Vision based macadamia yield assessment

Billingsley, John and Dunn, Mark and Bell, David (2006) Vision based macadamia yield assessment. Sensor Review, 26 (4). pp. 312-317. ISSN 0260-2288


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.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Depositing User: Bulkimport bulkimport
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Mechanical and Mechatronic Engineering
Date Deposited: 30 Nov 2007 11:47
Last Modified: 03 Jul 2013 00:22
Uncontrolled Keywords: agricultural equipment; image processing; sensors
Fields of Research (FoR): 09 Engineering > 0906 Electrical and Electronic Engineering > 090605 Photodetectors, Optical Sensors and Solar Cells
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective (SEO): E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: doi: 10.1108/02602280610692024

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