Internet of things: cotton production and processing

Authors: HARDIN, ROBERT - Texas A&M University; BARNES, EDWARD - Cotton, Inc; Delhom, Christopher; Wanjura, John; WARD, JASON - North Carolina State University

Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/8/2022
Publication Date: 9/5/2022
Citation: 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.
DOI: https://doi.org/10.1016/j.compag.2022.107294

Interpretive Summary: Cotton undergoes multiple processing stages from the time it is planted to the time it becomes a finished textile product. These processing sequences are interconnected and affect the final product quality. However, limited data transfer currently occurs between the segments of the cotton production chain. The internet of things (IoT) offers a novel approach to expand the scope of information gathered on the farm, at the gin, and during processing at the textile mill. In this paper, a framework for interconnecting information flow between industry segments is discussed in efforts to improve the quality and value of finished products and enhance the sustainability of cotton grown in the United States. Limitations to the development of this data system related to rural broadband connectivity, data standardization, and data ownership/security are discussed. The most challenging obstacle to the successful implementation of the interconnected data system lies in the need for scientific advancements. Specifically, a greater understanding of the interaction between factors affecting fiber and yarn quality are needed to better design sensing and control systems.

Technical Abstract: Cotton requires multiple processing steps to convert the raw agricultural products into finished textiles. Genetic and environmental factors, crop management decisions, and processing practices interact to affect optimal end use, product quality, and process efficiency. Currently, only limited data sharing occurs between sectors of the cotton industry, primarily the official USDA classing data used to determine the value of cotton bales. Increasing digitization could improve productivity, sustainability, and competitiveness with synthetic fibers. Current research has focused on utilizing RFID technology incorporated in a recently introduced harvest system for logistics and associating cotton fiber quality with field locations. Gins and textile mills use some connected sensors; however, their use is primarily limited to remote monitoring and diagnostics. In the future cotton industry, a much larger number of connected devices and sensors can provide information on the production and processing history of raw materials. Developments in agricultural robotics will offer a platform for measuring yield and quality on a site-specific basis in the field. Additional networked sensors and devices at gins and textile mills will provide additional information on product quality and process efficiency. Networking these connected devices will allow for the development of advanced analytics for optimizing logistics and processing industry-wide. Several challenges must be addressed to successfully implement IoT devices in the cotton industry. Improved rural broadband access and more suitable wireless networking protocols for field sensors are needed, although recently introduced technology may offer potential solutions. The cotton industry needs to develop appropriate data standards and data sharing policies. Integrating these data sources creates a new management paradigm, but research will be needed to optimally use this data.