Production Performance of Narrow Row 2D Fruit Orchards

This PhD project will study the impact of planting stone and pome fruit trees in very narrow rows at 2 m apart and training trees to create a thin wall of foliage. The project will utilise a newly established apple, pear, cherry, plum and nectarine narrow row 2D experimental orchard at the Tatura SmartFarm to:

• Measure the combined effects of dwarfing rootstocks and tree height on tree eco-physiology, tree growth, flower initiation, productivity and fruit quality.
• Determine relationships between light regimes and production outcomes under different dwarfing rootstocks and tree heights.
• Develop mobile sensing technologies to measure the distribution of light, flowers and fruit quality within the canopy.

The candidate is expected to be based primarily at Tatura SmartFarm, to join the innovation of smart orchard designs for maximisation of yield, fruit quality, climate resilience and the efficient use of labour and resources for pome and stone fruits.

The successful candidate will be enrolled at UQ (The University of Queensland), and primarily based in the AVR (Agriculture Victoria Research, Department of Energy, Environment and Climate Action) Tatura SmartFarm.

UQ is one of the world's Top 50 universities. AVR Tatura SmartFarm is a globally renowned leader in the innovation of orchard systems and AgTech solutions. The candidate will have access to state-of-the-art resources in both institutions.

She/he will be supported by a cross-disciplinary advisory team from UQ and AVR, and will work closely with a group of research leaders and fellow members including horticulturalists, AgTech specialists and computer scientists.

This project is supported by the Research project scholarship.

Learn more about the Research project scholarship.

You must contact the principal supervisor for this project to discuss your interest. You should only complete the online application after you have reached agreement on supervision.

Always make sure you are approaching your potential supervisor in a professional way. We have provided some guidelines for you on how to contact a supervisor.

Your application will be assessed on a competitive basis.

We take into account your:

• previous academic record
• publication record
• honours and awards
• employment history

A working knowledge of remote and proximal sensing technologies in horticulture (particularly light measurement and LiDAR scanning) would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field/s of agronomy and/or data science and the potential for scholastic success.

A background or knowledge of orchard systems is highly desirable.

To be considered for this scholarship, please email the following documents to Dr Liqi Han (liqi.han@uq.edu.au):

• Cover letter
• CV
• Academic transcript/s
• List of referees
• Evidence for meeting UQ's English language proficiency requirements eg TOEFL, IELTS

Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission. You can familiarise yourself with the documents required for this process on the UQ Study website.