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Sensing Technologies for Grain Crop Yield Monitoring Systems: A Review

  • Chung, Sun-Ok (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Choi, Moon-Chan (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Lee, Kyu-Ho (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Kim, Yong-Joo (Department of Biosystems Machinery Engineering, Chungnam National University) ;
  • Hong, Soon-Jung (Rural Human Development Center, Rural Development Administration) ;
  • Li, Minzan (China Agricultural University)
  • Received : 2016.11.22
  • Accepted : 2016.11.25
  • Published : 2016.12.01

Abstract

Purpose: Yield monitoring systems are an essential component of precision agriculture. They indicate the spatial variability of crop yield in fields, and have become an important factor in modern harvesters. The objective of this paper was to review research trends related to yield monitoring sensors for grain crops. Methods: The literature was reviewed for research on the major sensing components of grain yield monitoring systems. These major components included grain flow sensors, moisture content sensors, and cutting width sensors. Sensors were classified by sensing principle and type, and their performance was also reviewed. Results: The main targeted harvesting grain crops were rice, wheat, corn, barley, and grain sorghum. Grain flow sensors were classified into mass flow and volume flow methods. Mass flow sensors were mounted primarily at the clean grain elevator head or under the grain tank, and volume flow sensors were mounted at the head or in the middle of the elevator. Mass flow methods used weighing, force impact, and radiometric approaches, some of which resulted in measurement error levels lower than 5% ($R^2=0.99$). Volume flow methods included paddle wheel type and optical type, and in the best cases produced error levels lower than 3%. Grain moisture content sensing was in many cases achieved using capacitive modules. In some cases, errors were lower than 1%. Cutting width was measured by ultrasonic distance sensors mounted at both sides of the header dividers, and the errors were in some cases lower than 5%. Conclusions: The design and fabrication of an integrated yield monitoring system for a target crop would be affected by the selection of a sensing approach, as well as the layout and mounting of the sensors. For accurate estimation of yield, signal processing and correction measures should be also implemented.

Keywords

References

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