Monga, Aman (2016) Optimizing spot spray nozzles for delivering herbicides on broad acre crops. [USQ Project]
Abstract
Weeds are identified as one of the biggest problems in the agriculture sector of Australia. They increase the capital cost of crops by reducing the annual yield. In addition to that, weed control methods are very expensive. The most commonly used strategy for weed control is blanket spraying of herbicides. This strategy of weed control wastes herbicides by spraying the herbicides on the main crop as well instead of spraying only on the weeds and causes land, soil and water pollution by contamination of herbicides with ground and surface water. Automatic spot spray systems are available in the market. These systems have the capability to detect the weeds and spray only on the detected weeds. 'WEEDSEEKER' and 'WEEDIT' are two examples of automated spot spray technologies available in the market, but they are not efficient enough to spray the whole surface of the weed plant. They can leave a plant half killed, which can contribute to the potential problem of herbicide resistance. This thesis describes the problems associated with the fluid delivery system of the current spot spray systems (specifically WEEDIT and WEEDSEEKER). This thesis evaluates the coverage problem of spraying herbicides on weed plants using the old design and providing an effective solution to the problem by designing and testing a new fluid delivery system. Computer-aided design simulation software AutoCAD 2016 and Autodesk Inventor is used to create and simulate the CAD models of old and new design. The prototype developed uses a different arrangement of spray nozzles than the old design. The results of the simulations conducted by the new design shows a significant increase in spray coverage than the old design.
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Item Type: | USQ Project |
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Item Status: | Live Archive |
Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021) |
Supervisors: | Steven Rees |
Qualification: | Master of Engineering Sciences (Mechanical) |
Date Deposited: | 31 Oct 2024 06:21 |
Last Modified: | 31 Oct 2024 06:21 |
URI: | https://sear.unisq.edu.au/id/eprint/52087 |
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