Novel imaging-based phenotyping strategies for dissecting crosstalk in plant development
Author(s) -
Simon Fraas,
Hartwig Lüthen
Publication year - 2015
Publication title -
journal of experimental botany
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.616
H-Index - 242
eISSN - 1460-2431
pISSN - 0022-0957
DOI - 10.1093/jxb/erv265
Subject(s) - phenomics , bottleneck , computer science , data science , computational biology , crosstalk , metabolomics , genomics , artificial intelligence , biology , bioinformatics , genome , engineering , biochemistry , electronic engineering , gene , embedded system
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.
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