Investment

Crop improvement is dependent on accurate measurements of plant traits such as flowering time, leaf and seed number. For canola, a major grain crop in Australia, these traits are currently assessed by human observation, a time-consuming and costly process. This investment will develop tools and methods to automate and scale up the collection of phenotype data with a focus on flowering time and canopy architecture. The project will employ a variety of imaging techniques and data extraction methods based on recent advances in artificial intelligence and machine learning.