@article{fuhrer_porter_barnes_rains_snider_virk_ward_2024, title={UTILIZING JOHN DEERE ' S HARVEST I DENTIFICATION SYSTEM IN COTTON FIBER QUALITY MAPPING}, volume={40}, ISSN={["1943-7838"]}, DOI={10.13031/aea.15893}, abstractNote={Highlights Cotton fiber can now be tracked from the field through the ginning process. The methodology illustrates how cotton fiber quality can be georeferenced and visualized. Future project works include developing a deeper understanding of fiber quality variation. Abstract. Due to the innovation and adoption of module-building cotton pickers, cotton harvest has experienced improvements in field efficiencies and harvest operations. Yield maps for post-harvest analysis of in-season production decisions on most major crops are becoming common practice. For a crop such as cotton, the quality of the fiber is impactful on the final price received, and growers are currently unable to geographically visualize said quality to make more informed decisions for future seasons. The main objective of this project was to demonstrate and utilize harvest identification (HID) data to create a useful grower tool to aid in the decision-making process for cotton growers through the development of net profit, fiber quality, yield, and other field parameter maps. Through the utilization of a machine-generated harvest path, HID file, and bale report from the gin, the creation of module-resolution georeferenced fiber quality maps makes it possible for growers to visualize cotton fiber quality as another metric for crop performance. Through the development of this methodology, a process for utilizing HID data to pair fiber quality data with the machine travel path has successfully shown that tracking and mapping of fiber quality is possible. Keywords: Cotton, Cotton fiber, Cotton harvest, Fiber quality.}, number={4}, journal={APPLIED ENGINEERING IN AGRICULTURE}, author={Fuhrer, Luke M. and Porter, Wesley M. and Barnes, Edward M. and Rains, Glen C. and Snider, John L. and Virk, Simerjeet and Ward, Jason K.}, year={2024}, pages={377–384} }