Development of sensor systems for precision agriculture in cotton

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 collected data.The CFQMS was designed and fabricated to perform real-time measurement of cotton fiber quality as the cotton is harvested in the 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.

Grain flow rate sensing for a 55 kW full-feed type multi-purpose combine

Real time sensing of crop yield is critical for a successful implementation of precision agriculture.Yield monitoring system is an optional component of a 55 kW multi-purpose combine harvester,developed in Korea,for both domestic and global markets,especially Asian countries where field sizes are relatively small.The aim of the present study was to fabricate and evaluate the performance of a grain flow sensor suitable to the mid-sized full-feed type combine for rice,soybean,and barley.Firstly,commercially available non-contact type sensing modules(optical,ultrasonic,laser,and microwave modules)were chosen for alternative candidates,to be further tested in a laboratory bench.Through the laboratory tests,the ultrasonic module was selected as a potential approach and the performance was improved by increasing the number of modules and their layout.Finally,the improved grain flow sensor was evaluated during field harvesting operation.Field tests with the improved grain flow sensor showed a good potential for rice(R^(2)=0.85,RMSE=126.14 g/s),soybean(R^(2)=0.78,RMSE=43.87 g/s),and barley(R^(2)=0.83,RMSE=37.39 g/s).Further research would be necessary for improvement and commercialization,through various signal processing and field tests under different field and crop conditions.

Proportional distribution method for estimating actual grain flow under combine harvester dynamics

The yield monitors use a constant delay time to match the grain flow with location.Therefore,mixing and smoothing effects on the grain flow are neglected.Although constant time delay compensates for time mismatch,actual grain flow at a combine harvester head is not equal to the grain flow measured by a sensor due to the dynamics effects.In order to eliminate the dynamics effects,a new method for estimating actual grain flow,called proportional distribution(PD),is proposed.This method assumes that actual grain flow is directly proportional to the feedrate.Based on this assumption,the actual grain flow results from redistributing accumulated grain mass over a certain time according to the profile of the feedrate.The PD can avoid the dynamics effects because the feedrate is measured at a combine harvester’s head.Compared with constant time delay,the proposed method can effectively estimate actual grain flow and be applied to improve the accuracy of yield maps.