A harvest area measurement system based on ultrasonic sensors and DGPS for yield map correction

A harvest area measurement system based on ultrasonic sensors and DGPS for yield map correction 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

A harvest area measurement system based on ultrasonic sensors and DGPS for yield map correction

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Publisher
Springer US
Copyright
Copyright © 2010 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-010-9157-6
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Precision AgricultureSpringer Journals

Published: Jan 28, 2010

References

  • Grain yield mapping: Yield sensing, yield reconstruction, and errors
    Arslan, S; Colvin, TS
  • Comparison of sensors and techniques for crop yield mapping
    Birrel, SJ; Sudduth, KA; Borgelt, SC
  • Remedial correction of yield map data
    Blackmore, BS; Moore, M

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