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ARS Home » Southeast Area » Stoneville, Mississippi » Crop Production Systems Research » Research » Publications at this Location » Publication #286998

Title: Development of sensor systems for precision agriculture in cotton

Author
item Sui, Ruixiu
item THOMASSON, J - Texas A&M University
item GE, YUFENG - Texas A&M University

Submitted to: International Journal of Agricultural and Biological Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/29/2012
Publication Date: 12/28/2012
Citation: Sui, R., Thomasson, J.A., Ge, Y. 2012. Development of sensor systems for precision agriculture in cotton. International Journal of Agricultural and Biological Engineering. 5(4):1-14.

Interpretive Summary: Collection of information on crop growth conditions and yield is an essential requirement in precision agriculture practices. Sensing technologies provide powerful tools to collect biotic and abiotic variables for optimizing field managements. In collaboration with researchers at Texas A&M University, a scientist at ARS Crop Production Systems Research Unit at Stoneville, MS developed the sensors and instrument systems for cotton production, including a plant height mapping system, mass-flow sensor, and cotton yield and quality monitoring systems. Those devices were evaluated in lab and field. Results indicated that the plant mapping system performed well in measuring plant heights in real time in situ, and the plant height data were closely related with plant leaf-N content and the yield; the cotton yield monitor with the mass-flow sensor was able to make cotton yield maps showing yield variation of the field; and the fiber quality mapping system was capable of indentifying cotton quality for each individual location within a field. This research has been generated useful information for cotton production and created significant impact on precision agriculture.

Technical Abstract: Precision agriculture (PA) is an information-based technology, using detailed information within an agricultural field to optimize production inputs on a spatially variable basis, maximize farm profit, and minimize environmental impact. Information collection and processing plays a very important role in PA. In recent years PA technologies have been gradually adopted in cotton production. Several sensor systems for PA were developed and field-evaluated in cotton, including a plant height measurement system (PHMS), the Mississippi cotton yield monitor (MCYM), and cotton fiber quality mapping. The PHMS used an ultrasonic sensor to scan the plant canopy and determine plant height in real time in situ. A plant height map was generated with the data collected with the PHMS. Cotton plant height showed a close relationship with yield (R2=0.63) and leaf-nitrogen content (R2=0.48). The MCYM was developed for cotton yield mapping. A patented mass-flow sensor technology was employed in the MCYM. The sensor measured optical reflectance of cotton particles passing through the sensor and used the measured reflectance to determine cotton-mass flow rates. Field tests indicated that the MCYM could measure cotton yield with an average error less than 5%, and it was easy to install and maintain. The cotton fiber-quality mapping research involved a wireless cotton module-tracking system (WCMTS) and a cotton fiber quality mapping system (CFQMS). The WCMTS was based on the concept that a cotton fiber-quality map could be generated with spatial information collected by the system during harvesting coupled with fiber quality information available in cotton classing offices. The WCMTS was constructed and tested, and it operated according to design, with module-level fiber-quality maps easily made from the data collected. The CFQMS was designed and fabricated to perform real-time measurement of cotton fiber quality as the cotton is harvested in field. Test results indicated that the sensor was capable of accurately estimating fiber micronaire in lint cotton (R2=0.99), but estimating fiber quality in seed cotton was more difficult. Cotton fiber quality maps can be used with cotton yield maps for developing field profit maps and optimizing production inputs.