Vision based macadamia yield assessment
Article
Article Title | Vision based macadamia yield assessment |
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Article Category | Article |
Authors | Billingsley, John (Author), Dunn, Mark (Author) and Bell, David (Author) |
Journal Title | Sensor Review |
Journal Citation | 26 (4), pp. 312-317 |
Number of Pages | 6 |
Year | 2006 |
Place of Publication | Bingley, United Kingdom |
Digital Object Identifier (DOI) | https://doi.org/10.1108/02602280610692024 |
Web Address (URL) | http://www.emeraldinsight.com/journals.htm?articleid=1575687&show=abstract |
Abstract | Purpose – To describe the prototype macadamia nut yield monitor. Design/methodology/approach – In this paper, the machine vision-based yield monitor for macadamia nut plantations is described. A summary of sensor fusion procedures is presented. Additionally, a summary of current testing progress is provided. Findings – Using vision to count nuts has the potential to revolutionise yield monitoring for the macadamia industry. Additionally, using a vision sensor for in-field location can provide a low cost, highly accurate method of positioning. Tractor (and nut) location can be determined accurate to 12?mm. Practical implications – This project has culminated in the creation of a working prototype harvester. A commercial unit is in the design stage for operation in 2007 harvest season. Originality/value – This paper describes the solution to a particular problem in the macadamia industry, with potential use in wider fields. |
Keywords | agricultural equipment; image processing; sensors |
ANZSRC Field of Research 2020 | 400999. Electronics, sensors and digital hardware not elsewhere classified |
300207. Agricultural systems analysis and modelling | |
460306. Image processing | |
Byline Affiliations | National Centre for Engineering in Agriculture |
Hidden Valley Plantation, Australia | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q0693/vision-based-macadamia-yield-assessment
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