W611
Automating Plant Phenotyping for Breeding and Research

Date: Sunday, January 12, 2014
Time: 8:20 AM
Room: Pacific Salon 3
Andreu Alcalde-Barrios , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Roger Boyle , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Anyela Camargo-Rodriguez , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Amanda J. Clare , Computer Science Department, Aberystwyth University, Aberystwyth, United Kingdom
Fiona Corke , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
John Draper , IBERS, Aberystwyth University, United Kingdom
Markku Farrell , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Alan Gay , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Georgios Gkoutos , Computer Science Department, Aberystwyth University, Aberystwyth, United Kingdom
Jiwan Han , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Catherine Howarth , IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Matt Lowe , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Marie Neal , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Andrew J. Rawlins , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
John Doonan , NPPC, IBERS, Aberystwyth University, Aberystwyth, United Kingdom
Breeding depends on the ability to generate a wide range of genetic diversity from which to select desirable phenotypic variants that perform well under given environmental conditions.  Many, if not all, steps in the breeding process are sub-optimal and therefor limit the rate of plant improvement.  The National Plant Phenomics Centre, a BBSRC funded national facility based in IBERS and a member of the EPPN consortium, aims to develop tools and resources to facilitate objective high content phenotyping of high value genetic populations of cereals, grasses and model plants grown under both controlled environments and field conditions.  We are evaluating traditional, remote sensing and emerging computer-vision based approaches to analyzing plant development and performance, and discuss issues associated with data handling, mining, visualization and sharing.