Development and evaluation of a prototype precision spot spray system using image analysis to target guinea grass in sugarcane

Rees, S. J. and McCarthy, C. L. and Baillie, C. P. and Burgos-Artizzu, X. P. and Dunn, M. T. (2011) Development and evaluation of a prototype precision spot spray system using image analysis to target guinea grass in sugarcane. Australian Journal of Multi-Disciplinary Engineering, 8 (2). pp. 97-106. ISSN 1448-8388

Abstract

Herbicide usage in weed control represents a significant economic cost and environmental risk in Australian sugarcane production. Weed spot spraying has potential to increase sugarcane production whilst reducing chemical usage and environmentally damaging runoff. However, weed spot spraying is traditionally a laborious manual task. This paper reports on a precision machine vision system that was developed to automatically identify and target the difficult to control weed Panicum spp. (Guinea Grass) in sugarcane crops. The infield machine vision system comprised a camera and artificial illumination to enable day and night trials. Image analysis algorithms were developed to discriminate Guinea Grass and sugarcane based on colour and textural differences between the species. A positive weed identification from the image analysis activated solenoid-controlled spray nozzles. Evaluations of the system in a sugarcane crop established that the image analysis algorithm parameters required frequent recalibration during the day but that the requirement for recalibration was reduced at night with constant artificial illumination. The algorithm was only effective at detecting mature Guinea Grass. The developed technology is considered a viable alternative to manual spot spraying of mature Guinea Grass in sugarcane at night. A cost benefit analysis of the new weed control system indicated potential grower savings of $170/ha by adopting the technology.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to published version due to publisher copyright policy. © The Institution of Engineers Australia, 2011.
Depositing User: Ms Cheryl McCarthy
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Agricultural, Civil and Environmental Engineering
Date Deposited: 27 Mar 2012 00:27
Last Modified: 22 Oct 2013 05:47
Uncontrolled Keywords: precision agriculture; plant identification; precision spraying; technology
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision
09 Engineering > 0913 Mechanical Engineering > 091302 Automation and Control Engineering
07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070308 Crop and Pasture Protection (Pests, Diseases and Weeds)
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences
URI: http://eprints.usq.edu.au/id/eprint/20657

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