Korean Journal of Agricultural Science (Korean J. Agric. Sci.; KJOAS)
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Kabir MS, Gulandaz MA, Ali M, Reza MN, Kabir MSN, Chung SO, Han K. 2024. Yield monitoring systems for non-grain crops: A review. Korean Journal of Agricultural Science 51:63-77.
Korean Journal of Agricultural Science (Korean J. Agric. Sci.) 2024 March, Volume 51, Issue 1, pages 63-77. https://doi.org/10.7744/kjoas.510106
Received on 11 October 2023, Revised on 30 November 2023, Accepted on 19 December 2023, Published on 1 March 2024.
Md Sazzadul Kabir1, Md Ashrafuzzaman Gulandaz1, Mohammod Ali2, Md Nasim Reza1,2, Md Shaha Nur Kabir3, Sun-Ok Chung1,2, Kwangmin Han4,*
1Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Korea
2Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Korea
3Department of Agricultural and Industrial Engineering, Faculty of Engineering, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh
4Hyundai Agricultural Machinery, Iksan 54584, Korea
*Corresponding author: ghkfkdals@gmail.com
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.
mass-based yield monitoring, precision agriculture, volume-based yield monitoring, yield monitoring system
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Md Sazzadul Kabir, https://orcid.org/0000-0002-0160-1305
Md Ashrafuzzaman Gulandaz, https://orcid.org/0000-0002-6391-1165
Mohammod Ali, https://orcid.org/0000-0002-1822-3005
Md Nasim Reza, https://orcid.org/0000-0002-7793-400X
Md Shaha Nur Kabir, https://orcid.org/0000-0003-1685-5292
Sun-Ok Chung, https://orcid.org/0000-0001-7629-7224
Kwangmin Han, https://orcid.org/0000-0002-5083-0200
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).
No potential conflict of interest relevant to this article was reported.