Creating shared value(s) from On-Farm Experimentation: ten key lessons learned from the development of the SoYield® digital solution in Africa

Autor: Chloé Alexandre, Léa Tresch, Julien Sarron, Jéremy Lavarenne, Gaspard Bringer, Hamza Rkha Chaham, Hamza Bendahou, Sofia Carmeni, Philippe Borianne, Jean-Mathias Koffi, Emile Faye

Publikováno v: Agronomy for Sustainable Development

This study is based on the observation that many digital tools and services for agriculture do not put farmers' expectations and interests first, resulting in top-down research and development. On-Farm Experimentation (OFE) contributes to overcoming

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c7f6eed394d1b18a4e31c136dbfd90f
https://doi.org/10.1007/s13593-023-00888-7

A First Attempt to Combine NIRS and Plenoptic Cameras for the Assessment of Grasslands Functional Diversity and Species Composition

Autor: Julien, Simon Taugourdeau, Mathilde Dionisi, Mylène Lascoste, Matthieu Lesnoff, Jean Marie Capron, Fréderic Borne, Philippe Borianne, Lionel

Publikováno v: Agriculture; Volume 12; Issue 5; Pages: 704

Grassland represents more than half of the agricultural land. Numerous metrics (biomass, functional trait, species composition) can be used to describe grassland vegetation and its multiple functions. The measures of these metrics are generally destr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=multidiscipl::f4f71e16180c6ba25ac23a59181adc81

Modelling the functional dependency between root and shoot compartments to predict the impact of the environment on the architecture of the whole plant. Methodology for model fitting on simulated data using Deep Learning techniques

Autor: Jean-François Barczi, Yves Caraglio, Philippe Borianne, Abel Louis Masson, Eric Nicolini

Publikováno v: in silico Plants
in silico Plants, Oxford Academic, In press, ⟨10.1093/insilicoplants/diab036⟩
in silico Plants, 2022, 4 (1), ⟨10.1093/insilicoplants/diab036⟩
In Silico Plants

Tree structural and biomass growth studies mainly focus on the shoot compartment. Tree roots usually have to be taken apart due to the difficulties involved in measuring and observing this compartment, particularly root growth. In the context of clim

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::acee61c526ea95ab6e25ca33408fa282
https://hal.inrae.fr/hal-03456803

Urban object classification with 3D Deep-Learning

Autor: Gérard Subsol, Philippe Borianne, Marc Chaumont, Mustapha Derras, Younes Zegaoui

Publikováno v: Biennial International Joint Urban Remote Sensing Event
JURSE: Joint Urban Remote Sensing Event
JURSE: Joint Urban Remote Sensing Event, May 2019, Vannes, France
2019 Joint Urban Remote Sensing Event (JURSE 2019): Proceedings of a meeting held 22-24 May 2019, Vannes, France
JURSE
JURSE 2019-Joint Urban Remote Sensing Event
JURSE 2019-Joint Urban Remote Sensing Event, May 2019, Vannes, France. ⟨10.1109/JURSE.2019.8809043⟩
HAL

International audience; Automatic urban object detection remains a challenge for city management. Existing approaches in remote sensing include the use of aerial images or LiDAR to map a scene. This is, for example, the case for patch-based detection

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5841545107b53a23bd68f58cffcacc3f
https://hal-lirmm.ccsd.cnrs.fr/lirmm-02087761/file/JURSE-2019-ZEGAOUI-CHAUMONT-SUBSOL-BORIANNE_DERRAS_UrbanObjectClassification_3D_DL.pdf

Is machine learning efficient for mango yield estimation when used under heterogeneous field conditions?

Autor: Philippe Borianne, Thibault Nordey, Cheikh Amet Bassirou Sane, Julien Sarron, Frédéric Normand, Emile Faye, Paterne Diatta, Eric Malézieux, Youga Niang

Publikováno v: Acta Horticulturae
II Symposium on Mechanization, Precision Horticulture, and Robotics
II Symposium on Mechanization, Precision Horticulture, and Robotics, F. Larcher; J. Ochoa Rego; V. Loges; S. Sever Mutlu; S. Arslan; R. Ehsani, Aug 2018, Istanbul, Turkey. pp.201-208, ⟨10.17660/ActaHortic.2020.1279.30⟩
Proceedings of the VII Conference on Landscape and Urban Horticulture, IV Conference on Turfgrass Management and Science for Sports Fields and II Symposium on Mechanization, Precision Horticulture, and Robotics: : XXX International Horticultural Congress

International audience; In the last decade, image analysis using machine learning algorithms proved its potential for the detection and counting of plant organs. Numerous studies provided fruit tree yield estimates based on machine learning with high

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::961882234b4feea9c3db7db9d34643ee
https://hal.inrae.fr/hal-02911639