Smart Decision Tools for Nutrient Management in Swan Coastal Plain

Project Outline:

The aims of this project is to develop Smart Decision Support Tool for Crop Nitrogen Management in Swan Coastal Plain using Artificial Intelligence and other related techniques

The project will carry out data collection and analysis and the development of the prototype Decision Support System (DSS) Tool.

• Data set collection and pre-processing to develop a data repository
• Preliminary data visualisation.
• Assess the best classification techniques to establish the crop x nitrogen yield prediction models and effects under different climate and fertiliser scenarios
• Validation with field data measurements to develop prediction model
• Develop a prototype web application of the DSS tool.

This research is based existing methodologies on determination of nitrogen deficiency in wheat and can have a wide application to a range of crops grown in the Swan Coastal Plain.

This project will also use NDVI to model the relationship between nitrogen fertiliser management and crop growth, These techniques have already been shown to be useful for understanding watershed management (and vegetation degradation.  Other techniques such as data and geospatial visualization will also be explored.

Desired Skills:

1. Skills in Database Programming, and Artificial Intelligent systems and Advanced Computer Programming.  Essential
2. R and other languages Desirable
3. Skills in Computer Hardware and sensors  Desirable
4. Experience in Plant Science, Agriculture/Horticulture an advantage Desirable
5. Good oral and report writing skills (Essential)
6. Able to work in team environment  (Essential)
7. Good project management skills (Essential)

Project Area: Computing and Agriculture (Digital Agriculture Research Group)

Supervisor(s): Dr Leisa Armstrong

Project level: Honours, Masters, PhD

Funding: Applicant should apply for ECUHDR or RTP Scholarship

Start date: Semester 1 2022