Since 1st September 2018, I have been working as a Research Scientist in the team ‘Virology’ of the Plant Pathology Research Unit (INRAE, Avignon). My main research interest focus on the identification of efficient, cost-effective and durable strategies to manage plant diseases and especially those caused by viruses on vegetablecrops.
RESEARCH ACTIVITIES
I use spatiotemporal simulation models, complemented with laboratory and glasshouse experiments, as well as statistical analyses of epidemiological data. These experiments and field data result in the acquisition of crucial knowledge on the biology of the interactions between host plants, pathogens and possibly their vectors. Indeed, these knowledge give the possibility to calibrate model parameters or test model predictions, and can be very helpful to identify promising control methods. Finally, it is crucial for me to identify strategies that match with farmers’ needs, and communicate them in such a way that my researches have an impact on the real world.
1. Modelling control strategies of epidemics
Simulation models are very useful to optimise management strategies of epidemics, and circumvent the ethical, legal, logistical and economic constraints associated with experiments at large spatiotemporal scales. My models simulate the epidemiological dynamics of pathogens in cultivated landscapes under disease management, and aim at optimising management strategies. However, pathogens have an extraordinary evolutionary potential that allow them to overcome control methods employed in the field. This is particularly the case with the deployment of plant resistance. Thus, because they include pathogen evolution, the demo-genetic models I use are of great interest, and enable the identification of strategies that are both efficient and durable to manage plant diseases.
In collaboration with the BioSP unit (Biostatistics and spatial processes, INRAE PACA Avignon), I contributed to the development of the R package landsepi(Landscape Epidemiology and Evolution), which can be downloaded following this link [https://cran.r-project.org/package=landsepi]. This package allows the simulation of a panel of resistance deployment strategies against plant pathogens, especially:
rusts of wheat, caused by fungi of the genus Puccinia
downy mildew of grapevine, caused by the oomycota Plasmopara viticola
black sigatoka of banana, caused by the fungus Pseudocercospora fijiensis
cucumber mosaic virus (CMV) and potato virus Y (PVY) on pepper
Diverse strategies can be compared with respect to their epidemiological (plant health), evolutionary (resistance durability) and economic (cost efficiency) performance. The package also includes a shiny web interface for pedagogical purpose.
Resistance deployment strategies. A durable management of plant resistance includes the choice of the resistance source, and its wise spatiotemporal deployment at different nested scales, with the aim of mitigating pathogen evolution towards resistance breakdown. Adapté from Rimbaud L., Fabre F., Papaïx J., Moury B., Lannou C., Barrett L. and Thrall P. (2021). Models of plant resistance deployment. Annu. Rev. Phytopathol. 59:125-152.
Example of simulation of an epidemic with landsepi. Right panel: colonization of a pathogen in an agricultural landscape composed of a susceptible cultivar (fields initially infected) and two resistant cultivar (hatched fields). Left panel: dynamics of disease prevalence, with time of resistance breakdown (blue vertical lines). Adapté de de Rimbaud L, Papaïx J, Rey JF, Barrett LG and Thrall PH (2018). Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens. PLoS Comput. Biol. 14:e1006067.
SEIR architecture of the model. Healthy hosts can be infected by propagules. Following a latent period, infectious hosts produce new propagules which may mutate and disperse across the landscape. At the end of the infectious period, infected hosts become epidemiologically inactive. A web pedagogical interface of SEIR models is available [https://loup.shinyapps.io/loup_demo_shiny/]. Adapté de Rimbaud L, Papaïx J, Barrett LG, Burdon JJ and Thrall PH (2018). Mosaics, mixtures, rotations or pyramiding: What is the optimal strategy to deploy major gene resistance? Evol. Appl. 11(10):1791-1810.
2. 2. Understanding plant-virus-vector interactions via experiments
A fine understanding of the biology of interaction between pathogens, hosts and vectors is necessary to identify relevant control strategies. It is crucial to identify the key factors of epidemic spread. It is the objective of my researches on the cucumber mosaic virus (Bromoviridae, Cucumovirus), which recently emerged on Espelette pepper crops, causing severe damages. based on field sampling, laboratory diagnostic tools (using serological and molecular methods) and statistical analyses, I explore the different dissemination pathways of CMV in the Basque Country (Southwestern France).
CMV impacts yield, size, form, colour and taste of Espelette pepper.
From Verdin E. & Rimbaud L. (2024). Biologie végétale : des cultures sous pression virale. La Recherche, Dossier « Les Virus », n°576:49-51 and adapted from Lepage E., Szadkowski M., Girardot G., Pascal M., Dumeaux P., Papaïx J., Moury B. and Rimbaud L. (2025). Cucumber mosaic virus degrades pepper fruit production, marketability and organoleptic quality, with isolate-specific effects. Plant Pathol. 74:1244-1255
Cucumber mosaic virus is a tri-partite virus composed of 3 particles, each of them containing a positive single stranded RNA. It infects a very wide range of host plants, among which pepper. It is transmitted by the seed of some host plants, and by more than 80 species of aphids in the non-persistant mode.
TRANSFER OF KNOWLEDGE
1. Teaching
I teach yearly:
on these three main themes:
bases of phytopathology
bases of biostatistics
mathematical approaches to assess resistance deployment strategies ;
in these organisms::
Avignon Université : Sciences et Durabilité des Productions Végétales (SDPV, M1 & M2), Ingénierie des Filières végétales (IFV, M1 & M2)
Montpellier SupAgro : Protection des Plantes et Environnement (PPE, M2)
2. PhD supervision
2026 – 2029 : Alban Fesquet (INRAE, directeur) : Identification, par la modélisation, de stratégies de déploiement de la résistance variétale et des traitements phytosanitaires pour une gestion réactive, efficace, durable et rentable des maladies.
2022 - 2025 : Elise Lepage (AgroParisTech IPEF, co-directeur) : Emergences à l’interface agro-écologique : le rôle des réservoirs naturels sur les dynamiques épidémique et évolutive des agents pathogènes.
3. Post-doctorate supersivion
2021 - 2024 : Marta Zaffaroni (INRAE, co-encadrant) : Stratégies de diversification des gènes de résistance pour gérer les agents pathogènes dans les agro-écosystèmes : approches théoriques et application aux vignobles français.
4. Internship supervision
2026 : Guillaume Visomblain (M2 Institut Agro Rennes, encadrant principal) : Evaluation de la compétence de 5 adventices pour constituer un réservoir viral du CMV.
2024 :
Alice Conilh (L2 Avignon Univ., 2024, encadrant principal) : Evaluation des différentes voies de transmission du CMV.
Lucas Gonzalez (L3 Avignon Univ., 2024, encadrant principal) : Evaluation des différentes voies de transmission du CMV.
2023 : Manon Couty (M2 INSA Lyon, co-encadrant) : Modélisation spatio-temporelle des épidémies : comment diversifier les paysages agricoles ?
2022 : Ulysse Caromel (L3 Avignon Univ., encadrant principal) : Analyse d’image pour mesurer la résistance du piment au PVY.
2021 :
Elise Lepage (M2 AgroParisTech, encadrant principal) : Itinéraire d’un virus fluorescent : Etudier la résistance du piment au Potato virus Y.
Pauline Bouvet (2nde Cité Scolaire du Diois, encadrant principal): Stage de découverte en milieu professionnel.
2020:
Pierre Mustin (M2 Agrocampus Ouest, encadrant principal) : Evaluation de la résistance des plantes à la transmission des virus.
Clarisse Vincent (M2 Montpelier SupAgro, co-encadrant) : Assurer la durabilité des résistances à la cercosporiose noire de nouvelles variétés de bananiers.
2019 : Jean-Loup Gaussen (M2 Avignon Univ., co-encadrant) : Développement d’outils spatiaux pour le package R landsepi.
2014:Samuel Marchat (M1 Univ. de Montpellier, co-encadrant) : Développement d’un protocole de détection précoce du virus de la sharka dans des Prunus.
By browsing our site you accept the installation and use cookies on your computer.
Know more
Our use of cookies
Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.
To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.
You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.
In the case of third-party advertising cookies, you can also visit the following site: https://www.youronlinechoices.com/fr/controler-ses-cookies/, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.
It is also possible to block certain third-party cookies directly via publishers:
Cookie type
Means of blocking
Analytical and performance cookies
Realytics Google Analytics Spoteffects Optimizely
Targeted advertising cookies
DoubleClick Mediarithmics
The following types of cookies may be used on our websites:
Mandatory cookies
Functional cookies
Social media and advertising cookies
These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.
These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.
These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.
Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times). These cookies are deleted at the end of the browsing session (when you log off or close your browser window)
Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months
Our EZPublish content management system (CMS) does not use this type of cookie.
For more information about the cookies we use, contact INRAE’s Data Protection Officer by email at cil-dpo@inra.fr or by post at:
INRAE 24, chemin de Borde Rouge –Auzeville – CS52627 31326 Castanet Tolosan cedex - France