Korean Journal of Agricultural Science (농업과학연구)

Institute of Agricultural Science, CNU (충남대학교 농업과학연구소)
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Yield monitoring systems for non-grain crops: A review

  • Md Sazzadul Kabir (Department of Smart Agricultural Systems, Graduate School, Chungnam National University) ;
  • Md Ashrafuzzaman Gulandaz (Department of Smart Agricultural Systems, Graduate School, Chungnam National University) ;
  • Mohammod Ali (Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University) ;
  • Md Nasim Reza (Department of Smart Agricultural Systems, Graduate School, Chungnam National University) ;
  • Md Shaha Nur Kabir (Department of Agricultural and Industrial Engineering, Faculty of Engineering, Hajee Mohammad Danesh Science and Technology University) ;
  • Sun-Ok Chung (Department of Smart Agricultural Systems, Graduate School, Chungnam National University) ;
  • Kwangmin Han (Hyundai Agricultural Machinery)
  • Received : 2023.10.11
  • Accepted : 2023.12.19
  • Published : 2024.03.01
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Abstract

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.

Keywords

Acknowledgement

This research was supported by Cluster Project through the Korea Industrial Complex Corporation (KICOX) grant funded by Ministry of Trade, Industry and Energy (MOTIE) of Korea (No. IRJB2208).

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