RFID—What's in it for me?

John Wanjura, USDA-ARS; Jason Ward, North Carolina State University; Wes Porter and Luke Fuhrer, University of Georgia; Bobby Hardin, Texas A&M University; Zafar Iqbal, University of Florida; Ed Barnes, Cotton Incorporated

Summary

• Prior to the current cotton harvester from John Deere, all cotton modules were formed in a module builder on the edge of the field and manually labeled with paper tags to indicate ownership information.  

• The new generation of cotton harvesters create cylindrical (aka “round”) cotton modules as cotton is harvested. When round modules are wrapped in module wrap products approved by the National Cotton Council, they contain at least four Radio Frequency Identification (RFID) tags that uniquely identify each module. Due to limited software support at the farm and gin, the RFID tags have not been widely used.

• If a gin is equipped with RFID readers and the appropriate software, modules can be tracked from field to gin without additional paper tags.

• Tools were created that allow farmers to combine RFID and classing data to create fiber quality maps of their fields (like yield maps, but with lower resolution).

• These data have been used to: map areas of a field that received seed coat fragment calls; visualize within-field variation of micronaire (a measure of fiber fineness and maturity); and develop more accurate profit / loss maps.

• Such quality maps may also help assess the impact of pest damage and other factors affecting fiber quality.

Introduction

Beginning in the 1970s, cotton farmers packed harvested cotton called seed cotton (cotton fibers still attached to the seed) in large rectangular “modules” on the edge of the field. These modules were approximately 8 feet wide, 8 feet tall, and 32 feet long, and held approximately 20,000 pounds of seed cotton. The modules were manually covered with a large tarp to protect them from rain, snow, and wind. In 2009, John Deere released harvesters that roll seed cotton into cylindrical or “round” modules (Figure 2a, c, and d) that are wrapped in plastic to protect the cotton and preserve module shape. The National Cotton Council maintains a list of “approved” wrap products that meet the minimum performance criteria outlined in the American Society of Agricultural and Biological Engineers (ASABE) Module Cover Material Performance Standard (ASABE, 2024). These contain at least four radio frequency identification (RFID) tags per wrap portion according to ASABE’s Seed Cotton Module Identification System (ASABE, 2025). 

The HID Cotton Pro system, now included on new John Deere cotton harvesters, associates module specific information collected on the harvester to a module identifier unique to each module that is programmed into RFID tags embedded in the plastic wrap. This information includes client, farm, field, harvest area, time/date of harvest, GPS position of wrap application, moisture content, diameter, and weight. Once a module has been wrapped and ejected from the harvester, the module-specific data are stored on the machine before it is transmitted wirelessly to John Deere’s Operations Center web interface, where it is available to the owner and those to whom they grant permission. 

The module specific data can be of great value to farmers seeking to improve site-specific production practices for maximizing both quality and yield once lint bales and associated classing data are reassociated to the modules from which they were ginned. Moreover, the new RFID-based system is of potential value to cotton gins through 1) automation of module management/logistics systems that use the ability to remotely identify round modules, and 2) maximizing gin efficiency by processing modules that have been grouped into sets of similar moisture content before ginning.

The new harvesters have been rapidly adopted, and current estimates are that about 80% of U.S. cotton is now stored in round modules. Each year, more farmers and gins are beginning to see the potential value in the new RFID based identification/data collection system, but utilization has been limited because there are no commercially available systems that provide an end-to-end solution for managing modules and harvest data from the field through the gin. While this new system has its advantages for data collection, the use of plastic wrap has a disadvantage, as plastic fragments are inadvertently found in lint bales. Moreover, when plastic makes its way into the ginning process and accumulates inside various cleaning and conveying machinery, it tends to wear off over a long period of time during which small pieces slough off, potentially contaminating many bales – even bales that originated from conventional modules that were not wrapped in plastic.  When plastic contamination is identified in classing samples at USDA AMS classing offices, the loan value of the bale is reduced by almost 80% which is a significant economic concern to farmers. Such plastic contamination could create defects in textile fabrics made from cotton, resulting in large financial losses to the textile manufacturer.

Goals

The goal of this manuscript is to review technologies that have been developed through recent research to help farmers and ginners improve profitability by RFID-based identification and data management systems. The tools discussed herein provide baseline functionality for automating the process of managing cotton modules and harvest data from the field through the ginning process and facilitate the creation of fiber quality and revenue maps for site specific management of cotton in terms of both yield and quality. Also discussed is how the utility of several of these tools has been extended to help mitigate the risk of plastic contamination in lint bales from module wrap.

The Research

The Electronic Module Management (EMM) system (Wanjura et al., 2020; 2023; 2024; 2025) is a set of hardware and software tools developed to read RFID tags each time a module is handled in the process of moving from the field to the gin, compile all module specific data collected during harvest and handling (RFID Gin Data Management, Figure 1), and link data from lint bales back to the modules from which they were ginned to facilitate field mapping of quality and yield. Hardware components to scan RFID tags were sourced from common industry vendors and are widely available (Wanjura et al., 2020; 2023; 2024). All tools included in the EMM system were developed under an open-source licensing structure and are freely available (Wanjura et al., 2025).

The EMM system hardware tools used to scan RFID tags on round cotton modules at various points in the handling process from field to gin are presented in Figure 2.  

The RFID Module Scan system (Figure 2a) is a hand-held system that uses a Bluetooth connected RFID reader and Android device to scan modules (in the field or on the gin yard) and record the GPS location of each module. This tool is used to generate georeferenced module inventory lists that can be used by gins to identify and locate modules from a farmer who is not using the HID Cotton Pro system from John Deere to collect module specific data. RFID Truck Scan (Figure 2b) is a utility installed on conventional chain-bed type module trucks to facilitate scanning and GPS location capture when modules are loaded or unloaded from the truck. The software provides driving directions to module locations based on GPS data originating from RFID Module Scan or from the HID Cotton Pro system. 

EMM Scale Bridge (Figure 2c) is a stationary bridge tool used at cotton gin truck scales to capture module IDs from RFID tags on modules contained within a truck load and associate those module IDs to a load number and information regarding cotton ownership, truck ID, net load weight, and additional load specific information. The EMM Scale Bridge system can function in “unattended” mode in which the system automatically captures the information for each load without the need for immediate operator intervention. This provides flexibility to gin employees, allowing them to confirm or edit load information, if needed, at a more convenient time. 

EMM Loader Scan (Figure 2d) is a tool installed on wheel loaders or telehandlers to capture module ID, weight, seed cotton moisture content, and ownership information when modules are engaged during the loading or unloading process from semi-trucks. EMM Feeder Scan (Figure 2e) is a stationary bridge utility installed at cotton gin module feeders to scan modules and generate a time ordered processing log of round modules as they are placed on the feeder before ginning. The PBI Scanner (Figure 2f) utility functions in a similar fashion to EMM Feeder Scan but at the bale press, to generate a time ordered log of lint bales as they are ejected. The module processing and lint bale creation logs generated by EMM Feeder Scan and PBI Logger, respectively, are used to link lint bales and associated classing data back to the modules from which they were ginned in RFID Gin Data Management (Figure 1).  The data collected by each system in the EMM System are transmitted to RFID Gin Data Management through a Microsoft Azure cloud database where it is compiled for reporting and analysis.

Modules with wrap damaged during in-field staging or in handling between the field and gin have been identified as a major source of plastic contamination risk at the gin. To help identify modules with damaged wrap, cameras were mounted on front-end loaders (Figure 2d) to capture images of each module as they were unloaded from transport vehicles (Wang et al., 2022), and a deep learning model was trained to detect damaged module wrap automatically. 

Plastic contamination risk is also increased when wrap is cut outside of the manufacturer recommended “cut zone” (John Deere, 2013; TAMA, 2025) during wrap removal at the cotton gin module feeder. Work by Wanjura et al. (2024) extended the EMM Loader Scan utility to include an optional feature that uses the RFID tags to automatically rotate modules into proper position so that workers can easily cut the wrap in the recommended “cut zone.” 

A few fiber quality maps were developed for multiple fields. Where variation in fiber quality was found, researchers sought to identify its causes and determine whether management changes could improve quality and increase returns. For example, data on the moisture content of the seed cotton at harvest were related to discounts for color grade and used to show the costs of harvesting cotton above 12% moisture content (Barnes, et al., 2020). Fiber quality data were then combined with yield maps to calculate gross returns for specific zones in the field.

Success in Module Tracking

The EMM software developed by USDA ARS was successfully used at U.S. gins located in: Texas (2019 – 2024), Louisiana (2018 to 2024), Missouri (2021 – 2024), North Carolina (2018-2024), and Georgia (2019 to 2024). The suite of tools installed at each gin location varied from the full suite to a partial subset depending on the needs and interests of the gin. The flexibility to install and use either a full or partial set of hardware and software tools that meet the specific needs of a particular gin was a primary design goal of the EMM system.

Mitigating Plastic Contamination

The machine vision software developed by Wang et al. (2022) detected damaged areas on module wraps with 92% accuracy compared to a manual assessment of the images on a module-by-module basis. During testing, 3,800 round cotton modules were evaluated by the system, and 4% of those modules had damaged wraps. While a small percentage, these damaged module wraps pose a significant risk of plastic contamination in the gin.  Work is now underway to identify how these wraps were damaged and develop handling suggestions to mitigate damage and plastic contamination.

The module rotating work tool developed by Wanjura et al. (2024) was used by a cooperating gin to unload and rotate approximately 12,200 round modules during the 2023/24 ginning season. In the same year, the work tool was also used to unload several large groups of modules that were not rotated during unloading. The effect of rotating modules on the risk of plastic contamination was evaluated by documenting the incidence rate of plastic accumulation on the dispersing cylinders of the module feeder for extended periods when the gin was processing modules that had or had not been rotated. Use of the module rotating work tool to rotate modules into proper position for wrap cutting in the recommended cut zone reduced the risk of plastic contamination by approximately 50%. A manually controlled version of the module rotating work tool is commercially available.

Fiber Quality Mapping

Fiber quality maps were generated for a field in 2020 in Georgia (Figure 3). The module contained extraneous matter calls (code 31 = seed coat fragments, code 71 = plastic as defined by the USDA Agricultural Marketing Service). That year, Georgia had a record number of seed coat calls, where part of the seed coat remained attached to the fiber during the ginning process. Seed coats are difficult for the textile mill to remove, which results in a financial discount for cotton receiving this designation. Comparisons with yield, soil conductivity, and evaluation maps did not fully explain why only parts of this field received seed coat calls. One challenge is that the resolution of the fiber quality map is limited to about 2 acres in fields yielding 1,000 lbs lint/acre so it can be harder to correlate the quality to small spatial features, such as a small sandy area in the field.

In another field, seed cotton yield was overlayed with micronaire fiber quality and loan value for a North Carolina farm (Figure 4).  Micronaire most consistently showed within-field variation that resulted in a change in cotton price. The research demonstrated the linkage between yield data and fiber quality as it is distributed in the field. Thus, helping farmers identify underperforming zones for potential remediation or enhanced management practices to improve cotton growth and development. These maps could also be helpful to evaluate insect pest damage in on-farm research trials.

Next Steps

RFID module tracking open-source software is available (Wanjura et al., 2025), and commercial gin management software is now able to support RFID data. Work to streamline the integration of RFID data from the EMM system with commercial gin software is underway. Efforts are ongoing to automatically associate bale and module IDs without RFID hardware at the module feeder, using timing and throughput data between the feeder and the bale press. This could simplify the hardware and software required for full traceability. Furthermore, a commercial tool from pct called Linked Cotton^TM is now available to help farmers generate fiber quality maps. Work continues to expand RFID adoption among U.S. gins and make fiber quality maps more widely available to farmers, and we hope to gain new insights on factors that impact fiber quality as more fiber quality maps are evaluated.

References

In addition to the references listed below, additional resources to support RFID implementation are available.

ASABE. 2024. S615.3 - Module Cover Material Performance. St. Joseph, MI. American Society of Agricultural and Biological Engineers. Article

ANSI/ASABE. 2025. S647.1 - Seed Cotton Module Identification System. St. Joseph, MI. American Society of Agricultural and Biological Engineers. 

Barnes, E.M., H. Ashley, B. Hardin, D. Findley, and J. Wanjura. 2020. Proper moisture at harvest for cotton stored in round modules. Cotton Incorporated. 2pp. Article

Fuhrer, L.M., W.M. Porter, E.M. Barnes, G.C. Rains, J.L. Snider, S. Virk, and J.K. Ward. 2024. Utilizing John Deere’s Harvest Identification System in cotton fiber quality mapping. Applied Engineering in Agriculture 40(4): 377-384 (doi: 10.13031/aea.15893). Article | Google Scholar

John Deere. 2013. Round cotton module ginning recommendations. John Deere Des Moines.

Works. KK11359. Deere and Company. Moline, IL.

TAMA. 2025. Better Cotton Wrap for Greater American Cotton. Brochure

Wang, T., R.G. Hardin IV, J.K. Ward, J.D. Wanjura, E.M. Barnes. 2022. A smart cotton module tracking and monitoring system for handling logistics and cover damage, Computers and Electronics in Agriculture, Volume 193, 106620, ISSN 0168-1699. Article

Wanjura, J.D., Holt, G.A., Pelletier, M.G., Barnes, E.M. 2020. Advances in Managing Cotton Modules Using RFID Technology – System Development Update. In Proc. 2020 Beltwide Cotton Conf. pp. 588-609. Memphis, TN: National Cotton Council. Article

Wanjura, J.D., Holt, G.A., Pelletier, M.G. 2023. A New Tool for Handling and Rotating Round Modules. In Proc. 2023 Beltwide Cotton Conf. pp. 139-157. Memphis, TN: National Cotton Council.

Wanjura, J.D., Holt, G.A., Pelletier, M.G. 2024. A Loader Attachment for Managing Round Modules. In Proc. 2024 Beltwide Cotton Conf. pp. 367-389. Memphis, TN: National Cotton Council. 

Wanjura, J., Pelletier, M., Holt, G., Bohn, M., Barnes, E. 2025. Electronic Module Management Systems Software. Program Source Code; CERN: Geneve, Switzerland. Article

Acknowledgements

The authors gratefully acknowledge Tanner and Co. Gin in Frogmore, LA for their assistance in testing the tools in the EMM system. Mr. Matt Bohn of Bohn Technology Solutions is gratefully acknowledged for his help in coding the software used in the EMM system. The authors gratefully acknowledge the funding from Cotton Incorporated that supported this work.

Authors

John Wanjura, USDA-ARS; Jason Ward, North Carolina State University; Wes Porter and Luke Fuhrer, University of Georgia; Bobby Hardin, Texas A&M University; Zafar Iqbal, University of Florida; Ed Barnes, Cotton Incorporated

Reviewers

Travis Faske, University of Arkansas; Daren Mueller, Iowa State University; Damon Smith, University of Wisconsin-Madison

How to cite: Wanjura, J., Ward, J., Porter, W., Fuhrer, L., Hardin, B., Iqbal, Z., Barnes, E. 2026. RFID—What's in it for me?. Crop Protection Network. CPN-5020. https://cropprotectionnetwork.org/publications/rfid-whats-in-it-for-me