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

被引:10
作者
Fraas, Simon [1 ]
Luethan, Hartwig [1 ]
机构
[1] Biozentrum Hamburg Univ, Physiol, D-22609 Hamburg, Germany
关键词
Image analysis; imaging; machine vision; phenomics; phenotyping; plant hormone physiology; signal transduction networks; ROOT-SYSTEM ARCHITECTURE; AUXIN-INDUCED GROWTH; ARABIDOPSIS-THALIANA; ANALYSIS PLATFORM; SELECTION METHOD; RESOLUTION; RESPONSES; SOFTWARE; CELL; QUANTIFICATION;
D O I
10.1093/jxb/erv265
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
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 imagingbased 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.
引用
收藏
页码:4947 / 4955
页数:9
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