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RootNav: navigating images of complex root architectures

Pound, Michael P.; French, Andrew P.; Atkinson, Jonathan A.; Wells, Darren M.; Bennett, Malcolm J.; Pridmore, Tony


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Professor of Computer Science

Principal Research Fellow

Professor of Computer Science


We present a novel image analysis tool that allows the semiautomated quantification of complex root system architectures in a range of plant species grown and imaged in a variety of ways. The automatic component of RootNav takes a top-down approach, utilizing the powerful expectation maximization classification algorithm to examine regions of the input image, calculating the likelihood that given pixels correspond to roots. This information is used as the basis for an optimization approach to root detection and quantification, which effectively fits a root model to the image data. The resulting user experience is akin to defining routes on a motorist’s satellite navigation system: RootNav makes an initial optimized estimate of paths from the seed point to root apices, and the user is able to easily and intuitively refine the results using a visual approach. The proposed method is evaluated on winter wheat (Triticum aestivum) images (and demonstrated on Arabidopsis [Arabidopsis thaliana], Brassica napus, and rice [Oryza sativa]), and results are compared with manual analysis. Four exemplar traits are calculated and show clear illustrative differences between some of the wheat accessions. RootNav, however, provides the structural information needed to support extraction of a wider variety of biologically relevant measures. A separate viewer tool is provided to recover a rich set of architectural traits from RootNav’s core representation.


Pound, M. P., French, A. P., Atkinson, J. A., Wells, D. M., Bennett, M. J., & Pridmore, T. (2013). RootNav: navigating images of complex root architectures. Plant Physiology, 162(4), 1802-1814.

Journal Article Type Article
Acceptance Date Jun 2, 2013
Online Publication Date Jun 13, 2013
Publication Date Jul 31, 2013
Deposit Date Nov 6, 2018
Journal Plant Physiology
Print ISSN 0032-0889
Electronic ISSN 1532-2548
Publisher American Society of Plant Biologists
Peer Reviewed Peer Reviewed
Volume 162
Issue 4
Pages 1802-1814
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