A harvest area measurement system based on ultrasonic sensors and DGPS for yield map correction
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Unknown crop width entering into the header and the delay time caused by the uncertain start and stop of cutting are the two main error sources in a yield map. A harvest area measurement system (HAMS) is presented in this article. The system has ultrasonic sensors mounted on both sides of the harvest header to detect the presence of crop, which was used to start or stop data recording, as well as measure the cutting width. A high-precision Differential Global Positioning System (DGPS) receiver was used to measure the travelled distance. Field tests were conducted to evaluate the performance of the system. Results showed that: Firstly, the developed HAMS can be used to reduce the area error and the data collected by the HAMS can be used to correct the yield data. In a yield map, the area error reached 6.89% relative to the actual area calculated based on the DGPS tracks. The travelled distance error accounted for about 1.08% and the cutting width error accounted for the other 5.81%. However, the error of the area measured by the HAMS decreased to 0.95%. The position offset of yield points could be calculated and the correction coefficient at each sampling point was determined. Secondly, ultrasonic sensors could replace the header position sensors in most yield monitoring systems, as ultrasonic sensors can detect the presence of the crop, which can be used to start or stop data recording. Finally, the HAMS also provides a potential solution to realize online correction of yield data. The time delay estimated by the HAMS between cutting and sensing was 3–6 s at the start of cutting, and was 1–7 s at the end of cutting. An online correction model of yield data was proposed.
KeywordsHarvest area Ultrasonic sensor Cutting width Delay time Yield map
Our project is supported by National Key Technologies R&D Program of China (Project No. 2006BAD11A17), Young Scientists’ Foundation of Beijing Academy of Agriculture and Forestry Sciences (Project No. 2007030312), National Natural Science Foundation of China (Project No. 30600375) and National High-Tech Research and Development Program of China (863 Program) (Project No. 2006AA10A306). Authors would like to thank the anonymous reviewers for their constructive comments. Thanks to Prof. Simon Blackmore whose advice was helpful in improving this manuscript. We would like to thank Mr. Yanping Liu and Mr. Lianhe Jin for help in the field tests conducted in Precision Agriculture Demonstration Station.
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