber length and fiber entanglements (i.e., nep content), reducing processing energy costs, and understanding micro-fiber generation. The first objective will provide bale quality properties to ginners and warehouses by developing a robotic measurement platform to capture digital images as bales are produced. The images will be used to determine some fiber properties, and the data will allow gins to address quality issues in real-time, creating a more uniform and higher quality cotton that can better compete with man-made fibers. The data will enable warehouses to implement new strategies for the movement of bales from field to market, which will reduce the frequency of bale movements and reduce the energy used in staging bales. Contamination, a major issue impacting U.S. cotton, will be addressed by conducting processing trials that will provide information on the disposition of contaminants during textile processing. This data will be used to help design machinery modifications that aid in the removal of contaminants. Additionally, a low-cost system for the detection and removal of contamination as the fiber is cleaned will also be designed and built. Improved competition with man-made fiber will be achieved in the third objective through improved measurements of cotton properties. Improved fiber length measurement and high-speed measurement of neps, will aid mills in utilizing cotton, and the creation of new measurements will allow for the more predictable processing of cotton. Improving the sustainability of cotton is addressed in the fourth and fifth objectives. Reducing the energy used in the commercial processing of cotton can be achieved by developing practical methods for estimating the fiber-seed attachment force and fiber friction, which will be achieved by monitoring the energy used to gin cotton at a laboratory scale. Developing this knowledge will allow for seed attachment force to be considered when breeding improved cotton varieties. The fifth objective will identify links between fiber and textile properties and the amount of micro-fibers generated during the lifecycle of commercial textiles. Micro-fibers will be collected from dry fabric abrasion experiments, and methods will be developed to characterize and quantify the micro-fibers generated.
Progress Report
Progress was made on all objectives of this project under National Program 306, Component 2, Non-Food Product Quality and New Uses. Delays in the work due to the impact of the COVID-19 pandemic and maximized telework, as well as critical vacancies, have impacted the overall progress but there has been substantial progress on all objectives of the research project. Progress in achieving some objectives of the project plan has been made through collaborations with ARS, university, and stakeholder projects to maximize efficiency. ARS researchers at New Orleans, Louisiana, have collaborated to address the measurement of energy during cotton processing and to develop ways to reduce plastic contamination in cotton. Partnering with collaborators allows for an industry-wide approach to solving problems and has led to enhanced collaborations and visibility of the research project.
In support of Objective 1, we have conducted additional field testing of our cotton bale quality measurement system, previously developed in a new commercial gin. We significantly refined and simplified the design to lower cost and increase reliability. The new design collected bale measurements on over 7,000 commercial samples during the trial. We designed and carried out a new approach to the leaf grade algorithm to improve results and analysis time. A redesigned lighting system reduced glare and simplified the construction of the imaging system while increasing consistency between images. The 2022-23 ginning season was the most successful test of the system thus far. This work was supported by reimbursable cooperative agreement number 6054-44000-080-016-R with Cotton Incorporated.
Work on Sub-objective 1B has not progressed as well as desired. The utilization of fiber maturity to improve the quality of ginned lint was hampered by challenges in measuring fiber maturity in seed cotton samples which contain significant non-lint content. However, we are exploring a contingency plan to utilize field production data such as planting date, growing degree days, and canopy temperature history is to provide the required data in an alternate form.
Despite environmental conditioning issues in the textile pilot plant that have reduced the capacity to carry out some processing trials, we were able to conduct collaborative research trials at a research ginning facility on plastic contamination. This allowed the progress on Objective 2 to remain on schedule. We subjected different plastic contaminant sizes, thicknesses, and materials to processing through cylinder and saw-type cleaners. In this work, we identified various physical parameters of the plastic contaminants, such as stiffness, thickness, and cohesion, as influencing the ease of removal from cotton during processing. Stakeholders have encouraged this collaborative work and it is showing the potential to greatly reduce the level of plastic contamination that end up in finished textile products.
Large-scale processing trials for cotton contaminated with excessive entomological sugars, so-called “sticky cotton”, were delayed due to the environmental conditioning issues in the textile pilot plant. We have collected additional samples of suspected sticky cotton and tested these additional materials using both the sticky cotton thermodetector and the mini-card in preparation for the future trials.
The textile industry continues to request improvements to measurement of fiber length distributions and nep (fiber entanglements) content (Objective 3) due to the critical importance of these parameters. We continue to collect a large number of diverse fiber samples and carry out characterization with traditional methods and novel capacitance-based techniques. A new instrument, the OFDA 4000, was added to the testing protocol this year. New capacitance-based measurements are able to measure length distributions with higher resolution than the traditional electro-optical methods but are slower. The OFDA 4000 has reduced sample preparation time than traditional capacitance-based technique and shows promise, with modified software, to be an intermediate option. Achieving the goal of a capacitance-based technique which has the speed of the traditional electro-optical method remains viable. We have tested additional samples with a wide range of length distributions and nep contents using capacitance-based measurements as well as traditional techniques. Additional testing has been carried out through collaborations with researchers at Texas Tech University in Lubbock, Texas as part of Project Number 6054-44000-080-015S. Analysis to compare the results between new methods and the reference electro-optical approach continue and we are working on a digital signal processing (DSP) approach to identify discrete increases in capacitance which may correlate with the presence of neps.
Progress on reducing the energy used during commercial processing of cotton (Objective 4) continues. Much of this work is progressing thanks to informal collaborations with research at the Cotton Ginning Research Unit in Stoneville, Mississippi. The datalogger for measurement of energy consumption which was originally designed within this project has been significantly improved upon by a collaborator at the Cotton Ginning Research Unit. Most significantly, the collaborator has developed an algorithm which automates the extraction of the useful data from processing trials. This system will be incorporated into the textile processing line, both full-scale and miniature, within the textile pilot plant and allow for a large amount of data to be collected as a co-product of all research processing trials. Static friction tests have been conducted on a set of samples representing diversity in cultivar and growing locations which allows for fiber quality parameter differences due to genetics, environment, and the interaction of genetics and environment (G x E) to be considered during the analysis of the relationship between fiber quality parameters and frictional characteristics. It is believed that this will further explain why different samples consume varying amount of energy during processing.
We have developed a microfiber generation and collection system (Objective 5) which will allow the cotton industry to address consumer concerns about microfibers. The appropriate parameters for the abrasion tester have been identified which allow for consistent results during replicated trials. We have developed a sonication process to enhance the efficiency of microfiber measurements through the FQA-360 instrument by using ultrasonic vibrations to ensure well-distributed samples. A fiber collection system utilizing a vacuum pump and water trap has been developed and is providing consistent results during replicated trials and allowing for work to progress on relating the role of fiber quality, yarn, and fabric construction on influencing the propensity for microfibers to be generated during consumer use of textiles.
We have published the National Cotton Variety Test data and Legacy on-farm variety trial (OVT) data on a public-facing dashboard within AgCROS (Agricultural Collaborative Research Outcomes System) as part of the Partnerships for Data Innovation (PDI) effort. Part of this work has led to the beta-testing of a new version of the cotton production management software, Cotman, which is being tested during the 2023 cotton season. The revised Cotman software is compatible with modern web-browsers and allows for storage of crop data within AgCROS. The Cotman program serves a Decision Support Tool (DST) to aid in production decisions. The revised DST is anticipated to provide the field data which will allow maturity of seed cotton to be transmitted to the gin prior to ginning to allow for the gin to maintain fiber quality during ginning (sub-objective 1B).
We continue to establish a program to develop characterization methods for industrial hemp fibers. Hemp fiber samples and industrial hemp stems have been provided through partnerships with ARS researchers in Geneva, New York. This work is intended to provide the largest collection of hemp fiber quality available and currently over 2,000 samples representing over 100 cultivars are in the process of being characterized. This work will provide the basis for the development of a viable domestic industrial hemp industry.
Accomplishments
1. Classification of cotton fiber maturity genotypes with Fourier Transform Infrared (FT-IR) spectroscopy. The development of the secondary cell wall of a cotton fiber through the deposition of cellulose is referred to as maturity. Cotton fiber maturity is an important trait for the textile industry as it impacts fiber strength, entanglements, and dyeing. In general, cotton fiber geneticists have identified a mutation that prevents fibers from maturing. Crossing the immature mutant with standard, wild-type, cottons results in offspring that either have the mutation causing immature fibers or do not. Researchers in New Orleans, Louisiana, developed an innovative data analysis approach for Fourier Transform Infrared (FT-IR) spectroscopic measurements of the fiber samples. With the help of a statistical technique called Soft Independent Modeling of Class Analogy of Principal Component Analysis (SIMCA/PCA) we could determine the difference between fibers from plants with and without the mutation. Conventional fiber measurements were unable to detect differences. The results could provide cotton researchers a sensitive and rapid tool for monitoring subtle differences within the fibers and further for understanding and quickly evaluate the impact of mutations that may affect fiber maturity.
2. Development of cotton leaf grade algorithm for use independent of cotton classification systems. Practically every bale of cotton is classified and graded by the USDA-Agricultural Marketing Service including the assignment of leaf grade, a measure of non-fiber content. Cotton classification takes place after samples are shipped from the gin to a Classing Office and results are delivered seven to ten days later. Leaf grade is determined using a non-public proprietary system. ARS researchers in New Orleans, Louisiana, have developed an independent method that can predict the assigned leaf grade correctly on 87% of the samples, as tested in a commercial gin. Because this method is fast, it will allow for correction of problems during the ginning process quickly. It may also reduce bale handling costs, labor and energy, by providing data for cotton warehouse organization more efficiently than the current delayed process.
Review Publications
Santiago-Cintron, M., Hinchliffe, D.J., Hron, R. 2023. Comparison of focal plane array FTIR pixel binning size for the nondestructive determination of cotton fiber maturity distributions. Fibers and Polymers. 24:1473-1482. https://doi.org/10.1007/s12221-023-00149-0.
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.
Kim, H.J., Delhom, C.D., Jones, D.C., Xu, B. 2023. Comparative analyses of a maturity distributional parameter evaluating immature fibre contents by reference microscopic analysis and conventional fibre measurement methods. Journal of Textile Institute. Article 2204460. https://doi.org/10.1080/00405000.2023.2204460.
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.
Zeng, L., Wu, J., Delhom, C.D. 2022. Genetic improvement of lint yield by selections of within-boll yield components based on commonality analysis. Euphytica. 218. https://doi.org/10.1007/s10681-022-03071-3.
Naoumkina, M.A., Florane, C.B., Kim, H.J., Santiago Cintron, M., Delhom, C.D. 2023. Overexpression of an actin Gh_D04G0865 gene in cotton reduced fineness of fiber. Crop Science. 63:740-749. https://doi.org/10.1002/csc2.20888.
Edwards, J.V., Prevost, N.T., Santiago Cintron, M. 2023. A comparison of hemostatic activities of zeolite-based formulary finishes on cotton dressings. Journal of Functional Biomaterials. 14(5):255. https://doi.org/10.3390/jfb14050255.
Hron, R.J., Hinchliffe, D.J., Thyssen, G.N., Condon, B.D., Zeng, L., Santiago Cintron, M., Jenkins, J.N., Mccarty Jr, J.C., Sui, R. 2023. Interrelationships between cotton fiber quality traits and fluid handling and moisture management properties of nonwoven textiles. Textile Research Journal. https://doi.org/10.1177/00405175221132011.
Kim, H.J., Liu, Y., Thyssen, G.N., Naoumkina, M.A., Frelichowski, J.E. 2023. Phenomics and transcriptomics analyses reveal deposition of suberin and lignin in the short fiber cell walls produced from a wild cotton species and two mutants. PLOS ONE. 18. Article e0282799. https://doi.org/10.1371/journal.pone.0282799.
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.
