Root System Markup Language: Toward a Unified Root Architecture Description Language

Lobet, Guillaume; Pound, Michael P.; Diener, Julien; Pradal, Christophe; Draye, Xavier; Godin, Christophe; Javaux, Mathieu; Leitner, Daniel; Meunier, Félicien; Nacry, Philippe; Pridmore, Tony; Schnepf, Andrea

doi:10.1104/pp.114.253625

Cited by 117 publications

(100 citation statements)

References 45 publications

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“…With these large numbers of imaging and image analysis platforms, the need for sharing and use of data requires establishment of trait ontology across them to allow development of root ideotypes for different environments. Efforts by Lobet et al (2015) to develop a unified root architecture development language are therefore right on time. This, combined with scaling up of the image analysis methods mentioned above, will be able to provide further knowledge required to adapt crops to their highly variable environments.…”

Section: Phenotyping Root System Architecture Traits: Available Technmentioning

confidence: 99%

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

2016

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The challenge to produce more food for a rising global population on diminishing agricultural land is complicated by the effects of climate change on agricultural productivity. Although great progress has been made in crop improvement, so far most efforts have targeted above-ground traits. Roots are essential for plant adaptation and productivity, but are less studied due to the difficulty of observing them during the plant life cycle. Root system architecture (RSA), made up of structural features like root length, spread, number, and length of lateral roots, among others, exhibits great plasticity in response to environmental changes, and could be critical to developing crops with more efficient roots. Much of the research on root traits has thus far focused on the most common cereal crops and model plants. As cereal yields have reached their yield potential in some regions, understanding their root system may help overcome these plateaus. However, root and tuber crops (RTCs) such as potato, sweetpotato, cassava, and yam may hold more potential for providing food security in the future, and knowledge of their root system additionally focuses directly on the edible portion. Root-trait modeling for multiple stress scenarios, together with high-throughput phenotyping and genotyping techniques, robust databases, and data analytical pipelines, may provide a valuable base for a truly inclusive ‘green revolution.’ In the current review, we discuss RSA with special reference to RTCs, and how knowledge on genetics of RSA can be manipulated to improve their tolerance to abiotic stresses.

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Section: Phenotyping Root System Architecture Traits: Available Technmentioning

confidence: 99%

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

2016

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“…This ensures that root tips are labelled at the outer layer of the roots and not within the roots, away from their surface boundary. The result is a nested tree structure expressed in Root System Markup Language (RSML) format [45].…”

Section: Spatial Characteristicsmentioning

confidence: 99%

Visual tracking for the recovery of multiple interacting plant root systems from X-ray $$\upmu $$ μ CT images

Mairhofer

Johnson

Sturrock

et al. 2015

Machine Vision and Applications

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We propose a visual object tracking framework for the extraction of multiple interacting plant root systems from three-dimensional X-ray micro computed tomography images of plants grown in soil. Our method is based on a level set framework guided by a greyscale intensity distribution model to identify object boundaries in image cross-sections. Root objects are followed through the data volume, while updating the tracker's appearance models to adapt to changing intensity values. In the presence of multiple root systems, multiple trackers can be used, but need to distinguish target objects from one another in order to correctly associate roots with their originating plants. Since root objects are expected to exhibit similar greyscale intensity distributions, shape information is used to constrain the evolving level set interfaces in order to lock trackers to their correct targets. The proposed method is tested on root systems of wheat plants grown in soil.

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“…Monitoring this biological process by automated computer vision is one of the most challenging tasks in imaging and image analysis for the plant sciences. The development of various imaging systems to address this challenge with rhizotron in projected 2D or X-ray tomography in 3D has recently triggered many developments in image analysis [8] to extract phenotypic traits of root systems or in informatics to define universal description formats for root systems based on graphs [9]. However, despite these important efforts to promote reproducible science practices, specific issues, brought by the diversity of imaging systems and the richness of fundamental biological questions, continue to pop up and remain to be addressed.…”

Section: Graph-based Denoising Of Skeletonized Root-systemsmentioning

confidence: 99%

On the value of graph-based segmentation for the analysis of structural networks in life sciences

Bujoreanu¹,

Rasti²,

Rousseau³

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-We propose, under the form of a short overview, to stress the interest of graph to encode the "topological" structure of networks hidden in images especially when applied in life sciences. We point toward existing computer science tools to extract such structural graph from images. We then illustrate different applications, such as segmentation, denoising, and simulation on practical examples of various bioimaging domains including vascular networks observed with fluorescent microscopy in 2D imaging, macroscopic root systems observed in 2D optical intensity imaging, and 3D porosity networks of seed observed in absorption X-ray microtomography.

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Root System Markup Language: Toward a Unified Root Architecture Description Language

Cited by 117 publications

References 45 publications

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

Root System Architecture and Abiotic Stress Tolerance: Current Knowledge in Root and Tuber Crops

Visual tracking for the recovery of multiple interacting plant root systems from X-ray $$\upmu $$ μ CT images

On the value of graph-based segmentation for the analysis of structural networks in life sciences

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