2022 journal article
Internet of things: Cotton harvesting and processing
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 202.
author keywords: Cotton; Internet of things; Traceability; Harvesting; Ginning; Textiles
UN Sustainable Development Goal Categories
2. Zero Hunger
(Web of Science)
13. Climate Action
(Web of Science)
Source: Web Of Science
Added: September 26, 2022
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.