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9 results on '"Guillaume Cerutti"'

1. A quantitative gibberellin signalling biosensor reveals a role for gibberellins in internode specification at the shoot apical meristem

Author

Bihai Shi, Amelia Felipo-Benavent, Guillaume Cerutti, Carlos Galvan-Ampudia, Lucas Jilli, Geraldine Brunoud, Jérome Mutterer, Elody Vallet, Lali Sakvarelidze-Achard, Jean-Michel Davière, Alejandro Navarro-Galiano, Ankit Walia, Shani Lazary, Jonathan Legrand, Roy Weinstain, Alexander M. Jones, Salomé Prat, Patrick Achard, Teva Vernoux, Reproduction et développement des plantes (RDP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de biologie moléculaire des plantes (IBMP), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Simulation et Analyse de la morphogenèse in siliCo (MOSAIC), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), École normale supérieure - Lyon (ENS Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), and École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
0106 biological sciences, 0303 health sciences, Chemistry, Repressor, food and beverages, Meristem, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, 01 natural sciences, Cell biology, 03 medical and health sciences, Signalling, Shoot, Gibberellin, Primordium, Biosensor, Function (biology), 030304 developmental biology, 010606 plant biology & botany
Abstract

Growth at the shoot apical meristem (SAM) is essential for shoot architecture construction. The phytohormones gibberellins (GA) play a pivotal role in coordinating plant growth, but their role in the SAM remains mostly unknown. Here, we developed a ratiometric GA signalling biosensor by engineering one of the DELLA proteins, to suppress its master regulatory function in GA transcriptional responses while preserving its degradation upon GA sensing. We demonstrate that this novel degradation-based biosensor accurately reports on cellular changes in GA levels and perception during development. We used this biosensor to map GA signalling activity in the SAM. We show that high GA signalling is found primarily in cells located between organ primordia that are the precursors of internodes. By gain- and loss-of-function approaches, we further demonstrate that GAs regulate cell division plane orientation to establish the typical cellular organisation of internodes, thus contributing to internode specification in the SAM.

Published
2021

2. Temporal integration of auxin information for the regulation of patterning

Author

Carlos S. Galvan-Ampudia, Yvon Jaillais, Christian Wenzl, Guillaume Cerutti, Jonathan Legrand, Steven Moussu, Christophe Godin, Vincent Bayle, Raquel Martin-Arevalillo, Romain Azaïs, Géraldine Brunoud, Jan U. Lohmann, Teva Vernoux, Reproduction et développement des plantes (RDP), École normale supérieure - Lyon (ENS Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Simulation et Analyse de la morphogenèse in siliCo (MOSAIC), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Heidelberg University, Centre for Organismal Studies, Universität Heidelberg [Heidelberg], HFSP RPG0054-2013, ANR-12-BSV6-0005,AuxiFlo,Couplage entre le réseau transcriptionnel de l'auxine et l'identité florale(2012), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Universität Heidelberg [Heidelberg] = Heidelberg University

Subjects
0106 biological sciences, 0301 basic medicine, Time Factors, Transcription, Genetic, Arabidopsis, Plant Biology, Biosensing Techniques, 01 natural sciences, Organogenesis, Plant, Plant Growth Regulators, Gene Expression Regulation, Plant, Genes, Reporter, heterocyclic compounds, Auxin, Biology (General), [SDV.BDD]Life Sciences [q-bio]/Development Biology, chemistry.chemical_classification, shoot apical meristem, Microscopy, Confocal, General Neuroscience, food and beverages, General Medicine, Plants, Genetically Modified, Cell biology, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Medicine, Research Article, Quantitative imaging, QH301-705.5, Science, Organogenesis, Biology, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, General Immunology and Microbiology, Indoleacetic Acids, fungi, Meristem, Plant biology, Shoot apex, Multicellular organism, 030104 developmental biology, chemistry, A. thaliana, Developmental biology, 010606 plant biology & botany, Developmental Biology
Abstract

Positional information is essential for coordinating the development of multicellular organisms. In plants, positional information provided by the hormone auxin regulates rhythmic organ production at the shoot apex, but the spatio-temporal dynamics of auxin gradients is unknown. We used quantitative imaging to demonstrate that auxin carries high-definition graded information not only in space but also in time. We show that, during organogenesis, temporal patterns of auxin arise from rhythmic centrifugal waves of high auxin travelling through the tissue faster than growth. We further demonstrate that temporal integration of auxin concentration is required to trigger the auxin-dependent transcription associated with organogenesis. This provides a mechanism to temporally differentiate sites of organ initiation and exemplifies how spatio-temporal positional information can be used to create rhythmicity., eLife digest Plants, like animals and many other multicellular organisms, control their body architecture by creating organized patterns of cells. These patterns are generally defined by signal molecules whose levels differ across the tissue and change over time. This tells the cells where they are located in the tissue and therefore helps them know what tasks to perform. A plant hormone called auxin is one such signal molecule and it controls when and where plants produce new leaves and flowers. Over time, this process gives rise to the dashing arrangements of spiraling organs exhibited by many plant species. The leaves and flowers form from a relatively small group of cells at the tip of a growing stem known as the shoot apical meristem. Auxin accumulates at precise locations within the shoot apical meristem before cells activate the genes required to make a new leaf or flower. However, the precise role of auxin in forming these new organs remained unclear because the tools to observe the process in enough detail were lacking. Galvan-Ampudia, Cerutti et al. have now developed new microscopy and computational approaches to observe auxin in a small plant known as Arabidopsis thaliana. This showed that dozens of shoot apical meristems exhibited very similar patterns of auxin. Images taken over a period of several hours showed that the locations where auxin accumulated were not fixed on a group of cells but instead shifted away from the center of the shoot apical meristems faster than the tissue grew. This suggested the cells experience rapidly changing levels of auxin. Further experiments revealed that the cells needed to be exposed to a high level of auxin over time to activate genes required to form an organ. This mechanism sheds a new light on how auxin regulates when and where plants make new leaves and flowers. The tools developed by Galvan-Ampudia, Cerutti et al. could be used to study the role of auxin in other plant tissues, and to investigate how plants regulate the response to other plant hormones.

Published
2019

3. Treex : a Python package for manipulating rooted trees

Author

Didier Gemmerle, Romain Azaïs, Florian Ingels, Guillaume Cerutti, Reproduction et développement des plantes (RDP), École normale supérieure de Lyon (ENS de Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Simulation et Analyse de la morphogenèse in siliCo (MOSAIC), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut Élie Cartan de Lorraine (IECL), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), The work of Romain Azaïs and Florian Ingles has been partially supported by the European Union’s H2020 project ROMI, and École normale supérieure - Lyon (ENS Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL)

Subjects
0303 health sciences, Source code, Theoretical computer science, Java, computer.internet_protocol, Computer science, media_common.quotation_subject, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], Python (programming language), Data structure, 01 natural sciences, Vertex (geometry), 03 medical and health sciences, 0103 physical sciences, Edit distance, Game tree, 010303 astronomy & astrophysics, computer, XML, 030304 developmental biology, media_common, computer.programming_language
Abstract

International audience; Trees form an expanded family of combinatorial objects that offers a wide range of application fields, from plant modeling to XML files analysis through study of lineage trees. One can also mention classification trees that arise in statistical learning, as well as game trees. In all these examples, the underlying structure is a rooted tree which can be ordered (if the order of siblings is significant) or not. For the sake of modeling, the vertices of a tree might be augmented with labels describing their properties: for example, in a cell lineage tree, each vertex represents a cell and the labels might describe its volume, the tissue type, etc. Despite the diversity of applications, one may want a unique data structure to encode rooted trees and perform operations on them.Treex is a Python package for manipulating rooted trees, ordered or not, with or without labels on their vertices. Basically, Treex allows (i) random generation of trees, (ii) edit operations (e.g., add or remove vertices or labels), (iii) visualization of structures and their properties (in command line or a Matplotlib figure and exportation to TeX), (iv) conversion to different formats, and (v) application of various algorithms. Concerning the latter two, coding processes (Pitman, 2006) have been implemented, as well as DAG compression (Godin & Ferraro, 2010). In addition, comparison between trees can be performed via an edit distance algorithm (Azais, Durand, & Godin, 2019). Self-nested approximations of trees (Godin & Ferraro, 2010, Azais (2017), Azais et al. (2019)) have been implemented through different algorithms. To the best of our knowledge, treex is the only Python library that permits encoding of rooted trees in various formats together with such a diversity of treatments. Let us mention the related Java library TED (Pawlik & Augsten, 2016) for efficient edit distance algorithms. Treex offers converters to the standard encoding of nested brackets (see for instance (Aho, Hopcroft, & Ullman, 1974)) and L-strings as manipulated by L-Py, a simulation framework for modeling plant architectures (Boudon, Pradal, Cokelaer, Prusinkiewicz, & Godin, 2012). Numerical experiments and/or figures of recent publications (Azais, Genadot, & Henry, 2019, Azais (2017), Azais et al. (2019)) have been made using the current or previous versions of treex. Furthermore, ongoing academic projects on the development and implementation of supervised classification methods for tree data, the study of lineage trees, as well as investigations on plant modeling, make intensive use of structures and algorithms implemented in treex. Treex is open source and distributed under the LGPL License. The source code is hosted on GitLab. Releases are automatically built and tested for 64-bit Linux and Mac OS X machines using Jenkins CI, and packaged on Anaconda Cloud (Azais, Cerutti, Gemmerle, & Ingels, 2019a). The documentation of all classes, methods and functions is built upon release and made available online (Azais, Cerutti, Gemmerle, & Ingels, 2019b).

Published
2019

4. Bark and Leaf Fusion Systems to Improve Automatic Tree Species Recognition

Author

Lionel Valet, Didier Coquin, Guillaume Cerutti, Sarah Bertrand, Rihab Ben Ameur, Laure Tougne, Extraction de Caractéristiques et Identification ( imagine ), Laboratoire d'InfoRmatique en Image et Systèmes d'information ( LIRIS ), Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ), Modeling plant morphogenesis at different scales, from genes to phenotype ( VIRTUAL PLANTS ), Inria Sophia Antipolis - Méditerranée ( CRISAM ), Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de la Recherche Agronomique ( INRA ) -Centre de coopération internationale en recherche agronomique pour le développement [CIRAD] : UMR51, ANR-15-CE38-0004,ReVeRIES,Reconnaissance de Végétaux Récréative, Interactive et Educative sur Smartphone, Extraction de Caractéristiques et Identification (imagine), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Simulation et Analyse de la morphogenèse in siliCo (MOSAIC), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Reproduction et développement des plantes (RDP), École normale supérieure - Lyon (ENS Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure de Lyon (ENS de Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), ANR-15-CE38-0004,ReVeRIES,Reconnaissance de Végétaux Récréative, Interactive et Educative sur Smartphone(2015), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut National de la Recherche Agronomique (INRA)-École normale supérieure - Lyon (ENS Lyon)

Subjects
[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR], [ INFO ] Computer Science [cs], Computer science, 02 engineering and technology, 01 natural sciences, Bark, Tree recognition, [ INFO.INFO-TI ] Computer Science [cs]/Image Processing, 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], Fusion, Ecology, Evolution, Behavior and Systematics, Ecology, business.industry, Applied Mathematics, Ecological Modeling, 010401 analytical chemistry, Confusion matrix, Pattern recognition, Distinctive feature, 15. Life on land, 0104 chemical sciences, Computer Science Applications, Tree (data structure), Leaf, Computational Theory and Mathematics, Modeling and Simulation, visual_art, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], Combination, visual_art.visual_art_medium, 020201 artificial intelligence & image processing, Identification (biology), Artificial intelligence, business, Tree species
Abstract

International audience; For everyone, the identification of tree is a difficult task. The main organ of the plant used generally to identify a tree is the leaf. However, due to the large variability of the shapes of leaves, it is difficult to obtain good recognition results. Moreover, sometimes the bark is a very distinctive feature and we think it may be possible to improve the recognition rate by considering it. The main purpose of this article is to investigate how we can combine the features extracted respectively from the leaf and the bark images to recognize the tree the photos come from. An important point is the consideration of the confusion matrix that can be constructed between several species, when the form of a leaf or the shape of a bark is common to a number of tree species. So, we present various strategies of fusion including belief functions and compare them on a public database of 72 species of trees and shrubs, which can be find in metropolitan France.

Published
2018

5. An Image Analysis Pipeline to Quantify Emerging Cracks in Materials or Adhesion Defects in Living Tissues

Author

Stéphane Verger, Guillaume Cerutti, Olivier Hamant, Reproduction et développement des plantes (RDP), École normale supérieure de Lyon (ENS de Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Simulation et Analyse de la morphogenèse in siliCo (MOSAIC), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Recherche Agronomique (INRA)-École normale supérieure - Lyon (ENS Lyon), European Research Council [ERC-2013-CoG-615739], European Project: 615739,EC:FP7:ERC,ERC-2013-CoG,MECHANODEVO(2014), Verger, Stéphane, École normale supérieure - Lyon (ENS Lyon)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), and Cerutti, Guillaume

Subjects
Cracks, 010504 meteorology & atmospheric sciences, Tissue imaging, Strategy and Management, [SDV]Life Sciences [q-bio], 0211 other engineering and technologies, Mechanical properties, 02 engineering and technology, analyse d'image, 01 natural sciences, Industrial and Manufacturing Engineering, Article, Image analysis, Plant science, adhésion cellulaire, MICROCRACK, mental disorders, fissures, ComputingMilieux_MISCELLANEOUS, 021102 mining & metallurgy, 0105 earth and related environmental sciences, Orientation (computer vision), Mechanical Engineering, Metals and Alloys, food and beverages, pipeline, Cell adhesion, Adhesion, Tension, Github, quantification, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Cell structure, fissure, quantization, Biological system
Abstract

Microcracks in materials reflect their mechanical properties. The quantification of the number or orientation of such cracks is thus essential in many fields, including engineering and geology. In biology, cracks in soft tissues can reflect adhesion defects, and the analysis of their pattern can help to deduce the magnitude and orientation of tensions in organs and tissues. Here, we describe a semi-automatic method amenable to analyze cell separations occurring in the epidermis of Arabidopsis thaliana seedlings. Our protocol is applicable to any image exhibiting small cracks, and thus also adapted to the analysis of emerging cracks in animal tissues and materials.

Published
2018

6. Bark Recognition to Improve Leaf-based Classification in Didactic Tree Species Identification

Author

Sarah Bertrand, Guillaume Cerutti, Laure Tougne, Extraction de Caractéristiques et Identification (imagine), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), ANR-15-CE38-0004,ReVeRIES,Reconnaissance de Végétaux Récréative, Interactive et Educative sur Smartphone, Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), ANR-15-CE38-0004,ReVeRIES,Reconnaissance de Végétaux Récréative, Interactive et Educative sur Smartphone(2015), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
0106 biological sciences, Smart phone, Computer science, Feature vector, 02 engineering and technology, 010603 evolutionary biology, 01 natural sciences, Bark, Tree recognition, 0202 electrical engineering, electronic engineering, information engineering, Recognition system, business.industry, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020207 software engineering, Pattern recognition, 15. Life on land, Smart-phone, Leaf, Identification (information), Tree (data structure), [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], visual_art, visual_art.visual_art_medium, Artificial intelligence, business, Tree species
Abstract

International audience; In this paper, we propose a botanical approach for tree species classification through automatic bark analysis. The proposed method is based on specific descriptors inspired by the characterization keys used by botanists, from visual bark texture criteria. The descriptors and the recognition system are developed in order to run on a mobile device, without any network access. Our obtained results show a similar rate when compared to the state of the art in tree species identification from bark images with a small feature vector. Furthermore, we also demonstrate that the consideration of the bark identification significantly improves the performance of tree classification based on leaf only

Published
2017

7. Meshing Meristems - An Iterative Mesh Optimization Method for Modeling Plant Tissue at Cell Resolution

Author

Christophe Godin, Guillaume Cerutti, Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), HFSP, Cerutti, Guillaume, Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
0106 biological sciences, Surface (mathematics), Deformable Models, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Tissue reconstruction, Biology, 01 natural sciences, Image (mathematics), 03 medical and health sciences, Botany, Morphogenesis, Polygon mesh, Representation (mathematics), 030304 developmental biology, Energy functional, ComputingMethodologies_COMPUTERGRAPHICS, 0303 health sciences, Meristem, Visualization, Shoot Apical Meristem, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Cell Reconstruction, Mesh Optimization, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Biological system, 010606 plant biology & botany
Abstract

We address in this paper the problem of reconstructing a mesh representation of plant cells in a complex, multi-layered tissue structure, based on segmented images obtained from confocal microscopy of shoot apical meristem of model plant Arabidopsis thaliana. The construction of such mesh structures for plant tissues is currently a missing step in the existing image analysis pipelines. We propose a method for optimizing the surface triangular meshes representing the tissue simultaneously along several criteria, based on an initial low-quality mesh. The mesh geometry is deformed by iteratively minimizing an energy functional defined over this discrete surface representation. This optimization results in a light discrete representation of the cell surfaces that enables fast visualization, and quantitative analysis, and gives way to in silico physical and mechanical simulations on real-world data. We provide a framework for evaluating the quality of the cell tissue reconstruction, that underlines the ability of our method to fit multiple optimization criteria.

Published
2015

8. The forward ring imaging cherenkov detector of DELPHI

Author

W. Dulinski, K. Pakonski, F. Montano, Andre Augustinus, E. Karvelas, P. Kindblom, N. Dimitriou, A.P. Budziak, B. Lund-Jensen, P. Carecchio, A. Korporaal, E. Zevgolatakos, D. Isenhower, S. Squarcia, Tord Ekelof, Borge Svane Nielsen, T. Henkes, O. Ullaland, Håkan T Johansson, C. Perdikis, E. Saragas, E. Schyns, E. Dahl-Jensen, Mario Sannino, L. O. Eek, G. Lenzen, Wolfgang Adam, Jorge-Armando Benitez Garcia, A. Fontanelle, C. Barnoux, F. Fontanelli, B. Koene, A. Robohm, R. Cereseto, G. Polok, A. Wärm, A. Florek, G. Damgaard, P. Cavalli, Allan Hallgren, A.S. de la Vega, L.-E. Lindqvist, N. de Koning, L. Mattsson, G. E. Theodosiou, J.M. Ostler, E. Albrecht, K. Galuszka, V. Gracco, J. Erikson, L. Ceelie, J. Werner, Marek Stodulski, G. Sajot, J. Thadome, M. Zavrtanik, A. Maltezos, B. Boštjančič, J. Medbo, P. Lorenz, P. Dam, Panos Kostarakis, Demetrios Loukas, Z. Stopa, W. Hao, Luiz Caloba, I. Ambec, L. Traspedini, Guillaume Cerutti, Olga Botner, A. Markou, B. Florek, Jerzy Michalowski, Georgios Stavropoulos, M. Turala, S. Xyroutsikos, Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS), Institut de Recherches Subatomiques (IReS), and Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Cancéropôle du Grand Est-Université Louis Pasteur - Strasbourg I-Centre National de la Recherche Scientifique (CNRS)

Subjects
Physics, Nuclear and High Energy Physics, Photon, Physics::Instrumentation and Detectors, 010308 nuclear & particles physics, business.industry, Cherenkov detector, Detector, Photodetector, 01 natural sciences, Particle detector, Particle identification, Ring-imaging Cherenkov detector, law.invention, Nuclear physics, Optics, law, 0103 physical sciences, High Energy Physics::Experiment, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Detectors and Experimental Techniques, 010306 general physics, business, Instrumentation, Cherenkov radiation
Abstract

The Forward Ring Imaging Cherenkov detector of the DELPHI experiment at LEP provides hadron identification at polar angles15° < θ < 35° and 145° < θ < 165°. Two radiator media, a layer of liquid C6F14 and a volume of gaseous C4F10, in combination provide coverage of momenta up to 40 GeV/c. A single array of photosensitive Time Projection Chambers registers the impact points of ultraviolet photons from both radiators. The design of the detector and of its readout system is described. First results obtained with a partly installed detector are reported.

Published
1994

9. Performance of the forward RICH detector system at DELPHI

Author

T. Henkes, G. Lenzen, P. Cavalli, O. Ullaland, A. Markou, B. Koene, V. Gracco, L. Traspedini, Jorge-Armando Benitez Garcia, E. Schyns, Z. Stopa, J. Erikson, J. Medbo, R. Cereseto, M. Turala, Mario Sannino, A.S. de la Vega, L.-E. Lindqvist, P. Carechio, E. Albrecht, Georgios Stavropoulos, L. O. Eek, Guillaume Cerutti, S. Xyroutsikos, A. Wärm, A.P. Budziak, K. Pakonski, F. Fontanelli, H. Johansson, Jürgen H. Werner, Borge Svane Nielsen, M. Zavrtanik, F. Montano, Z. Thome, P. Lorenz, Tord Ekelof, E. Karvelas, W. Hao, N. Dimitriou, Bengt Lund-Jensen, B. Florek, Jerzy Michalowski, I. Ambec, A. Robohm, Marek Stodulski, G. Sajot, N. de Koning, W. Dulinski, A. Squarcia, O. Botner, A. Maltezos, C. Barnoux, L. Ceelie, Allan Hallgren, J. Thadome, C. Perdikes, Andre Augustinus, A. Korporaal, Demetrios Loukas, B. Boštjančič, Panos Kostarakis, A. Florek, G. Damgaard, E. Dahl-Jensen, K. Galuszka, Piet Van Dam, P. Kindblom, L. Mattsson, A. Fontenille, E. Zevgolatakos, D. Isenhower, Wolfgang Adam, E. Saragas, G. E. Theodosiou, G. Polok, bibliotheque, LPSC, Laboratoire de Physique Subatomique et de Cosmologie (LPSC), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)

Subjects
Nuclear and High Energy Physics, Physics::Instrumentation and Detectors, 01 natural sciences, Particle identification, Particle detector, law.invention, Optics, law, 0103 physical sciences, Electrical and Electronic Engineering, 010306 general physics, Ultraviolet radiation, Cherenkov radiation, computer.programming_language, Physics, 010308 nuclear & particles physics, business.industry, Detector, Particle accelerator, Nuclear Energy and Engineering, Measuring instrument, Optoelectronics, High Energy Physics::Experiment, business, computer, Delphi
Abstract

One quarter of the Forward Ring Imaging Cherenkov (Forward RICH) detector has been installed and operated in the DELPHI experiment. The detector covers the forward-backward regions (15 degrees >

Published
1993

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