Literature DB >> 26041318

Novel imaging-based phenotyping strategies for dissecting crosstalk in plant development.

Simon Fraas1, Hartwig Lüthen2.   

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.
© The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Keywords:  Image analysis; imaging; machine vision; phenomics; phenotyping; plant hormone physiology; signal transduction networks.

Mesh:

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Year:  2015        PMID: 26041318     DOI: 10.1093/jxb/erv265

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


  2 in total

1.  Hormone crosstalk in plants.

Authors:  Angus Murphy
Journal:  J Exp Bot       Date:  2015-08       Impact factor: 6.992

2.  Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

Authors:  Avi C Knecht; Malachy T Campbell; Adam Caprez; David R Swanson; Harkamal Walia
Journal:  J Exp Bot       Date:  2016-05-03       Impact factor: 6.992

  2 in total

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