Supporting data for "ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture"

Dataset type: Phenotyping, Imaging, Software, Hardware
Data released on July 02, 2021

Gaggion N; Ariel F; Daric V; Lambert E; Legendre S; Roule T; Camoirano A; Milone DH; Crespi M; Blein T; Ferrante E (2021): Supporting data for "ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture" GigaScience Database. http://dx.doi.org/10.5524/100911

DOI10.5524/100911

Deep learning methods have outperformed previous techniques in most computer vision tasks, including image-based plant phenotyping. However, massive data collection of root traits and the development of associated artificial intelligence approaches have been hampered by the inaccessibility of the rhizosphere. Here we present ChronoRoot, a system which combines 3D printed open-hardware with deep segmentation networks for high temporal resolution phenotyping of plant roots in agarized medium. We developed a novel deep learning based root extraction method which leverages the latest advances in convolutional neural networks for image segmentation, and incorporates temporal consistency into the root system architecture reconstruction process. Automatic extraction of phenotypic parameters from sequences of images allowed a comprehensive characterization of the root system growth dynamics. Furthermore, novel time-associated parameters emerged from the analysis of spectral features derived from temporal signals. Altogether, our work shows that the combination of machine intelligence methods and a 3D-printed device expands the possibilities of root high-throughput phenotyping for genetics and natural variation studies as well as the screening of clock-related mutants, revealing novel root traits.





Sample IDTaxonomic IDCommon NameGenbank NameScientific NameSample Attributes
ContLight_rpi14_2020-01-08_1_Plant13702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi14_2020-01-08_1_Plant23702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi14_2020-01-08_1_Plant33702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi14_2020-01-08_2_Plant13702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi14_2020-01-08_2_Plant23702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi14_2020-01-08_3_Plant13702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi14_2020-01-08_3_Plant23702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi14_2020-01-08_3_Plant33702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi14_2020-01-08_4_Plant13702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
ContLight_rpi15_2020-01-08_3_Plant13702mouse-ear cressthale cressArabidopsis thaliana Description:Temporal sequence of images used by Ch...
Collection date:2020-01-08
Tissue:root [PO:0009005]
...
+
Displaying 1-10 of 50 Sample(s).




File NameSample IDData TypeFile FormatSizeRelease Date 
GitHub archivezip3.25 MB2021-06-30
GitHub archivezip913.22 KB2021-06-30
GitHub archivezip6.41 MB2021-06-30
FigurePNG880.77 KB2021-06-30
Tabular DataCSV2.43 MB2021-06-30
FigurePNG1.03 MB2021-06-30
Tabular DataCSV52.66 KB2021-06-30
Tabular DataCSV1.36 KB2021-06-30
Tabular DataCSV131.76 KB2021-06-30
Tabular DataCSV1.13 KB2021-06-30
Displaying 1-10 of 46 File(s).
Funding body Awardee Award ID Comments
Agence Nationale de la Recherche V Daric & T Roule & M Crespi & T Blein ANR-17-EUR-0007 Investments for the Future program
Agence Nationale de la Recherche V Daric & T Roule & M Crespi & T Blein EUR SPS-GSR Investments for the Future program
Centre National de la Recherche Scientifique T Blein MITI Interdisciplinary Program
Agencia Nacional de Promoción Científica y Tecnológica E Ferrante PICT2018-3907
Universidad Nacional del Litoral E Ferrante CAI+D 50220140100084LI
Universidad Nacional del Litoral E Ferrante CAI+D 50620190100145LI
Agencia Nacional de Promoción Científica y Tecnológica F Ariel PICT2019-04137
Agencia Nacional de Promoción Científica y Tecnológica DH Milone PICT 2018-3384
Centre National de la Recherche Scientifique F Ariel Laboratoire International Associé NOCOSYM
Centre National de la Recherche Scientifique M Crespi Laboratoire International Associé NOCOSYM

3D Models:

Date Action
July 2, 2021 Dataset publish
July 12, 2021 Manuscript Link added : 10.1093/gigascience/giab052