Use of Electronic Technologies to Manage Seed Cotton Modules

Authors: BARNES, EDWARD - Cotton, Inc; Wanjura, John

Submitted to: World Cotton Research Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 3/31/2016
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Most U.S. farmers and ginners still use paper tags to identify cotton modules along with a large number painted on the side of traditional modules. The gin typically assigns tags for the modules. When the gin gets the module, the paper tag is removed and the information is manually entered into a software program. With RFID technology already used in round modules, every module comes with a unique identifier and all of the data associated with the module can be transmitted or downloaded directly from the picker. Many Australian gins use this technology to manage a majority of their modules. Adoption of this technology in Australia has been facilitated by the large size of their operations with in-house technical and computer support. There is growing interest in the U.S. to examine the benefits of electronic module tracking. This presentation provides early examples of attempts to use RFID technologies to track modules at U.S. gins. One effort that will facilitate electronic module tracking in the U.S. is the American Society of Agricultural and Biological Engineers (ASABE) Cotton Engineering committee’s work to develop a voluntary numbering standard for cotton modules which specifies the associated technology required to support electronic data tracking (project number X647). Thus, when an equipment company, tarp manufacturer, or module tag distributor wants to use something like a bar code, QR code, or RFID tag to store a module number, gins will not need multiple hardware and software systems unique to each manufacturer in order to utilize electronic module identification. The current draft of the standard proposes to use a GS1 product code to provide a globally unique identifier for each module. Similar to the permanent bale identification tag for U.S. cotton bales, the GS1 manufacturer’s code will be analogous to the gin code, and the module serial number analogous to the bale number. It is hoped that the standard will be balloted and approved in the summer of 2016. One of the key drivers for interest in electronic tracking at this time is the fact that John Deere round modules already have RFID tags embedded in the module wrap. Harvest Identification, Cotton is a process in which the RFID tags are automatically documented for use by the grower, gin, or other trusted advisor to aid in agronomic decision support, improve traceability of round modules, and simplify the module booking process while optimizing the delivery process. In addition to the infrastructure supplied by John Deere, new software tools are also needed to facilitate electronic module tracking. For example, a demonstration application, developed by Cotton Incorporated’s Fiber Competition Division, provided a means to read the RFID tags with a hand-held scanner and store the GPS coordinates for the location of that module. The hand held scanner performed well and was able to read modules from about 15-ft away. Another app related to tracking RFID tags is available from eCotton (EWR). The new mobile application can be used to dispatch module truck drivers to the field, and when coupled with a hand-held RFID reader, verify that the correct modules are being loaded. Several U.S. gins have implement the RFID system with different levels of automation. Some gins have been able to implement the Australia model where the RFID tag is the only identifier use throughout the life of the module. One gin has modified its module feeder with load cells so that the weight of individual round modules can be recorded. The gin then uses module averaging for each round module (a four lint bale average) so the fiber quality associated with each round module is known. It is likely that electronic module tracking will be a good option for many U.S. cotton gins. In the not too distant future, the data will be used beyond logistics and ownership information. Attribu