If you would like more information or have any questions about this scholarship, please contact the project supervisors.
Dr Anuroop Gaddam
anuroop.gaddam@deakin.edu.au
Sensing and data analytics for quantifying stress and traits in grain crops
Applications will remain open until a candidate has been appointed
Supporting a PhD candidate to conduct technological research on stress responses and traits in grain crops.
Key details
Project supervisor
Deakin school and faculty
Additional supervisors
Location
Melbourne Burwood Campus
Value and duration
This scholarship is available over three years and offers:
- a stipend of $41,650 per annum tax exempt.
Students will complete a six-month industry placement, continuing their thesis research. At least six months will be spent at the Horsham SmartFarm for data collection and fieldwork.
Research aim
This PhD project will leverage the expertise and technology at the Agriculture Victoria Research (AVR) SmartFarm in Horsham, building on ongoing research to improve the detection and quantification of abiotic and biotic stresses and to measure key traits in high-throughput phenotyping of lentils and peas. Depending on your research question and current projects, there may also be opportunities to investigate heat and drought stress. The successful candidate will gain hands-on experience operating ground-based sensors and developing analytical pipelines to test their hypotheses. Additionally, training in flying remotely piloted aerial systems (RPAs) will be provided, enabling data collection across multiple scales, from satellites to RPAs to ground sensors.
Background information
Remote sensing has been used in agriculture since at least the 1970s to map crops and detect and measure stresses for yield forecasting. This technology has advanced from broadband low resolution multispectral to narrow band hyperspectral data and imagery – along with thermal, fluorescence and LiDAR sensing. The ability of modern sensors to detect a range of stresses important to improving crop adaptation to more extreme environments and changing climate has advanced dramatically. In parallel, data analytical techniques such as machine learning and broadly artificial intelligence have increased our ability to detect and quantify stress signals and patterns within increasingly large data sets. These technologies are increasingly being applied to crops to quantify abiotic and biotic stress impacts to improve yield predictions, forecast grain quality and characterise important traits for high throughput crop improvement.
Research conducted on the SmartFarm includes a range of crops grown in the Wimmera, a semi-arid dryland region of south-eastern Australia. The predominant crops include wheat, barley, canola and pulses such as lentil, peas and chickpeas. Research includes studying the impacts of heat, drought, frost and disease to crops, selection of traits for crop improvement and soil and water impacts to crops. Experiments are conducted both on a research farm and in growers’ fields. In addition, AVR has a range of ground and aerial sensing technologies available, including ground-based hyperspectral, thermal and sun-induced fluorescence sensors, RPA multispectral, thermal and LiDAR sensors. These are available for the successful student to conduct their research project.
Am I eligible?
To be eligible you must:
- be a domestic candidate
- meet Deakin's PhD entry requirements
- enrol full time
- hold an honours degree (first class) or an equivalent standard masters degree with a substantial research component
- not be in full-time employment
- meet the requirements for CSIRO Student affiliate onboarding (e.g. satisfy a national police check)
- not be subject to an obligation to a third party to provide that third party with rights to any intellectual property created during their degree.
Please refer to the research degree entry requirements page for further information.
Additional desirable criteria include:
- programming skills in remote sensing and GIS software such as Python, R, ENVI and/or QGIS, and interest in field deployment of sensors
- the ability to integrate hardware and analytical capability with understanding the biology of crop growth and development within the disciplines of precision agriculture and crop breeding.
Ready to apply?
Please email your CV and cover letter to Dr Anuroop Gaddam. Your CV should highlight your skills, education, publications and relevant work experience. If you are successful, you will then be invited to submit a formal application.
Research degree entry requirements
Set yourself up for success. Each type of Deakin research degree has specific entry requirements designed to ensure that graduate researchers are well prepared for the challenges of advanced study.
