Project Outline:
This project will examine specific image processing techniques that can be used to assessing frost and nutrient damage of broad acre crops using drone and other images.
The project will investigate the issues associated with integrating image processing into nutrient modeling and the influences of crop nutrition on predicting likelihood of susceptibility to leaf and head frost damage.
Desired Skills:
- Skills in Database Programming, and Artificial Intelligent systems and Advanced Computer Programming. (Essential)
- Image processing (Essential)
- R or other languages (Essential)
- Experience in Plant Science, Agriculture/Horticulture an advantage (Desirable)
- Good oral and report writing skills (Essential)
- Able to work in team environment (Essential)
- Good project management skills (Essential)
- Drivers license (desirable)
Project Area: Computing and Agriculture (Digital Agriculture Research Group)
Supervisor(s): Dr Leisa Armstrong, Dr David Cook, Professor Dean Diepeveen
Project level: Honours, Masters, PhD
Funding: Applicant should apply for ECUHDR or RTP Scholarship
Start date: Semester 1 2022
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