29 April, 2021
This project builds on recent SRA-funded research which has introduced a drone-based high-throughput phenotyping platform for SRA. The current project aims to further optimise this technology and provide an indirect trait-based optimal selection index for repeatable assessment of sugarcane clonal performance in early-stage selections. Improved efficiency in early-stage selections will help contribute towards the goal of achieving the 2% annual genetic gain set in the SRA Strategic Plan.
Chief Investigator, Sijesh Natarajan from SRA, provided an update on the progress towards using cutting-edge drones, plant-imaging sensors, and machine learning algorithms for improving variety selections in the SRA plant breeding program.