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Productions

Retrouvez ici les publications issues des thèses et post-docs financés et cofinancés par #DigitAg depuis le début du projet
  • Théo Martin (2023), Le robot de traite : une machine pour tous… ou presque, Séminaire Nouvelles pratiques agricoles et transformations du travail, RIU Travail INRAE ACT, Mar 2023, Montpellier, France,https://hal.inrae.fr/hal-04123285

 

 

  • Théo Martin (2022), La mise en débat du travail dans les collectifs : Le cas du robot en AOP Reblochon, 5. Rencontres Nationales Travail en Agriculture, RMT Travail en agriculture, Nov 2022, Clermont-Ferrand, France, https://hal.inrae.fr/hal-04123256

 

  • Théo Martin (2022), Robot de traite : continuités et ruptures dans la division du travail, Politiques de la machine agricole - Approches sociologiques et historiques des trajectoires de mécanisation de l'agriculture (1945-2021), Université Paris Dauphine, Jun 2022, Paris, France, https://hal.inrae.fr/hal-04066017

 

  • Elie Najm, Jean-François Baget and Marie-Laure Mugnier (2022), Rule-Based Data Access: A Use Case in Agroecology, RuleML+RR 2022 (6th International Joint Conference on Rules and Reasoning) - 16th International Rule Challenge, https://hal-lirmm.ccsd.cnrs.fr/lirmm-03785968

 

  • Laclef, E., Debus, N., Taillandier, P., Hassoun, P., Parisot, González-García, E., Lurette, A. (2022), Simulation de l’impact de la pratique de l’insémination sans hormones sur les performances et l’alimentation d’un troupeau ovin laitier, 26èmes Rencontres autour des Recherches sur les Ruminants, 7-8 décembre 2022, Paris, France, https://hal.inrae.fr/hal-04033343

  

  • Laclef, E., Debus, N., Taillandier, P., Hassoun, P., Parisot, González-García, E., Lurette, A. (2022), Introducing hormone-free insemination in dairy sheep farms challenges their feeding system design, Presented at the EAAP, 73th Annual Meeting of the European Federation of Animal Science, September 2022, Porto, Portugal, https://hal.inrae.fr/hal-03775185

  

  • Véronique Bellon-Maurel, Ludovic Brossard, Frédérick Garcia, Nathalie Mitton, Alexandre Termier (2022), Agriculture and Digital Technology: Getting the most out of digital technology to contribute to the transition to sustainable agriculture and food systems, https://hal.inrae.fr/hal-03604970

 

  • Elie Najm, Marie-Laure Mugnier, Christian Gary, Jean-François Baget, Raphaël Métral, Léo Garcia (2022), Integrating Data and Knowledge to Support the Selection of Service Plant Species in Agroecology, https://hal.inrae.fr/ABSYS/lirmm-03879910v1

 

  • Rénier L., Cardona A., Goulet F., Ollivier G (2022), La proximité à distance. Comment les agri-youtubeurs communiquent sur leurs pratiques, Reseaux, https://hal.inrae.fr/hal-03582091

  

  • Maxime Metz, Maxime Ryckewaert, Sílvia Mas Garcia, Ryad Bendoula, Pierre Dardenne, Matthieu Lesnoff, Jean Michel Roger (2022), RoBoost-PLS2-R: An extension of RoBoost-PLSR method for multi-response, Chemometrics and Intelligent Laboratory Systems, https://doi.org/10.1016/j.chemolab.2022.104498  

  

 

  • Aldrig Courand, Maxime Metz, Daphné Héran, Carole Feilhes, Fanny Prezman, Eric Serrano, Ryad Bendoula, Maxime Ryckewaert (2022), Evaluation of a robust regression method (RoBoost-PLSR) to predict biochemical variables for agronomic applications: Case study of grape berry maturity monitoring, Chemometrics and Intelligent Laboratory Systems, https://hal.inrae.fr/ITAP/hal-03538442v1 

 

  • Eva Lopez-Fornieles, Guilhem Brunel, Nicolas Devaux, Jean-Michel Roger, Bruno Tisseyre (2022), Is It Possible to Assess Heatwave Impact on Grapevines at the Regional Level with Time Series of Satellite Images?, Agronomy, https://hal.inrae.fr/hal-03645259 

 

 

  • Maxime Ryckewaert, Daphné Héran, Thierry Simonneau, Florent Abdelghafour, Romain Boulord, Nicolas Saurin, Daniel Moura, Sílvia Mas Garcia, Ryad Bendoula (2022), Physiological variable predictions using VIS–NIR spectroscopy for water stress detection on grapevine: Interest in combining climate data using multiblock method, Computers and Electronics in Agriculture, https://doi.org/10.1016/j.compag.2022.106973

 

  • Lopez-Fornieles E, Brunel G, Rancon F, Gaci B, Metz M, Devaux N, Taylor J, Tisseyre B, Roger J-M (2022), Potential of Multiway PLS (N-PLS) Regression Method to Analyse Time-Series of Multispectral Images: A Case Study in Agriculture, Remote Sensing, https://doi.org/10.3390/rs14010216

  

  • Maxime Ryckewaert, Gilles Chaix, Daphné Héran, Abdallah Zgouz, Ryad Bendoula (2022), Evaluation of a combination of NIR micro-spectrometers to predict chemical properties of sugarcane forage using a multi-block approach, Biosystems Engineering, https://doi.org/10.1016/j.biosystemseng.2022.02.019

  

  • Mahmoud, R., Casadebaig, P., Hilgert, N. et al. (2022), Species choice and N fertilization influence yield gains through complementarity and selection effects in cereal-legume intercrops, Agronomy Sustainable Devlopment, https://doi.org/10.1007/s13593-022-00754-y

  

  • Debus, N., Laclef, E., Lurette, A., Alhamada, M., Tesniere, A., González-García, E., Menassol, J.B., Bocquier, F. (2022), High body condition score combined with a reduced lambing to ram introduction interval improves the short-term ovarian response of milking Lacaune ewes to the male effect, Animal, https://hal.inrae.fr/hal-03651997

  

  • Laclef, E., González-García, E., Taillandier, P., Hassoun, P., Parisot, S., Allain, C., Portes, D., Debus, N., Lurette, A. (2022), Alternative hormone free reproduction management of a dairy sheep flock disrupts the farm’s annual feeding system calendar and its associated strategies, Journal of Dairy Sciencehttps://doi.org/10.3168/jds.2022-22080

  

  • Laclef, E., Debus, N., Taillandier, P., González-García, E., Lurette, A (2022), Modelling the long-term consequences of implementing hormone-free reproductive management on the sustainability of a dairy sheep farm, Computers and Electronics in Agriculture, http://dx.doi.org/10.2139/ssrn.4237482

  

  • Benjamin Deneu, Alexis Joly, Pierre Bonnet, Maximilien Servajean and Francois Munoz (2022), Very high resolution Species Distribution Modelling based on remote sensing imagery: how to capture fine-grained and large-scale vegetation ecology with convolutional neural networks ?, Frontiers in Plant Science, https://hal.inrae.fr/hal-03695760

  

  • Pichon, L., Brunel, G., Payan, J.C. et al. (2021), ApeX-Vigne: experiences in monitoring vine water status from within-field to regional scales using crowdsourcing data from a free mobile phone application, Precision Agriculture, https://doi.org/10.1007/s11119-021-09797-9

  

  

  • Théo Martin, David Quentin, Pierre Gasselin (2021), Diversité et spatialité de la France laitière par le prisme des entreprises du robot de traite, 15èmes Journées de Recherches en Sciences Sociales (JRSS), INRA, SFER, CIRAD, Dec 2021, Toulouse, France.,https://hal.inrae.fr/hal-03514569

 

  • Schnebelin Eléonore (2021), Which digital uses for which ecologisation of agriculture?  The example of cereal farms in South-West France, European Association for Evolutionary Political Economy (EAEPE), 33rd conference, https://ideas.repec.org/p/hal/journl/hal-04009789.html

  

  

  • Maxime Ryckewaert (2021), Comparison between ParSketch-PLSDA and PLSDA in a context of large amounts of spectral data for sunflower genotype discrimination, NIR2021, https://hal.inrae.fr/hal-03783378

  

  • Josie Signe (2021), Extraction de sous-groupes exceptionnels de séries temporelles, RJCIA 2021 - Rencontres des Jeunes Chercheurs en Intelligence Artificielle, Jul 2021, Bordeaux / Virtual, France, https://hal.science/hal-03298742/document  

  

  

  • Laclef, E., Debus, N., Taillandier, P., García, E.G., Lurette, A. (2021), Exploring the impact of within flock variability on hormone-free dairy sheep farm performances, Presented at the 72nd Annual Meeting of the European Federation of Animal Science, Wageningen Academic Publishers, https://hal.inrae.fr/hal-03376302

  

  • Debus, N., Laclef, E., Lurette, A., Alhamada, M., Tesniere, A., González-García, E., Menassol, J.B., Bocquier, F. (2021), Factors influencing the short term ovarian response of milking Lacaune ewes to the male effect, Presented at the EAAP, 72th Annual Meeting of the European Federation of Animal Science, August 2021, Davos, Switzerland, https://hal.inrae.fr/hal-03376369

   

  • Tresson P., Tixier P., Puech W., Carval D. (2021), The challenge of biological control of Cosmopolites sordidus Germar (Col. Curculionidae): A review, Journal of Applied Entomology, https://agritrop.cirad.fr/599471/

  

  

  • Théo Martin,  Pierre Gasselin, Nathalie Hostiou, Gilles Feron, Lucette Laurens, François Purseigle (2021), Robots and Transformations of Work on Farms: A Systematic Review, , https://hal.inrae.fr/hal-03259549

  

  • Schnebelin, É., Labarthe, P., Touzard, J.-M. (2021), How digitalisation interacts with ecologisation? Perspectives from actors of the French Agricultural Innovation System, Journal of Rural Studies 86, 599–610, https://doi.org/10.1016/j.jrurstud.2021.07.023

  

  • Kenza Boumaza, Nesrine Kalboussi, Alain Rapaport, Sébastien Roux, Carole Sinfort (2021), Optimal control of a crop irrigation model under water scarcity, Optimal Control Applications and Methods, https://dx.doi.org/10.1002/oca.2749

  

  • Alessandra Biancolillo, Sebastien Preys, Belal Gaci, Jean-Luc Le-Quere, Hélène Labouré, Zoe Deuscher, Veronique Cheynier, Nicolas Sommerer, Noemie Fayeulle, Pierre Costet, Clotilde Hue, Renaud Boulanger, Karine Alary, Marc Lebrun, Marie Christine Lahon, Gilles Morel, Isabelle Maraval, Fabrice Davrieux, Jean-Michel Roger (2021), Multi-block classification of chocolate and cocoa samples into sensory poles, Food Chemistry, https://agritrop.cirad.fr/598703/  

  

  • Maxime Ryckewaert, Nathalie Gorretta, Fabienne Henriot, Alexia Gobrecht, Daphné Heran, Daniel Moura, Ryad Bendoula, Jean-Michel Roger (2021), Potential of high-spectral resolution for field phenotyping in plant breeding: Application to maize under water stress, Computers and Electronics in Agriculture, https://doi.org/10.1016/j.compag.2021.106385

  

  

  • Petit, J., Ait-Mouheb, N., Mas García, S., Metz, M., Molle, B., Bendoula, R. (2021), Potential of Visible/Near Infrared Spectroscopy coupled with chemometric methods for clogging estimation and discrimination in drip-irrigation, Biosystems Engineeringhttps://doi.org/10.1016/j.biosystemseng.2021.07.013

  

  

  • Ryckewaert,M., Metz, M., Héran, D., George, P., Grezes-Besset, B., Akbarinia, R., Roger, J.M., Bendoula, R. (2021), Massive spectral data analysis for plant breeding using parSketch-PLSDA method: discrimination of sunflower genotypes, Biosystems Engineering, https://hal.inrae.fr/hal-03329674 

  

  

  • Oger, B., Laurent, C., Vismara, P., Tisseyre, B. (2021), Is the optimal strategy to decide on sampling route always the same from field to field using the same sampling method to estimate yield?, Oeno One, https://doi.org/10.20870/oeno-one.2021.55.1.3334

  

  • Puneet Mishra, Roy Sadeh, Maxime Ryckewaert, Ehud Bino, Gerrit Polder, Martin P.Boer, Douglas N.Rutledge, Ittai Herrmann (2021), A generic workflow combining deep learning and chemometrics for processing close-range spectral images to detect drought stress in Arabidopsis thaliana to support digital phenotyping, Chemometrics and Intelligent Laboratory Systemshttps://doi.org/10.1016/j.chemolab.2021.104373 

  

  • Sílvia Mas Garcia, Maxime Ryckewaert, Florent Abdelghafour, Maxime Metz, Daniel Moura, Carole Feilhes, Fanny Prezman, Ryad Bendoula (2021), Combination of multivariate curve resolution with factorial discriminant analysis for the detection of grapevine diseases using hyperspectral imaging. A case study: flavescence dorée, Analyst, Royal Society of Chemistry, https://doi.org/10.1039/D1AN01735G

  

  

  • Midingoyi C.A., Pradal C., Enders A., Fumagalli D., Raynal H., Donatelli M., Athanasiadis I.N., Porter C., Hoogenboom G., Holzworth D., Garcia F., Thorburn P., Martre P. (2021), Crop2ML: An open-source multi-language modeling framework for the exchange and reuse of crop model components, Environmental Modelling and Softwarehttps://doi.org/10.1016/j.envsoft.2021.105055 

  

  • Silvie P.J., Martin P., Huchard M., Keip P., Gutierrez A., Sarter S. (2021), Prototyping a knowledge-based system to identify botanical extracts for plant health in sub-saharan africa, Plants, https://www.mdpi.com/2223-7747/10/5/896

  

  

  • Laclef, E., Debus, N., Taillandier, P., González-García, E., Lurette, A. (2021), REPROsheep: A model that integrates individual variability to optimise hormone-free reproduction management strategies for a dairy sheep flock, Computers and Electronics in Agriculture 189, 106412, https://doi.org/10/gmmq9h

  

  • Censi A.M., Ienco D., Gbodjo Y.J.E., Pensa R.G., Interdonato R., Gaetano R. (2021), Attentive Spatial Temporal Graph CNN for Land Cover Mapping from Multi Temporal Remote Sensing Data, IEEE Access, https://doi.org/10.1109/ACCESS.2021.3055554

  

  • Deneu B., Servajean M., Bonnet P., Botella C., Munoz F., Joly A (2021), Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment, PLoS Computational Biology, https://hal.inrae.fr/hal-03220977

  

  • Deneu B., Joly A., Bonnet P., Servajean M., Munoz F. (2021), How Do Deep Convolutional SDM Trained on Satellite Images Unravel Vegetation Ecology?, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), https://hal.inrae.fr/hal-03167637

  

  • Heidsieck G., de Oliveira D., Pacitti E., Pradal C., Tardieu F., Valduriez P. (2021), Cache-aware scheduling of scientific workflows in a multisite cloud, Future Generation Computer Systemshttps://doi.org/10.1016/j.future.2021.03.012

  

  • Keip P., Ferre S., Gutierrez A., Huchard M., Silvie S., Martin P (2020), Practical Comparison of FCA Extensions to Model Indeterminate Value of Ternary Data, The 15th International Conference on Concept Lattices and Their Applications (CLA 2020). Tallinn, Estonia, 29-1/06-07/2020, https://agritrop.cirad.fr/596562/

  

  • Pierre Gasselin, Françoise Jarrige, Théo Martin, Marc Moraine, Brigitte Nougaredes, et al (2020), La souveraineté alimentaire. Concept et conditions d'une mise en œuvre, Séminaire de l'UMR Innovation, UMR Innovation - Collectif AgriCités, Jun 2020, Montpellier, France, https://hal.inrae.fr/hal-03229183

  

  • K. Fauvel, D. Balouek-Thomert, D. Melgar, P. Silva, A. Simonet, G. Antoniu, A. Costan, V. Masson, M. Parashar, I. Rodero, and A. Termier. (2020), A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning, In Proceedings of the 34th AAAI Conference on Artificial Intelligence - AAAI'20, https://dx.doi.org/10.1609/aaai.v34i01.5376

  

  • K. Fauvel, V. Masson, and E. Fromont (2020), A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series Classifiers., In Proceedings of the IJCAI-PRICAI 2020 Workshop on Explainable Artificial Intelligence - IJCAI-PRICAI'20, https://arxiv.org/abs/2005.14501

  

  • Gabriel Volte, Eric Bourreau, Rodolphe Giroudeau, Olivier Naud (2020), Exact method approaches for the differential harvest problem, 21ème congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision (ROADEF 2020), https://link.springer.com/chapter/10.1007/978-3-030-58942-4_32

  

  • Commandré Ysé, Imbert Eric, Macombe Sophie, Mignon Sophie (2020), Transformation numérique d’une filière d’exportation : le cas des avocats en provenance du Pérou, XXVème Colloque de l’AIM - session pays émergents, Jun 2020, Marrakech, France, https://hal.science/hal-03011913

  

  • Commandré Ysé (2020), L’utilisation des images des producteurs agricoles pour la transparence alimentaire à l’aide de la blockchain, 9èmes rencontres des Perspectives critiques en management, Oct 2020, Paris, France, https://hal.science/hal-03011924

  

  

  

  

  • Commandré Ysé, Mignon Sophie, Macombe Catherine (2020), Transparence alimentaire et blockchain, quelles conséquences pour les producteurs agricoles en France ?, XXIXème conférence de l’AIMS - ST AIMS Systèmes Alimentaires, Jun 2020, Toulouse, France, https://hal.science/hal-03011901

  

  • Gaëlle Lefort, Laurence Liaubet, Cecile Canlet, Nathalie Villa, Rémi Servien (2020), ASICS: identification and quantification of metabolites in complex 1H NMR spectra, European RFMF Metabomeeting 2020, Jan 2020, Toulouse, France, https://hal.inrae.fr/hal-02790207

  

  • Gaëlle Lefort, Nathalie Vialaneix, Helene Quesnel, Marie–Christine Pere, Yvon Billon, et al (2020), Étude de la maturité des porcelets en fin de gestation par une approche métabolomique multifluide, 52. Journées de la Recherche Porcine, Feb 2020, Paris, France. IFIP – Institut du Porc, https://hal.archives-ouvertes.fr/hal-02479994/

  

  • G. Heidsieck, D. de Oliveira, E. Pacitti, C. Pradal, F. Tardieu, P. Valduriez (2020), Distributed Caching of Scientific Workflows in Multisite Cloud., DEXA 2020 : International Conference on Database and Expert Systems Applications, https://dx.doi.org/10.1007/978-3-030-59051-2_4

  

  • G. Heidsieck, D. de Oliveira, E. Pacitti, C. Pradal, F. Tardieu, P. Valduriez (2020), Cache-aware scheduling of scientific workflows in multisite cloud, BDA 2020 : Gestion de Données – Principes, Technologies et Applicationshttps://doi.org/10.1016/j.future.2021.03.012

  

  

  

  • K. Fauvel, T. Lin, V. Masson, E. Fromont, and A. Termier (2020), XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification, Mathematicshttps://doi.org/10.3390/math9233137

  

  

  

  • Gbodjo, Y.J.E.; Ienco, D.; Leroux, L.; Interdonato, R.; Gaetano, R.; Ndao, B. (2020), Object-Based Multi-Temporal and Multi-Source Land Cover Mapping Leveraging Hierarchical Class Relationships, Remote Sensing, https://inria.hal.science/hal-02931049/

  

  

  • Bélières Jean-François, Dianah Randriamitantsoa, Harimandranto Randrianirina, Noroseheno Ralisoa, Arthur Crespin-Boucaud (2020), Étude chaîne de valeur pomme de terre.Partie 1: Importance de la culture de la pomme de terre pour les exploitations agricoles etrentabilité de la production de plants de semence et de consommations, CASEF,  MAEP, https://hal.umontpellier.fr/hal-02963574

  

  

  • H. Deléglise, R. Interdonato, M. Roche, A. Bégué, M. Teisseire, E. Maître d'Hôtel (2020), Linking heterogeneous data for strengthening food security systems - Case of agricultural production in West Africa, Global Food Security, https://publications.cirad.fr/une_notice.php?dk=597783

  

  

  • Ivana Aleksovska, Laure Raynaud, Robert Faivre, François Brun and Marc Raynal (2020), Design and evaluation of calibrated and seamless ensemble weather forecasts for crop protection applications, AMS, https://doi.org/10.1175/WAF-D-20-0128.1

  

  

  

  • Cyrille Ahmed Midingoyi, Christophe Pradal, Ioannis N Athanasiadis, Marcello Donatelli, Andreas Enders, Davide Fumagalli, Frédérick Garcia, Dean Holzworth, Gerrit Hoogenboom, Cheryl Porter, Hélène Raynal, Peter Thorburn, Pierre Martre (2020), Reuse of process-based models: automatic transformation into many programming languages and simulation platforms, in silico plants, https://doi.org/10.1093/insilicoplants/diaa007

  

  • Braud A., Dolques X., Gutierrez A., Huchard M., Keip P., Le Ber F., Martin P., Nica C. and Silvie P (2020), Dealing with Large Volumes of Complex Relational Data using Relational Concept Analysis, Complex Data Analytics with Formal Concept Analysis, https://agritrop.cirad.fr/601324/

  

  

  • Kaaviya Velumani, Simon Madec, Benoit de Solan, Raul Lopez-Lozano, Jocelyn Gillet, Jeremy Labrosse, Stephane Jezequel, Alexis Comar, Frédéric Baret (2020), An automatic method based on daily in situ images and deep learning to date wheat heading stage, Field Crops Researchhttps://hal.inrae.fr/hal-03162912 

  

  • Nubukpo, Kako, Ludovic Temple, et Chloé Alexandre (2020), Innovation numérique et transformation structurelle des économies africaines francophones, opportunités risquées pour le développement ?, Technologie et innovation 5, https://doi.org/10.21494/ISTE.OP.2020.0515

  

  • Ludovic Temple, Chloe Alexandre (2020), Innovation numérique et transformation structurelle des économies africaines francophones, opportunités risquées pour le développement., Technologies et Innovations, https://agritrop.cirad.fr/595779/

  

  • Laborde, A., Jaillais, B., Roger, J. M., Metz, M., Bouveresse, D. J. R., Eveleigh, L., & Cordella, C. (2020), Subpixel detection of peanut in wheat flour using a matched subspace detector algorithm and near-infrared hyperspectral imaging, Talanta, https://doi.org/10.1016/j.talanta.2020.120993

  

  • Aichouche F., Kalboussi N., Rapaport A., Harmand J. (2020), Modeling and optimal control for production-regeneration systems - preliminary results -, European Control Conference 2020, ECC 2020, https://ieeexplore.ieee.org/document/9143741

  

  

  • Metz M.,Lesnoff M., Abdelghafour F., Akbarinia R., Masseglia F., Roger J.-M(2020), A “big-data” algorithm for KNN-PLS, Chemometrics and Intelligent Laboratory Systems, https://hal.inrae.fr/hal-02899789

  

  • Metz M., Biancolillo A., Lesnoff M., Roger J.-M. (2020), A note on spectral data simulation, Chemometrics and Intelligent Laboratory Systems, https://agritrop.cirad.fr/595280/

  

  

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  • Crespin-Boucaud, A.; Lebourgeois, V.; Lo Seen, D.; Castets, M.; Bégué, A (2020), Agriculturally consistent mappingof smallholder farming systems using remote sensing and spatial modelling, ISPRS—Int. Arch. Photogramm.Remote Sens. Spat. Inf. Sci, https://publications.cirad.fr/une_notice.php?dk=594282

 

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  • Ienco D., Gbodjo Y.J.E., Gaetano R., Interdonato R. (2020), Generalized Knowledge Distillation for Multi-Sensor Remote Sensing Classification: An Application to Land Cover Mapping, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, https://doi.org/10.5194/isprs-annals-V-2-2020-997-2020

  

  • Gbodjo Y.J.E., Ienco D., Leroux L. (2020), Toward Spatio-Spectral Analysis of Sentinel-2 Time Series Data for Land Cover Mapping, IEEE Geoscience and Remote Sensing Letters, https://hal.inrae.fr/hal-02950334

 

  • Crespin-Boucaud A., Lebourgeois V., Lo Seen D., Castets M., Bégué A. (2020), Agriculturally consistent mapping of smallholder farming systems using remote sensing and spatial modelling, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 10.5194/isprs-archives-XLII-3-W11-35-2020

  

  • Valentin, S., Mercier, A., Lancelot, R., Roche, M., Arsevska, E. (2020), Monitoring online media reports for early detection of unknown diseases: Insight from a retrospective study of COVID-19 emergence, Transboundary and Emerging Diseases, https://doi.org/10.1111/tbed.13738

  

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  • Pierre Bonnet, Alexis Joly, Jean-Michel Faton, Susan Brown, David Kimiti, Benjamin Deneu, Maximilien Servajean, Antoine Affouard, Jean-Christophe Lombardo, Laura Mary, Christel Vignau, François Munoz (2020), How citizen scientists contribute to monitor protected areas thanks to automatic plant identification tools, Ecological Solutions and Evidencehttps://doi.org/10.1002/2688-8319.12023

  

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  • Gaëtan Heidsieck, Daniel de Oliveira, Esther Pacitti, Christophe Pradal, François Tardieu, and Patrick Valduriez (2020), Efficient Execution of Scientific Workflows in the Cloud through Adaptive Caching, TLDKS Journal, https://doi.org/10.1007/978-3-662-62271-1_2

  

  • Heidsieck G., de Oliveira D., Pacitti E., Pradal C., Tardieu F., Valduriez P. (2020), Distributed caching of scientific workflows in multisite cloud, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), https://hal.inrae.fr/hal-02962579

 

  

  • I Aleksovska, L.Raynaud, R.Faivre, F. Brun, M. Raynal, O. Deudon, F. Souverain (2019), Accounting for the uncertainty of weather forecasts in decision support systems used for crop management, 12th EFITA International Conference, 27-29 June, 2019, Rhodes island, Greece, https://www.cabdirect.org/cabdirect/abstract/20193089494

  

  • A. Cheraiet, M. Carra, A. Lienard, S. Codis, A. Vergès, X. Delpuech, O. Naud. (2019), Investigation on LiDAR based indicators for predicting agrochemical deposition within a vine field., Precision Agriculture 2019, Proceedings of the 12th European Conference on Precision Agriculture, https://doi.org/10.3920/978-90-8686-888-9

  

  • G Heidsieck, D De Oliveira, E Pacitti, C Pradal, F Tardieu, P Valduriez (2019), Adaptive Caching for Data-Intensive Scientific Workflows in the Cloud, Dexa 2019:International Conference on Database and Expert Systems Applications, 452-466, https://agritrop.cirad.fr/593357/

  

  • Keip Priscilla, Ouzerdine Amirouche, Huchard Marianne, Silvie Pierre, Martin Pierre (2019), Navigation conceptuelle dans une base de connaissances sur l'usage des plantes en santé animale et végétale, CORIA 2019, 16th French Information Retrieval Conference, https://agritrop.cirad.fr/593472/1/Keip_et_al_2019a.pdf

  

  • Keip Priscilla, Gutierrez Alain, Huchard Marianne, Le Ber Florence, Sarter Samira, Silvie Pierre, Martin Pierre (2019), Effects of input data formalisation in relational concept analysis for a data model with a ternary relation, International Conference on Formal Concept Analysis (ICFCA 2019), https://link.springer.com/chapter/10.1007%2F978-3-030-21462-3_13

  

  • Bazin Alexandre, Carbonnel Jessie, Huchard Marianne, Kahn Giacomo, Keip Priscilla, Ouzerdine Amirouche. (2019), On-demand relational concept analysis, IFCA 2019, https://arxiv.org/abs/1803.07847

  

  • P. Borianne, J. Sarron, F. Borne and E. Faye (2019), Deep mangoes: from fruit detection to cultivar identification in color images of mango trees, DISP'19 - International Conference on Digital image and Signal Processing, Oxford, Royaume-Uni, https://hal.umontpellier.fr/hal-02295256

  

  • Tresson P., Tixier P., Puech W., Carval D. (2019), Insect interaction analysis based on object-detection and convolutional neural networks., IEEE MMSP, 10.1109/MMSP.2019.8901798

  

  • Sarron J., Sané C.A.B., Diatta P., Malézieux É, Faye É (2019), Plant diversity affects the productivity of Senegalese mango orchards: evidences from UAV photogrammetry, 4th World Congress of Agroforestry, https://agritrop.cirad.fr/592664/

  

  • A. Taleb Bendiab, M. Ryckewaert, D. Heran, C. Vigreux, R. Escalier, R. K. Kribich, R. Bendoula (2019), Optical sensor combined with chemometric methods for the spray deposits characterization, NIR2019, Gold Coast (Australie), septembre 2019, https://inria.hal.science/hal-02319691/

  

  • Lachia N., Pichon L., Tisseyre B., (2019), A collective framework to assess the adoption of precision agriculture in France: Description and preliminary results after two years, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, https://www.wageningenacademic.com/doi/10.3920/978-90-8686-888-9_105

  

  • Rabatel G., Lamour J., Moura D., Naud O. (2019), A multispectral processing chain for chlorophyll content assessment in banana fields by UAV imagery, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, https://doi.org/10.3920/978-90-8686-888-9_51

  

  

  • Lamour J., Leroux C., Le Moguédec G., Naud O., Léchaudel M., Tisseyre B., (2019), Disentangling the sources of chlorophyll-content variability in banana fields, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, https://doi.org/10.3920/978-90-8686-888-9_37

  

  • Oger, B., Vismara, P., Tisseyre, B. (2019), Échantillonnage sous contraintes en viticulture de précision, Proc. 12th European Conference on Precision Agriculture (ECPA 2019)., pp. 173-179, 2019, https://hal.science/lirmm-01924365/

  

  • Oger B., Vismara P., Tisseyre B. (2019), Combining target sampling with route-optimization to optimise yield estimation in viticulture, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, https://doi.org/10.1007/s11119-020-09744-0

  

  • C. Laurent, M. Baragatti, J. Taylor, T. Scholasch, A. Metay, B. Tisseyre (2019), Evaluation of a functional Bayesian method to analyse time series data in precision viticulture, 12th European Conference on Precision Agriculture (ECPA 2019), Montpellier SupAgro, Montpellier, France, https://dx.doi.org/10.3920/978-90-8686-888-9_7

  

  • Leroux C., Taylor J., Tisseyre B. (2019), Production gap analysis - an operational approach to yield gap analysis using historical high-resolution yield data sets, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, https://doi.org/10.3920/978-90-8686-888-9_8

  

  • Leroux C., Jones H., Tisseyre B. (2019), An iterative region growing algorithm to generate fuzzy management zones within fields, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, https://hal.inrae.fr/hal-02609780

  

  • Brunel G., Pichon L., Taylor J., Tisseyre B. (2019), Easy water stress detection system for vineyard irrigation management, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, https://doi.org/10.3920/978-90-8686-888-9_115

  

  • Pichon L., Leroux C., Geraudie V., Taylor J., Tisseyre B., (2019), Investigating the harmonization of highly noisy heterogeneous datasets hand-collected over the same study domain, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, https://doi.org/10.3920/978-90-8686-888-9_91

  

  • C. Laurent, M. Baragatti, J. Taylor, B. Tisseyre, A. Metay, T. Scholasch (2019), Data mining approaches for time series data analysis in viticulture. Potential of the BLiSS (Bayesian Functional Linear Regression with Sparse Step functions) method to identify temperature effects on yield potential, Accepted to the 21st Group of international Experts for Cooperation on Viti-vinicultural Systems INternational Meeting (GiESCO 2019) , Aristotle UNiversity of Thessaloniki, Thessaloniki, Greece, https://ives-openscience.eu/4385/

  

  • I. Piot-Lepetit, M. Florez, K. Gauche, Understanding the determinants of IT adoption in Agriculture using an integrated TAM-TOE model: A bibliometric analysis, 170e séminaire de l’EAAE, Montpellier les 15-17 mai 2019.  Session sur « Digital agriculture and Food chains », https://hal.inrae.fr/hal-02789959

  

  • B. Biao, L. Temri, N. Lachia (2019), Co-construction of innovation processes: What types of innovation networks in digital agriculture? 170e séminaire de l’EAAE, Montpellier les 15-17 mai 2019.  Session sur « Digital agriculture and Food chains », https://hal.inrae.fr/hal-02788884

  

  • I. Piot-Lepetit, M. Florez, K. Gauche (2019), Identifying the determinants of IT adoption in Agriculture: On the use of an integrated TAM-TOE model, 13e JRSS (Journées de Recherches en Sciences Socilaes (SFER-Inra-Cirad), Bordeaux, 12-13 décembre 2019. Session « Agriculture numériques et nouveaux usages en amont et à l’aval, https://hal.science/hal-02437653

  

  • Araba N. and François-Heude A (2019), Price discovery and volatility spillovers in the French wheat market, Journées doctorales Augustin Cournot organisées par l’Université de Strasbourg, https://hal.science/hal-03088859

 

  • Lefort, G., Liaubet, L., Canlet, C., Quesnel, H., Vialaneix, N., Servien, R. (2019), ASICS: a new R package for identification and quantification of metabolites in complex 1H NMR spectra, useR! 2019, https://hal.inrae.fr/hal-02789726

  

  • Gauthier, R., Largouët, C., Gaillard, C., Cloutier, L., Guay, F., Dourmad, J.-Y. (2019), Modélisation dynamique de l’utilisation des nutriments et des besoins individuels chez la truie en lactation, 51. Journées de la Recherche Porcine, https://hal.inrae.fr/hal-02738447

  

  • Nguyen Ba, H., Van Milgen, J., Taghipoor, M. (2019), Modelling the feed intake response of growing pigs to diets contaminated with mycotoxins, Proceedings of the 9th Workshop on Modelling Nutrient Digestion and Utilization in Farm Animals, https://doi.org/10.1017/S175173112000083X

  

  • Fize, J., Roche, M., Teisseire, M. (2019), Matching heterogeneous textual data using spatial features, IEEE International Conference on Data Mining Workshops, ICDMW, https://agritrop.cirad.fr/589684/

  

  

  • Deneu, B., Servajean, M., Botella, C., Joly, A. (2019), Evaluation of deep species distribution models using environment and  co-occurrences, International Conference of the Cross-Language Evaluation Forum for European Languages, https://doi.org/10.48550/arXiv.1909.08825

  

  • Gaëtan Heidsieck, Daniel de Oliveira, Esther Pacitti, Christophe Pradal, François Tardieu, Patrick Valduriez (2019), Adaptive Caching for Data-Intensive Scientific Workflows in the Cloud, Dexa 2019: Database and Expert Systems Applications, https://sde.hal.science/hal-02174445/

  

  • Gaëtan Heidsieck, Daniel de Oliveira, Esther Pacitti, Christophe Pradal, François Tardieu, Patrick Valduriez (2019), Efficient Execution of Scientific Workflows in the Cloud through Adaptive Caching, BDA2019: Gestion de Données – Principes, Technologies et Applications, https://doi.org/10.1007/978-3-662-62271-1_2

 

  • Alexandre Chloé et Modeste Florentin Bationo (2019), Une transformation des services de conseil agricole grâce au numérique ?, Grain de sel janvier – juin 2019 (no 77), 2p., https://agritrop.cirad.fr/593190/

  

  • Raynal ; M., Vergnes, M. Brun, F. Chen, M. (2019), Pronostic d’apparition du Mildiou : un challenge participatif en vue d’améliorer les Outils d’Aide à la Décision de demain, Technique IFV, https://rd-agri.fr/detail/DOCUMENT/acta_113

  

  • Faye, É. ; Sarron, J.; Diatta J. ; Borianne P. (2019), PixFruit Mangue : un outil d'acquisition, de gestion, et de partage de données pour une normalisation de la filière Mangue en Afrique de l'Ouest aux services de ses acteurs, AgriNumA, https://agritrop.cirad.fr/592757/

  

  • Lefort, G., Vialaneix, N., Quesnel, H., Pere, M.-C., Iannuccelli, N., Canlet, C., Paris, A., Servien, R., Liaubet, L., Study of fetal pig maturity in relation with neonatal survival using a multi-fluids metabolomic approach, Presented at 15. Annual Conference of the Metabolomics Society (Metabolomics 2019), La Haye, NLD, https://hal.inrae.fr/hal-02791588

  

  

  

  • Chen Mathilde, Brun François, Raynal Marc,  Debord Christian & Makowski David (2019), Use of probabilistic expert elicitation for assessing risk of appearance of grape downy mildew, Crop Protection, https://doi.org/10.1016/j.cropro.2019.104926

  

  • Tresson P., Tixier P., Puech W., Bagny Beile L., Roudine S., Pagès C., Carval  D. (2019), CORIGAN: Assessing multiple species and interactions within images, Methods in Ecology & Evolution, https://doi.org/10.1111/2041-210X.13281

  

  • Tresson P., Tixier P., Puech W., Carval D. (2019), Insect interaction analysis based on object detection and CNN, IEEE 21st International Workshop on Multimedia Signal Processing, https://ieeexplore.ieee.org/document/8901798

  

  

  • Bendiab, A.T, Ryckewaert, M, Heran, D, Escalier, R, Kribich, R.K, Vigreux, C., Bendoula (2019), Coupling waveguide-based micro-sensors and spectral multivariate analysis to improve spray deposit characterization in agriculture, Sensors, https://inria.hal.science/hal-02297422/

  

  • Araya-Alman M., Leroux C., Acevedo-Opazo C., Guillaume S., Valdés-Gómez H., Verdugo-Vásquez N., Pañitrur-De la Fuente C., Tisseyre B. (2019), A new localized sampling method to improve grape yield estimation of the current season using yield historical data, Precision Agriculture, https://link.springer.com/article/10.1007/s11119-019-09644-y

  

  • J. Lamour, O. Naud, M. Lechaudel, G. Le Moguédec, J. Taylor and B. Tisseyre (2019), Spatial analysis and mapping of banana crop properties: issues of the asynchronicity of the banana production and proposition of a statistical method to take it into account, Precision Agriculture, https://hal.umontpellier.fr/hal-02492098v1

  

  

  • Cheraiet A., Carra M., Lienard A., Codis S., Vergès A., Delpuech X., Naud O. (2019), Investigation on LiDAR-based indicators for predicting agrochemical deposition within a vine field, Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019, https://doi.org/10.3920/978-90-8686-888-9

  

  • Taylor J.A., Tisseyre B., Leroux C. (2019), A simple index to determine if within-field spatial production variation exhibits potential management effects: application in vineyards using yield monitor data, Precision Agriculture, https://hal.inrae.fr/hal-02608141

  

  • Leroux C., Tisseyre B., (2019), How to measure and report within-field variability: a review of common indicators and their sensitivity, Precision Agriculture, https://hal.science/hal-02607864/

  

  • Leroux C., Jones H., Clenet A., Tisseyre B. (2019), Knowledge discovery and unsupervised detection of within-field yield defective observations, Computers and Electronics in Agriculture, https://doi.org/10.1016/j.compag.2018.12.024

  

  

  • N. Kalboussi, S. Roux, B. Cheviron, J. Harmand, A. Rapaport, C. Sinfort (2019), Apport de la modélisation pour l’aide à la décision en vue de la réutilisation agricole des eaux usées traitées, Journal International Sciences et Techniques de l'Eau et de l'Environnement (JISTEE), Vol. 3 (1), pp.102-107, https://hal.science/hal-02623553/

  

  • Devaux N., Crestey T., Leroux C., Tisseyre B. (2019), Potential of Sentinel-2 satellite images to monitor vine fields grown at a territorial scale, Oeno One, https://hal.inrae.fr/hal-02609421

  

  • Fauvel K., Masson V., Fromont É., Faverdin P., Termier A. (2019), Towards sustainable dairy management - A machine learning enhanced method for estrus detection, Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, https://inria.hal.science/hal-02190790

  

  • Gauthier, R., Largouët, C., Gaillard, C., Cloutier, L., Guay, F., Dourmad, J.-Y. (2019), Dynamic modeling of nutrient use and individual requirements of lactating sows, Journal of Animal Science, https://doi.org/10.1093/jas/skz167

  

  • Gaillard, C., Gauthier, R., Cloutier, L., Dourmad, J.-Y. (2019), Exploration of individual variability to better predict the nutrient requirements of gestating sows, Animal, https://doi.org/10.1093/jas/skz320

  

  • Yawogan Jean Eudes Gbodjo, Dino Ienco, Louise Leroux (2019), Toward Spatio–Spectral Analysis of Sentinel-2 Time Series Data for Land Cover Mapping, IEEE Geoscience and Remote Sensing Letters, https://hal.inrae.fr/hal-02950334

  

  • Renier, L., Cardona, A., Lécrivain, E (2018), New arrangements for an agroecological management of animal health. The case of French farmers learning homeopathy, Presented at 13. European IFSA Symposium, Chania, Crete, GRC, https://prodinra.inra.fr/record/435567

  

  • Alexandre, Chloé (2018), Technologies de l’information et La Communication et Accompagnement Des Agriculteurs En Afrique de l’Ouest : Quelles Nouvelles Configurations Des Services de Conseil Agricole ? Proposition d’une Grille d’analyse, Conférence RRI, Nîmes, Atelier « Changements Organisationnels et Conseil : Nouvelles Formes d’accompagnement Du Processus d’innovations », 17p., https://agritrop.cirad.fr/592308/

  

  • Gauthier, R., Guay, F., Brossard, L., Largouët, C., Dourmad, J.-Y (2018), Precision feeding of lactating sows: development of a decision support tool to handle variability, EAAP 2018 - 69th Annual Meeting of the European Federation of Animal Science, Wageningen Academic Publishers, Dubrovnik, Croatia, https://hal.inrae.fr/view/index/identifiant/hal-01949645

  

  • Goel, R., Sallaberry, A., Fadloun, S., (...), Valentin, S., Poncelet, P. (2018), EpidNews: An epidemiological news explorer for monitoring animal diseases, 11th International Symposium on Visual Information Communication and Interaction, VINCI 2018; Vaxjo; Sweden; 13 August 2018 through 15 August 2018, https://www.hal.inserm.fr/AGROPOLIS/lirmm-01911990

  

  

  • Valentin, S., Lancelot, R., Roche, M. (2018), How to combine spatio-temporal and thematic features in online news for enhanced animal disease surveillance? 22nd International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2018; Metropol Palace HotelBelgrade; Serbia; 3 September 2018 through 5 September 2018, https://doi.org/10.1016/j.procs.2018.07.283

  

  

  • Julien Sarron, Éric Malézieux, Cheikh Amet Bassirou Sané and Émile Faye (2018), Mango Yield Mapping at the Orchard Scale Based on Tree Structure and Land Cover Assessed by UAV, Remote Sensing, https://doi.org/10.3390/rs10121900

  

  

  • Corentin Leroux, Hazaël Jones, Léo Pichon, Serge Guillaume, Julien Lamour, James Taylor, Olivier Naud, Thomas Crestey, Jean-Luc Lablee and Bruno Tisseyre (2018), GeoFIS: An Open Source, Decision-Support Tool for Precision Agriculture Data, Agriculture, https://hal.science/hal-02068798

  

  • Kalboussi, N., Harmand, J., Rapaport, A., ...Ellouze, F., Ben Amar, N. (2018), Optimal control of physical backwash strategy - towards the enhancement of membrane filtration process performance, Journal of Membrane Science, https://www.hal.inserm.fr/MIPS/hal-01591027v1

  

  • Cerón-Vivas, A., Kalboussi, N., Morgan-Sagastume, J.M., Harmand, J., Noyola, A. (2018), Model assessment of the prevailing fouling mechanisms in a submerged membrane anaerobic reactor treating low-strength wastewater, Bioresource Technology, https://doi.org/10.1016/j.biortech.2018.08.017

  

  • Alexandre, Chloé (2018), Comment l’utilisation des technologies de l’information et de la communication transforme-t-elle les dispositifs de conseil agricole ? Une enquête auprès de 16 services au Burkina Faso, Fiche de capitalisation AFD. Processus de réflexion sur le conseil agricole. Montpellier : CIRAD-AFD, 19p., https://doi.org/10.13140/RG.2.2.20335.25763

  

  • Bendiab, A.T, Ryckewaert, M, Heran, D, Escalier, R, Kribich, R.K, Vigreux, C., Bendoula (2018), Chalcogenide rib waveguides for the characterization of spray deposits, Optical Materials, https://doi.org/10.1016/j.optmat.2018.10.021

  

  • Kalboussi, Roux, Cheviron, Harmand, Rapaport, Sinfort (2018), Contribution of modeling to the decision support for agriculture reuse of treated wastewater, Journal International Sciences de l'Eau, du Climat et de l'Environnement, https://hal.science/hal-01975462/

  

  • Tisseyre, B., Leroux, C., Pichon, L., Geraudie, V., Sari, T. (2018), How to define the optimal grid size to map high resolution spatial data? Precision Agriculture 19(5), pp. 957-971, https://hal.inrae.fr/hal-02607457

  

  

  • Arsevska, E; Valentin, S; Rabatel, J; de Herve, JDG; Falala, S; Lancelot, R; Roche, M. (2018), Web monitoring of emerging animal infectious diseases integrated in the French Animal Health Epidemic Intelligence System, Web of sciences, https://doi.org/10.1371/journal.pone.0199960

  

  • Pradal, S. Cohen-Boulakia, G. Heidsieck, E. Pacitti, C. Pradal, F. Tardieu, P. Valduriez (2018), Distributed Management of Scientific Workflows for High-Throughput Plant Phenotyping., ERCIM News 2018, Smart Farming (pp.36-37), https://hal.inria.fr/hal-01948568

  

  • C. Laurent, T. Scholasch, B. Tisseyre, A. Metay (2021), Building New Temperature Indices for a local understanding of grapevine physiology, XIIIth International Terroir Congress, Virtual Congress, Adelaide, Australia, https://ives-openscience.eu/6730/

  

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