Image-based phenotyping to measure plant diversity and performance

John Doonan, Roger Boyle, Jiwan Han, Kevin Stewart Williams, Andreu Alcalde Barrios, Harry Strange, Fiona Corke, Candida Nibau, Callum Paul Scotson, Anyela Camargo-Rodriguez, Reyer Zwiggelaar, Craig Sturrock, Sacha Mooney

Research output: Contribution to conferenceAbstract


At the NPPC, we use both traditional and novel phenotyping strategies that allow detailed measurement of traits across the entire life cycle of crops and model plants and includes conveyor systems for dynamic imaging of small plants (seedlings) and large plants (up to 2m); instrumented hydroponics to assess root function, laser scanning and other 3-D imaging approaches. Image-based physiological measurements can provide insight into plant responses to environmental stresses. End point phenotyping and quality assessment is particularly important for many of our major crops, motivating us to explore novel high resolution methods (for example, based on X-ray Computed Tomography (CT) scanners) to visualize and measure grain characteristics in situ.
The abundance and diversity of image based data poses a challenge in terms of extracting accurate trait measurements and/or useful proxies, with minimal human intervention. The presentation will describe examples of computer-assisted measurements aimed at automated trait extraction.
Original languageEnglish
Publication statusPublished - 2016
EventPlant and Animal Genome Conference XXIV - San Diego, California, United States of America
Duration: 09 Jan 201613 Jan 2016


ConferencePlant and Animal Genome Conference XXIV
Country/TerritoryUnited States of America
CitySan Diego, California
Period09 Jan 201613 Jan 2016


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