Field ready, optimised precision weed identification sensor system : final report 2015/055
| Author | McCarthy, C |
| Date Accessioned | 2019-11-28 |
| Date Available | 2019-11-28 |
| Issued | 2019 |
| Identifier | https://hdl.handle.net/11079/18032 |
| Abstract | This project aimed to integrate machine vision-based weed discrimination algorithms with commercial spray control systems from a spray equipment manufacturer, to develop a field-ready, optimised, precision weed detection system. The project followed from SRA project NCA011 (2010/011) in which proof-of-concept algorithms for discriminating Guinea Grass from sugarcane were developed. |
| Language | en |
| Publisher | Sugar Research Australia Limited |
| Title | Field ready, optimised precision weed identification sensor system : final report 2015/055 |
| Keywords | precision weed |
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Pest, disease and weed management [181]
Research outcomes: A comprehensive RD&E program that addresses existing and emerging pests, diseases and weeds, allowing sugarcane growers to manage their crops efficiently with minimal environmental impacts. An enhanced industry capacity to deal with incursions of exotic pests, diseases and weeds.