High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings
Background: High-throughput phenotyping is crucial for the genetic and molecular understanding of adaptive root system development. In recent years, imaging automata have been developed to acquire the root system architecture of many genotypes grown in Petri dishes to explore the Genetic x Environment (GxE) interaction. There is now an increasing interest in understanding the dynamics of the adaptive responses, such as the organ apparition or the growth rate. However, due to the increasing complexity of root architectures in development, the accurate description of the topology, geometry, and dynamics of a growing root system remains a challenge. Results: We designed a high-throughput phenotyping method, combining an imaging device and an automatic analysis pipeline based on registration and topological tracking, capable of accurately describing the topology and geometry of observed root systems in 2D + t. The method was tested on a challenging Arabidopsis seedling dataset, including numerous root occlusions and crossovers. Static phenes are estimated with high accuracy (R2=0.996 and 0.923 for primary and second-order roots length, respectively). These performances are similar to state-of-the-art results obtained on root systems of equal or lower complexity. In addition, our pipeline estimates dynamic phenes accurately between two successive observations (R2=0.938 for lateral root growth). Conclusions: We designed a novel method of root tracking that accurately and automatically measures both static and dynamic parameters of the root system architecture from a novel high-throughput root phenotyping platform. It has been used to characterise developing patterns of root systems grown under various environmental conditions. It provides a solid basis to explore the GxE interaction controlling the dynamics of root system architecture adaptive responses. In future work, our approach will be adapted to a wider range of imaging configurations and species.
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Language: | eng |
Subjects: | système racinaire, phénotype, racine, Arabidopsis thaliana, analyse d'image, imagerie, http://aims.fao.org/aos/agrovoc/c_16034, http://aims.fao.org/aos/agrovoc/c_5776, http://aims.fao.org/aos/agrovoc/c_6651, http://aims.fao.org/aos/agrovoc/c_33292, http://aims.fao.org/aos/agrovoc/c_36762, http://aims.fao.org/aos/agrovoc/c_36760, |
Online Access: | http://agritrop.cirad.fr/603069/ http://agritrop.cirad.fr/603069/1/s13007-022-00960-5.pdf |
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dig-cirad-fr-6030692024-01-29T19:01:23Z http://agritrop.cirad.fr/603069/ http://agritrop.cirad.fr/603069/ High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings. Fernandez Romain, Crabos Amandine, Maillard Morgan, Nacry Philippe, Pradal Christophe. 2022. Plant Methods, 18:127, 19 p.https://doi.org/10.1186/s13007-022-00960-5 <https://doi.org/10.1186/s13007-022-00960-5> High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings Fernandez, Romain Crabos, Amandine Maillard, Morgan Nacry, Philippe Pradal, Christophe eng 2022 Plant Methods système racinaire phénotype racine Arabidopsis thaliana analyse d'image imagerie http://aims.fao.org/aos/agrovoc/c_16034 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_6651 http://aims.fao.org/aos/agrovoc/c_33292 http://aims.fao.org/aos/agrovoc/c_36762 http://aims.fao.org/aos/agrovoc/c_36760 Background: High-throughput phenotyping is crucial for the genetic and molecular understanding of adaptive root system development. In recent years, imaging automata have been developed to acquire the root system architecture of many genotypes grown in Petri dishes to explore the Genetic x Environment (GxE) interaction. There is now an increasing interest in understanding the dynamics of the adaptive responses, such as the organ apparition or the growth rate. However, due to the increasing complexity of root architectures in development, the accurate description of the topology, geometry, and dynamics of a growing root system remains a challenge. Results: We designed a high-throughput phenotyping method, combining an imaging device and an automatic analysis pipeline based on registration and topological tracking, capable of accurately describing the topology and geometry of observed root systems in 2D + t. The method was tested on a challenging Arabidopsis seedling dataset, including numerous root occlusions and crossovers. Static phenes are estimated with high accuracy (R2=0.996 and 0.923 for primary and second-order roots length, respectively). These performances are similar to state-of-the-art results obtained on root systems of equal or lower complexity. In addition, our pipeline estimates dynamic phenes accurately between two successive observations (R2=0.938 for lateral root growth). Conclusions: We designed a novel method of root tracking that accurately and automatically measures both static and dynamic parameters of the root system architecture from a novel high-throughput root phenotyping platform. It has been used to characterise developing patterns of root systems grown under various environmental conditions. It provides a solid basis to explore the GxE interaction controlling the dynamics of root system architecture adaptive responses. In future work, our approach will be adapted to a wider range of imaging configurations and species. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/603069/1/s13007-022-00960-5.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1186/s13007-022-00960-5 10.1186/s13007-022-00960-5 info:eu-repo/semantics/altIdentifier/doi/10.1186/s13007-022-00960-5 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1186/s13007-022-00960-5 info:eu-repo/semantics/reference/purl/https://github.com/Rocsg/RootSystemTracker info:eu-repo/semantics/reference/purl/https://imagej.net/plugins/rootsystemtracker info:eu-repo/grantAgreement/EC/H2020/1001-005//(FRA) Rhizopolis a federal project on the root system of plants/RHIZOPOLIS info:eu-repo/grantAgreement/EC/H2020/289300//(EU) Enhancing resource Uptake from Roots under stress in cereal crops/EUROOT info:eu-repo/grantAgreement/EC/H2020/101000747//(EU) Pre-breeding strategies for obtaining new resilient and added value berries/BreedingValue |
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système racinaire phénotype racine Arabidopsis thaliana analyse d'image imagerie http://aims.fao.org/aos/agrovoc/c_16034 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_6651 http://aims.fao.org/aos/agrovoc/c_33292 http://aims.fao.org/aos/agrovoc/c_36762 http://aims.fao.org/aos/agrovoc/c_36760 système racinaire phénotype racine Arabidopsis thaliana analyse d'image imagerie http://aims.fao.org/aos/agrovoc/c_16034 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_6651 http://aims.fao.org/aos/agrovoc/c_33292 http://aims.fao.org/aos/agrovoc/c_36762 http://aims.fao.org/aos/agrovoc/c_36760 |
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système racinaire phénotype racine Arabidopsis thaliana analyse d'image imagerie http://aims.fao.org/aos/agrovoc/c_16034 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_6651 http://aims.fao.org/aos/agrovoc/c_33292 http://aims.fao.org/aos/agrovoc/c_36762 http://aims.fao.org/aos/agrovoc/c_36760 système racinaire phénotype racine Arabidopsis thaliana analyse d'image imagerie http://aims.fao.org/aos/agrovoc/c_16034 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_6651 http://aims.fao.org/aos/agrovoc/c_33292 http://aims.fao.org/aos/agrovoc/c_36762 http://aims.fao.org/aos/agrovoc/c_36760 Fernandez, Romain Crabos, Amandine Maillard, Morgan Nacry, Philippe Pradal, Christophe High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings |
description |
Background: High-throughput phenotyping is crucial for the genetic and molecular understanding of adaptive root system development. In recent years, imaging automata have been developed to acquire the root system architecture of many genotypes grown in Petri dishes to explore the Genetic x Environment (GxE) interaction. There is now an increasing interest in understanding the dynamics of the adaptive responses, such as the organ apparition or the growth rate. However, due to the increasing complexity of root architectures in development, the accurate description of the topology, geometry, and dynamics of a growing root system remains a challenge. Results: We designed a high-throughput phenotyping method, combining an imaging device and an automatic analysis pipeline based on registration and topological tracking, capable of accurately describing the topology and geometry of observed root systems in 2D + t. The method was tested on a challenging Arabidopsis seedling dataset, including numerous root occlusions and crossovers. Static phenes are estimated with high accuracy (R2=0.996 and 0.923 for primary and second-order roots length, respectively). These performances are similar to state-of-the-art results obtained on root systems of equal or lower complexity. In addition, our pipeline estimates dynamic phenes accurately between two successive observations (R2=0.938 for lateral root growth). Conclusions: We designed a novel method of root tracking that accurately and automatically measures both static and dynamic parameters of the root system architecture from a novel high-throughput root phenotyping platform. It has been used to characterise developing patterns of root systems grown under various environmental conditions. It provides a solid basis to explore the GxE interaction controlling the dynamics of root system architecture adaptive responses. In future work, our approach will be adapted to a wider range of imaging configurations and species. |
format |
article |
topic_facet |
système racinaire phénotype racine Arabidopsis thaliana analyse d'image imagerie http://aims.fao.org/aos/agrovoc/c_16034 http://aims.fao.org/aos/agrovoc/c_5776 http://aims.fao.org/aos/agrovoc/c_6651 http://aims.fao.org/aos/agrovoc/c_33292 http://aims.fao.org/aos/agrovoc/c_36762 http://aims.fao.org/aos/agrovoc/c_36760 |
author |
Fernandez, Romain Crabos, Amandine Maillard, Morgan Nacry, Philippe Pradal, Christophe |
author_facet |
Fernandez, Romain Crabos, Amandine Maillard, Morgan Nacry, Philippe Pradal, Christophe |
author_sort |
Fernandez, Romain |
title |
High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings |
title_short |
High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings |
title_full |
High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings |
title_fullStr |
High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings |
title_full_unstemmed |
High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings |
title_sort |
high-throughput and automatic structural and developmental root phenotyping on arabidopsis seedlings |
url |
http://agritrop.cirad.fr/603069/ http://agritrop.cirad.fr/603069/1/s13007-022-00960-5.pdf |
work_keys_str_mv |
AT fernandezromain highthroughputandautomaticstructuralanddevelopmentalrootphenotypingonarabidopsisseedlings AT crabosamandine highthroughputandautomaticstructuralanddevelopmentalrootphenotypingonarabidopsisseedlings AT maillardmorgan highthroughputandautomaticstructuralanddevelopmentalrootphenotypingonarabidopsisseedlings AT nacryphilippe highthroughputandautomaticstructuralanddevelopmentalrootphenotypingonarabidopsisseedlings AT pradalchristophe highthroughputandautomaticstructuralanddevelopmentalrootphenotypingonarabidopsisseedlings |
_version_ |
1792500453056970752 |