title: Novel imaging-based phenotyping strategies for dissecting crosstalk in plant development.
abstract: In an era of genomics, proteomics, and metabolomics a large number of mutants are available. The discovery of their phenotypes is fast becoming the bottleneck of molecular plant physiology. This crisis can be overcome by imaging-based phenotyping, an emerging, rapidly developing and innovative approach integrating plant and computer science. A tremendous amount of digital image data are automatically analysed using techniques of 'machine vision'. This minireview will shed light on the available imaging strategies and discuss standard methods for the automated analysis of images to give the non-bioinformatic reader an idea how the new technology works. A number of successful platforms will be described and the prospects that image-based phenomics may offer for elucidating hormonal cross-talk and molecular growth physiology will be discussed.
authors.affiliation: Biozentrum Hamburg der Universität, Physiology, Ohnhorststr. 18, D-22609 Hamburg, Germany.
authors.forename: Simon
authors.initials: S
authors.lastname: Fraas
authors.affiliation: Biozentrum Hamburg der Universität, Physiology, Ohnhorststr. 18, D-22609 Hamburg, Germany h.luthen@botanik.uni-hamburg.de.
authors.forename: Hartwig
authors.initials: H
authors.lastname: Lüthen
mesh_terms: D017360:Arabidopsis / Q000254:growth & development / Q000502:physiology; D001901:Botany / Q000379:methods*; D019295:Computational Biology; D063245:Plant Development; D010937:Plant Growth Regulators / Q000378:metabolism*; D015398:Signal Transduction
chemical_list: D010937:Plant Growth Regulators
keywords: Image analysis; imaging; machine vision; phenomics; phenotyping; plant hormone physiology; signal transduction networks.