Using a structural root system model to evaluate and improve the accuracy of root image analysis pipelines
| العنوان: | Using a structural root system model to evaluate and improve the accuracy of root image analysis pipelines |
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| المؤلفون: | Pierre Tocquin, Guillaume Lobet, Manuel Noll, Claire Périlleux, Iko T. Koevoets, Loïc Pagès, Patrick E. Meyer |
| المساهمون: | Institut für Biound Geowissenschaften: Agrosphäre, InBioS-PhytoSYSTEMS, Université de Liège, Plant Cell Biology, Swammerdam Institute for Life Sciences, University of Amsterdam [Amsterdam] (UvA), Unité de recherche Plantes et Systèmes de Culture Horticoles (PSH), Institut National de la Recherche Agronomique (INRA), Interuniversity Attraction Poles Programme P7/29 F.R.S.-FNRS, 1.B.237.15F, 1.A.320.16F, University of Amsterdam, UCL - SST/ELI/ELIA - Agronomy, University of Liège - InBioS-PhytoSYSTEMS, Forschungszentrum Jülich - Institut für Bio-und Geowissenschaften: Agrosphare |
| المصدر: | Frontiers in Plant Science Frontiers in Plant Science, Frontiers, 2017, 8, ⟨10.3389/fpls.2017.00447⟩ Frontiers in Functional Plant Ecology 8, 447 (2017). doi:10.3389/fpls.2017.00447 Frontiers in Plant Science (8), . (2017) Frontiers in Plant Science, Vol. 8, no.0, p. 447 (2017) |
| بيانات النشر: | Cold Spring Harbor Laboratory, 2016. |
| سنة النشر: | 2016 |
| مصطلحات موضوعية: | analyse d'images, 0106 biological sciences, Root (linguistics), Calibration (statistics), Computer science, Plant Science, Root system, 01 natural sciences, Image (mathematics), 03 medical and health sciences, image analysis, ddc:570, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, benchmarking, Original Research, 030304 developmental biology, structural model, 0303 health sciences, Vegetal Biology, modèle structurel, business.industry, root structural model, pipeline, Pattern recognition, image library, Plant biology, structure racinaire, exploitation d'image, Pipeline transport, machine learning, Artificial intelligence, business, Biologie végétale, 010606 plant biology & botany |
| الوصف: | Root system analysis is a complex task, often performed using fully automated image analysis pipelines. However, these pipelines are usually evaluated with a limited number of ground-truth root images, most likely of limited size and complexity. We have used a root model, ArchiSimple to create a large and diverse library of ground-truth root system images (10.000). This library was used to evaluate the accuracy and usefulness of several image descriptors classicaly used in root image analysis pipelines. Our analysis highlighted that the accuracy of the different metrics is strongly linked to the type of root system analyzed (e.g. dicot or monocot) as well as their size and complexity. Metrics that have been shown to be accurate for small dicot root systems might fail for large dicots root systems or small monocot root systems. Our study also demonstrated that the usefulness of the different metrics when trying to discriminate genotypes or experimental conditions may vary. Overall, our analysis is a call to caution when automatically analyzing root images. If a thorough calibration is not performed on the dataset of interest, unexpected errors might arise, especially for large and complex root images. To facilitate such calibration, both the image library and the different codes used in the study have been made available to the community. |
| وصف الملف: | application/pdf |
| تدمد: | 1664-462X |
| DOI: | 10.1101/074922 |
| DOI: | 10.3389/fpls.2017.00447⟩ |
| DOI: | 10.3389/fpls.2017.00447 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04f2eb3b5a252ffe55ba89bf5d4ca892 https://doi.org/10.1101/074922 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....04f2eb3b5a252ffe55ba89bf5d4ca892 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 1664462X |
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| DOI: | 10.1101/074922 |