0000000000969444

AUTHOR

Christelle Gée

showing 17 related works from this author

Tendances d'évolution de l'agriculture

2015

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology
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Agricultural machinery chair: design an innovative teaching solution to answer to new industrial challenges.

2019

AgroSup Dijon is a French public Institution of Higher Education for agronomic sciences, food and the environment. It is the only French public institution accredited to issue graduate level (Master and Doctoral degrees) in Agricultural Machinery and Precision Farming with a team of academics specialised in agricultural equipment and innovative technologies dedicated to Precision Agriculture. Close ties to industry offer our graduates the opportunity to develop their professional skills. Our programs combine hands-on learning with relevant classroom work. However, times are changing for the agricultural machinery branch. International trade is an everyday fact, for most companies. Companies…

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology
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Spot spraying in oilseeds and protein crops

2019

International audience; Currently, spraying chemical products in agriculture became the main means of weed controlbecause this cultural practice is very fast, inexpensive and very effective. However, awarenessof their negative impacts (environment, human health) requires thinking about new technicaland agronomic solutions. New technologies are promising techniques for a site-specific weedmanagement through the development of localized spraying.Some sprayers (often small width) located on the row may be able to answer thoseexpectations but they are most often expensive. In this context, the objective of the project“PLEVOP” (development of spot sprayer in oilseed and protein crops), proposed …

[SPI]Engineering Sciences [physics]Precision agriculture[SPI] Engineering Sciences [physics][SDV]Life Sciences [q-bio]Protein crop[SDE]Environmental SciencesOilseed[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal BiologySpraying
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Competitive effect of segetal plants and common weeds upon barley (Hordeum vulgare L.) cultivated in mixture

2022

[SDV] Life Sciences [q-bio]
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Development of a low-cost portable PAR device for crop management

2021

Context: It becomes essential to have precise monitoring of crop growth to ensure rapid action in case of problems. Plant growth depends on the biomass accumulated by photosynthesis that requires as an energy source, the photosynthetically active radiation (PAR). This local variable is essential to study the plant phenology and for ecophysiological models that predict the accumulation of dry matter on a daily basis. Objectives: We design and evaluate a low-cost portable device, PAR Acquisition Device (PARADe), combining a PAR radiation sensor and a microcontroller acquisition card (Arduino) in order to measure automatically the in-field photosynthetically active radiation.

[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy[SDV.SA.STA]Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agriculture[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy[SDV.SA.STA] Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agricultureComputingMilieux_MISCELLANEOUS
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Potential of visible (RGB) imagery for dynamic monitoring of nitrogen requirements in winter wheat using the innovative APPI-N method

2022

The balance-sheet method has been widely used for decades as a reference method to calculate the amount of nitrogen (N) fertilizer to supply to winter wheat. With this method, the amount of N fertilizer is calculated at the end of the winter to support the N requirement for an estimated yield level. This method is now being questioned because it has become difficult to predict yields, given climate change and the increased presence of pests in agroecological cropping systems, resulting in greater uncertainty about the yield achieved compared to conventional systems of the past. Alternative methods, such as the innovative approach of nitrogen fertilization (APPI-N; Ravier et al., 2018), are …

[SDV] Life Sciences [q-bio]
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Towards the estimation of vole damage on grassland by aerial multispectral imaging

2017

International audience

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences[SDV.SA]Life Sciences [q-bio]/Agricultural sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[ SDV.SA ] Life Sciences [q-bio]/Agricultural sciencesComputingMilieux_MISCELLANEOUS
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Localized spraying in oilseeds rape crop with a conventional boom sprayer

2019

As a part of ECOPHYTO plan established by the French government to reduce the use of chemical plant protection products (PPP), specific spraying equipment are needed, for example to spray only the row of the crop. Often these devices have small spray boom widths and they are very expensive. The objectives of the project “PLEVOP” (development of in-row sprayer in oleaginous crops and protein crops), proposed by the technical Institute Terres-Inovia, are to define the conditions for successful localized post-emergence spraying for the herbicide application on the row using large width devices. This work is carried out in connection with a manufacturer of agricultural equipment (the Marechal c…

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology
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A crop field modeling to simulate agronomic images

2010

In precision agriculture, crop/weed discrimination is often based on image analysis but though several algorithms using spatial information have been proposed, not any has been tested on relevant databases. A simple model that simulates virtual fields is developed to evaluate these algorithms. Virtual fields are made of crops, arranged according to agricultural practices and represented by simple patterns, and weeds that are spatially distributed using a statistical approach. Then, experimental devices using cameras are simulated with a pinhole model. Its ability to characterize the spatial reality is demonstrated through different pairs (real, virtual) of pictures. Two spatial descriptors …

PixelComputer sciencebusiness.industryNearest neighbour algorithmComputer visionImage processingPrecision agricultureArtificial intelligenceFunction (mathematics)Virtual realityReal imagebusinessSpatial analysis2010 4th International Symposium on Communications, Control and Signal Processing (ISCCSP)
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Tracking Ideal Varieties and Cropping Techniques for Agroecological Weed Management: A Simulation-Based Study on Pea.

2022

Book of abstract p.110-111; International audience; Pea (Pisum sativum L.) is a key diversification crop but current varieties are not verycompetitive against weeds. The objective of this study was to identify, depending on the typeof cropping system and weed flora, (1) the key pea parameters that drive crop production,weed control and weed contribution to biodiversity, (2) optimal combinations of peaparameter values and crop-management techniques to maximise these goals. For this, virtualexperiments were run, using FLORSYS, a mechanistic simulation model (Colbach et al., 2021,Field Crops Res 261:108006). This individual-based 3D model simulates daily crop-weed seedand plant dynamics over t…

[SDV]Life Sciences [q-bio]TraitPea[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/AgronomyTrade-offWeed damageIdeotypeMulti-criteria decisionPlant Science[SDV] Life Sciences [q-bio]Yield gap[SDV.SA.STA]Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agricultureYield loss[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyFrontiers in plant science
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Mesocosm evaluation of the competittive ability of common and segetal weed species against barley

2022

In conventional cropping systems, arable weed species have always been considered undesirable because their presence can significantly reduce the yield and quality of the crop. Among the weed community, segetal weeds particularly inhabit winter cereal fields and are generally described as rare species (Jauzein, 1997). Following the observed decline in biodiversity in the field, there is a renewed interest in conserving segetal weeds as they represent an invaluable plant heritage as wild relatives of cultivated plants (Fried, 2020). The origin of the regression of these particular annual species is strongly linked to intensive agricultural practices (herbicides, fertilization) but also proba…

[SDV] Life Sciences [q-bio]
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Apport du numérique dans la gestion des intrants chimiques

2022

[SDV] Life Sciences [q-bio]
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Demain, l’agriculture sera 2.0 - Comment se préparer à l’arrivée des nouvelles technologies ?

2015

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology
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Aerial imagery for site specific weed management

2015

National audience

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal BiologyComputingMilieux_MISCELLANEOUS
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Digital tools for a biomass prediction from a plant-growth model. Application to a weed control in wheat crop

2019

International audience; Weed control is essential for crop quality and yield. Usually, the main factors affectingdecision-making of farmers in weeding are based on the presence of certain weedvarieties and their density (plants/m2). However, the weed management at the scale ofthe crop cycle refers to other competition indicators, more reliable, such as plantbiomass or leaf area index (LAI). Classically, plant biomass measurements are obtainedby a destructive method of sampling, time consuming and it turns out to be unworkablein practice for farmers. This project proposes to study an innovative method of biomassevaluation which is based on the acquisition of plot images to determine the leaf…

[SDV] Life Sciences [q-bio][SDE] Environmental Sciencesgrowth modelwheat[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal BiologyImageryWeedsBiomass[INFO.INFO-BT]Computer Science [cs]/Biotechnology
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Approche multicritère pour la caractérisation des adventices par imagerie

2019

La réduction des produits phytosanitaires représente un des enjeux majeurs du secteur agricole. Les plans gouvernementaux Ecophyto, Ecophyto II et Ecophyto II+ visent à réduire fortement leurs usages et les solutions actuelles ne permettent pas d’obtenir les résultats escomptés. La détection des adventices par imagerie est un des axes de travail devant permettre cette réduction. La qualité de la discrimination cultures/adventices est fortement liée au type de méthodes utilisées, à la résolution spatiale des images et au stade de développement des plantes présentes. L'objectif de ce travail, est donc d'évaluer l’impact des différents critères pouvant être extraits depuis des images acquises …

[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingVision par ordinateurPrédiction[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil studyStatistiqueAnalyse d'image
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Définir ensemble le futur du secteur des agroéquipements - Mission ministérielle

2015

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology
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