Image-based phenotyping to measure plant diversity and performance

Roger Boyle², Jiwan Han², Kevin Willams², Andreu Alcalde², Harry Strange¹, Fiona Corke², Candida Nibau², Callum Scotson², Anyela Camargo² , Reyer Zwigglaar¹, Craig Sturrock³, Sacha Mooney³, John H. Doonan².

¹Dept of Computer Science, ² National Plant Phenomics Centre, IBERS, Aberystwyth University, Aberystwyth, UK; ³School of Biosciences, 
University of Nottingham, Sutton Bonnington,
UK.

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.