Supervisors: Dr Grzegorz Cielniak (University of Lincoln); Mr Adam Whitehouse, Dr Helen Cockerton (NIAB EMR)
This student will be registered with the University of Lincoln and mainly based at the university campus. Beginning in October 2021, the successful candidate should have (or expect to have) an Honours Degree (or equivalent) with a minimum of 2.1 in Computer Science/Computer Engineering graduates, and other disciplines with strong mathematical and programming skills. Prior experience in deploying technology in agriculture or horticulture is a plus.
Fruit-picking robots are a promising technological solution to the labour problems faced by the soft fruit industry. The main obstacle for further development of successful robotic picking systems is a lack of general understanding which fruit variety is the most suitable for the task.
Objectives and approaches
This PhD project proposes to develop new automated phenotyping techniques deployed infield on a mobile robot providing high-throughput, high-fidelity indicators of strawberry varieties indicating their suitability for robotic harvest. The study will investigate techniques based on plant/fruit geometry (i.e. 3D) providing traits about the phenology of the variety and external fruit and plant characteristics. The approach will overcome the limitations of the laboratory-based phenotyping systems by exploiting an autonomous mobile robot to enable rapid identification of multiple traits in the field. The fundamental knowledge and practical solutions to robotic phenotyping will benefit the soft fruit industry, robotics companies and academia, driving future berry breeding programs and novel robot designs.
The successful candidate will have access to state-of-the-art research farms equipped with industrial fruit production facilities, as well as agricultural robots with advanced sensors and tools, including the world-leading Thorvald platform.
Contact Dr Grzegorz Cielniak for an informal discussion on research contents.