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3. Optimal and sustainable management of a soilborne banana pest

Author

Chedjou, Israël Tankam, Grognard, Frédéric, Tewa, Jean Jules, and Touzeau, Suzanne

Subjects
Mathematics - Optimization and Control, Quantitative Biology - Populations and Evolution
Abstract

In this paper we propose an eco-friendly optimization of banana or plantain yield by the control of the pest burrowing nematode \textit{Radopholus similis}. This control relies on fallow deployment, with greater respect for the environment than chemical methods. The optimization is based on a multi-seasonal model in which fallow periods follow cropping seasons. The aim is to find the best way, in terms of profit, to allocate the durations of fallow periods between the cropping seasons, over a fixed time horizon spanning several seasons. The existence of an optimal allocation is proven and an adaptive random search algorithm is proposed to solve the optimization problem. For a relatively long time horizon, deploying one season less than the maximum possible number of cropping seasons allows to increase the fallow period durations and results in a better multi-seasonal profit. For regular fallow durations, the profit is lower than the optimal solution, but the final soil infestation is also lower., Comment: Manuscript submitted to Applied Mathematics and Computation (Jun 13, 2020), 21 pages with 13 figures

Published
2020
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10. Impulsive modelling of rust dynamics and predator releases

Author

Djuikem, Clotilde, Grognard, Frédéric, Touzeau, Suzanne, Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Côte d'Azur (UCA), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), and EPITAG

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Floquet theory, seasonality, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], coffee leaf rust, hybrid model, stability, crop protection, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract

International audience; Fungal diseases cause serious damages in crop worldwide. In particular, coffee leaf rust (CLR), caused by fungus Hemileia vastatrix attacks coffee leaves and reduces coffee yield. Its control mainly relies on cultural practices, fungicides, resistant cultivars and biocontrol using hyperparasites. Fungicides are widely used, but have harmful ecological impact an important costs; the other methods need careful analysis for their deployment to be successful on the long term. This work presents a multi-seasonal model of the CLR development in the coffee plantation with continuous dynamics during the rainy season and a discrete event to represent the simpler dynamics during the dry season. Biological control using predators through one or more discrete introduction events over the year is then added. Analytical and semi-numerical studies are performed to identify how much and how frequently predators need to be introduced through the definition of a threshold value, as a function of various parameters. We show that the best strategy to efficiently control the disease depends on the predator mortality: low mortality predators need to be released only once a year, while high mortality predators should be released more frequently to ensure their persistence in the plantation. This work hence provides qualitative and quantitative bases for the deployment of predator-based biocontrol, a promising alternative to fungicides for rust control.

Published
2023

11. Optimal impulsive control of coffee berry borers in a berry age-structured epidemiological model

Author

Fotso Fotso, Yves, Touzeau, Suzanne, Tsanou, Berge, Grognard, Frédéric, Bowong, Samuel, Faculté des Sciences - Université de Dschang [Cameroun], Université de Dschang, Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO), Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA)-Sorbonne Université (SU)-Institut de Recherche pour le Développement (IRD [France-Nord]), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Côte d'Azur (UCA), Faculté des Sciences [Douala], Université de Douala, EPITAG, Fotso Fotso, Yves, and Dpt of Mathematics and Computer Science [Douala]

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, Plant-pest interactions, Integrated pest management, [MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC], [SDV.EE.IEO] Life Sciences [q-bio]/Ecology, environment/Symbiosis, [SDV.BA.ZI]Life Sciences [q-bio]/Animal biology/Invertebrate Zoology, Impulsive control, [SDV.BA.ZI] Life Sciences [q-bio]/Animal biology/Invertebrate Zoology, Maximum principle, Numerical simulations, Hypothenemus hampei, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], PDE dynamical model, [MATH.MATH-AP] Mathematics [math]/Analysis of PDEs [math.AP], [MATH]Mathematics [math], Impulsive control theory, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis, Plant-pest interactions PDE dynamical model Impulsive control Maximum principle Numerical simulations Hypothenemus hampei
Abstract

International audience; The coffee berry borer (CBB) Hypothenemus hampei (Coleoptera: Scolytidae) is the most important insect pest affecting coffee production worldwide and generating huge economic losses. As most of its life cycle occurs inside the coffee berry, its control is extremely difficult. To tackle this issue, we solve an optimal control problem based on a berry age-structured dynamical model that describes the infestation dynamics of coffee berries by CBB during a cropping season. This problem consists in applying a bio-insecticide at discrete times in order to maximise the economic profit of healthy coffee berries while minimising the CBB population for the next cropping season. We derive analytically the first-order necessary optimality conditions of the control problem. Numerical simulations are provided to illustrate the effectiveness of the optimal control strategy.

Published
2023

12. Self-financing model for cabbage crops

Author

Kambeu, Aurélien, Touzeau, Suzanne, Grognard, Frédéric, Tsanou, Berge, Faculté des Sciences - Université de Dschang [Cameroun], Université de Dschang, Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), Université Côte d'Azur (UCA), University of Pretoria [South Africa], and EPITAG

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, pest management, delay model, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], investment, mathematical analysis, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract

International audience; One of the biggest challenges for the farmer is to increase the incomes generated by his farm. This is not always easy because of pests and the scarcity of nutrients in the soil. In this work, we model, analyze and simulate a self-financing nonlinear mathematical model for cabbage crops. The model takes into account the young biomass, the adult biomass, the main cabbage pest (Plutella Xylostella) in its most devastating developmental state (larvae), the concentration of biopesticides in the culture, the external efforts and the incomes generated by the crop. We assume that the budget is allocated for purchasing new plants, biopesticides, and increasing the growth rate of crops (external efforts). This budget increases only through the sale of adult biomass. We study several variants of the main model. In these different cases, the condition in which the budget must be spent to keep the system alive is obtained. The model analysis reveals that prophylaxis can eradicate larvae in a cabbage crop. In addition, the impact of the delay in the supply of fertilizers and biopesticides to the culture is studied.

Published
2023

13. Sterile Insect Technique for crop protection: accounting for residual fertility

Author

Courtois, Marine, Rastello, Kévan, Grognard, Frédéric, Mailleret, Ludovic, Touzeau, Suzanne, van Oudenhove, Louise, Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), and Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST)

Subjects
[SDV]Life Sciences [q-bio], [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS]
Abstract

International audience

Published
2023

14. How does residual fertility impact the effectiveness of the sterile insect techniquein controlling Ceratitis capitata

Author

Courtois, Marine, Rastello, Kévan, Grognard, Frédéric, Mailleret, Ludovic, Touzeau, Suzanne, van Oudenhove, Louise, Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), and Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST)

Subjects
[SDV]Life Sciences [q-bio]
Abstract

International audience

Published
2023

15. A sex- and stage-structured population dynamics model for pest control using the sterile insect technique

Author

Kounoudji, Crésus, Touzeau, Suzanne, Grognard, Frédéric, van Oudenhove, Louise, Mailleret, Ludovic, Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), and Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST)

Subjects
[SDV]Life Sciences [q-bio]
Published
2023

18. Ecophysiological modelling of plant-nematode interactions to understand plant tolerance

Author

Penlap Tamagoua, Joseph, Touzeau, Suzanne, Grognard, Frédéric, Baldazzi, Valentina, Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria), Biological control of artificial ecosystems (BIOCORE), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), and Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST)

Subjects
[MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy
Abstract

International audience

Published
2023

20. Bifurcation analysis in a coffee leaf rust epidemiological model

Author

Djuikem, Clotilde, Grognard, Frédéric, Touzeau, Suzanne, Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), Université Côte d'Azur (UCA), Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), and EPITAG

Subjects
[SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy
Abstract

International audience; Coffee is an important cash crop cultivated in the tropics, which sustains the livelihood ofnot less than 125 million people worldwide. However, coffee plantations are subject tovarious diseases, among which coffee leaf rust (CLR), caused by fungus Hemileia vastatrix,which infects coffee leaves and can severely reduce coffee berry production.We developed a deterministic ODE model which describes the interaction between CLRand coffee branches in a coffee plantation. It is based on the classical SEIR epidemiologicalmodel, with an extra state variable for spores released by infected branches, which in turninfect susceptible branches. Moreover, coffee branches are subdivided into young andmature branches, the latter producing coffee berries. We computed the basic reproductionnumber R0, which classically determines the stability of the disease-free equilibrium(DFE), and studied the bifurcation around R0 = 1 using Castillo-Chavez and Song’stheorem.

Published
2022

21. Improving sustainable crop protection using population genetics concepts

Author

Saubin, Méline, primary, Louet, Clémentine, additional, Bousset, Lydia, additional, Fabre, Frédéric, additional, Frey, Pascal, additional, Fudal, Isabelle, additional, Grognard, Frédéric, additional, Hamelin, Frédéric, additional, Mailleret, Ludovic, additional, Stoeckel, Solenn, additional, Touzeau, Suzanne, additional, Petre, Benjamin, additional, and Halkett, Fabien, additional

Published
2022
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22. Improving sustainable crop protection using population genetics concepts.

Author

Saubin, Méline, Louet, Clémentine, Bousset, Lydia, Fabre, Frédéric, Frey, Pascal, Fudal, Isabelle, Grognard, Frédéric, Hamelin, Frédéric, Mailleret, Ludovic, Stoeckel, Solenn, Touzeau, Suzanne, Petre, Benjamin, and Halkett, Fabien

Subjects
POPULATION genetics, PLANT breeding, PLANT-pathogen relationships, POPULATION dynamics, PHYTOPATHOGENIC microorganisms
Abstract

Growing genetically resistant plants allows pathogen populations to be controlled and reduces the use of pesticides. However, pathogens can quickly overcome such resistance. In this context, how can we achieve sustainable crop protection? This crucial question has remained largely unanswered despite decades of intense debate and research effort. In this study, we used a bibliographic analysis to show that the research field of resistance durability has evolved into three subfields: (1) "plant breeding" (generating new genetic material), (2) "molecular interactions" (exploring the molecular dialogue governing plant–pathogen interactions) and (3) "epidemiology and evolution" (explaining and forecasting of pathogen population dynamics resulting from selection pressure[s] exerted by resistant plants). We argue that this triple split of the field impedes integrated research progress and ultimately compromises the sustainable management of genetic resistance. After identifying a gap among the three subfields, we argue that the theoretical framework of population genetics could bridge this gap. Indeed, population genetics formally explains the evolution of all heritable traits, and allows genetic changes to be tracked along with variation in population dynamics. This provides an integrated view of pathogen adaptation, in particular via evolutionary–epidemiological feedbacks. In this Opinion Note, we detail examples illustrating how such a framework can better inform best practices for developing and managing genetically resistant cultivars. [ABSTRACT FROM AUTHOR]

Published
2023
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23. A demo-genetic model of root-knot nematode dynamics with applications to optimal deployment of plant resistance

Author

Nilusmas, Samuel, Mercat, Mathilde, Perrot, Thomas, Touzeau, Suzanne, Calcagno, Vincent, Djian‐caporalino, Caroline, Castagnone-Sereno, Philippe, Mailleret, Ludovic, Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), and Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST)

Subjects
[SDV]Life Sciences [q-bio]
Published
2022

24. A multi-seasonal model of plant-pest interactions: the coffee berry borer

Author

Grognard, Frédéric, Bowong, Samuel, Fotso Fotso, Yves, Touzeau, Suzanne, Tsanou, Berge, Gouzé, Jean-Luc, Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Côte d'Azur (UCA), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), Dpt of Mathematics and Computer Science [Douala], Université de Douala, Unité de modélisation mathématique et informatique des systèmes complexes [Bondy] (UMMISCO), Université de Yaoundé I-Institut de la francophonie pour l'informatique-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Gaston Bergé (Saint-Louis, Sénégal)-Université Cadi Ayyad [Marrakech] (UCA)-Sorbonne Université (SU)-Institut de Recherche pour le Développement (IRD [France-Nord]), Faculté des Sciences - Université de Dschang [Cameroun], Université de Dschang, Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Department of Mathematics and Applied Mathematics [Pretoria], University of Pretoria [South Africa], and EPITAG

Subjects
[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, [MATH.MATH-DS] Mathematics [math]/Dynamical Systems [math.DS], [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering
Abstract

International audience; The coffee berry borer (CBB), Hypothenemus hampei (Coleoptera: Scolytidae) is the most devastating insect pest of coffee throughout the world, causing a lot of economic damage in all regions where commercial coffee is grown. In this work, we formulate and study a model describing multi-seasonal infestation dynamics of coffee berries by CBB in a rainy/dry season regime, with the aim of identifying how sanitation measures can be applied to ensure CBB eradication. We employ a semi-discrete formalism to describe these dynamics as the epidemiological dynamics are best represented by a continuous model in ODE, while the remaining dynamics, that connect one season to the next, are better or more simply described by discrete-time events: berry harvest and plantation sanitation. During the rainy season, the infestation dynamics of coffee berries by CBB are described as proposed in Fotso Fotso et al (2021) with the coffee berry production rate depending on time. During the dry season, the dynamics are very similar , except that no berry growth takes place and mortality rates are higher as the environment is less favorable. The model is then completed by the discrete events that take place at the end of the rainy season and at the end of the dry season, that correspond to harvesting and plantation cleaning respectively. Based on that model, we first obtain a periodic CBB-free solution, that will be the desirable behaviour of the system. Linearising the dynamics around that solution and applying Floquet theory, we obtain stability conditions for this solution, that give threshold values for the harvesting and cleaning parameters below which asymptotic stability is ensured, hence CBB eradication. Note however that, even with perfect harvesting and cleaning, CBB could still persist through the survival of the colonising forms over the dry season.Finally, with perfect harvesting of the healthy berries at the end of the cropping season, we obtain conditions on harvesting and cleaning of the infested berries, that ensures CBB eradication at the minimum cost, for two versions of the cost.

Published
2022

25. Sterile insect technique against the medfly: modelling, calibration and effect of residual fertility

Author

Courtois, Marine, Rastello, Kévan, Grognard, Frédéric, Mailleret, Ludovic, Touzeau, Suzanne, van Oudenhove, Louise, Gouzé, Jean-Luc, Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Ecophyto Ceratis

Subjects
[SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], [SDV.EE.ECO] Life Sciences [q-bio]/Ecology, environment/Ecosystems, [MATH.MATH-DS] Mathematics [math]/Dynamical Systems [math.DS], [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering, [SDV.BV.PEP] Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy
Abstract

International audience; This work takes place in the context of the experimental introduction of sterile males to fight the Mediterranean fruit fly Ceratitis capitata in orchard landscapes in Corsica (France). We first considered the natural population dynamics of the fly, by building a three-dimensional model structured in larva, male and female stages. The model wascalibrated in part by compiling data from literature, and in part by ensuring that the predicted dynamics were comparable to those observed in the field. Competition between females was shown to be the deciding factor for the extent of the fly infestation. Further, a sensitivity analysis performed on larval density at the end of a cropping season showed it is most influenced by the per capita oviposition rate and the larval mortality rate. These two biological processes are thus important to control the C. capitata population. Stemming from that model, we introduced a sterile males - wild males - females model to represent the dynamics resulting from sterile males introductions. We first consideredreleases of perfectly sterile insects, but also two different situations accounting for residual fertility of the “sterile" males. We showed how residual fertility could destabilize the pest-free equilibrium, and gave a condition to be satisfied to ensure that the pest-free equilibrium is the only equilibrium, and that it is stable. The developments were carriedout from qualitative properties on mating probability and competition between females, so that they hold true for a wide range of functional forms and situations. Generalizing the results brought forward in [1], we showed that, when residual fertility is below a threshold value, SIT could be made efficient by overflooding the landscape with sterilemales. We additionaly proved that SIT could still be efficient beyond that threshold, as long as releases are not too massive, since it would result in also massively releasing fertile males.References[1] M.S. Aronna and Y. Dumont, On Nonlinear Pest/Vector Control via the Sterile InsectTechnique: Impact of Residual Fertility, Bull Math Biol, 82(110), 2020.

Published
2022

27. Improving the design of sustainable crop protection strategies thanks to population genetics concepts

Author

Saubin, Méline, Louet, Clémentine, Bousset, Lydia, Fabre, Frédéric, Fudal, Isabelle, Grognard, Frédéric, Mailleret, Ludovic, Stoeckel, Solenn, Touzeau, Suzanne, Petre, Benjamin, Halkett, Fabien, Interactions Arbres-Microorganismes (IAM), Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, 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)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Santé et agroécologie du vignoble (UMR SAVE), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), BIOlogie et GEstion des Risques en agriculture (BIOGER), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut Sophia Agrobiotech (ISA), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Recherche Agronomique (INRA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-INSTITUT AGRO Agrocampus Ouest, 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), Université Nice Sophia Antipolis (1965 - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA)

Subjects
[SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], [MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM], food and beverages, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

Cropping genetically resistant plants allows to control pathogen populations while substantially reducing chemical inputs. However, resistances are often quickly defeated by pathogens. In this context, how can sustainable crop protection be achieved? This question has shaped the debate about the durability of genetic resistances in agriculture for decades, and, despite active research efforts, has not been satisfactorily answered yet. Here we demonstrate from a bibliography analysis that the research field of resistance durability evolved into two non-overlapping directions: (i) the subfield of 'epidemiology and evolution', which aims to forecast and explain pathogen population dynamics; (ii) the subfield of 'molecular interactions', which studies the molecular processes involved in the overcoming of resistance and in the dialogue between plants and pathogens. After reviewing briefly these two subfields and the gap between the corresponding research communities, we propose strategies to merge these approaches into one by using the concepts of population genetics. Ultimately, such new eco-evolutionary studies could be used to determine the best strategy for the deployment of genetically resistant cultivars by integrating, from gene to landscape, all relevant and contextual biological knowledge into sound theoretical models.

Published
2021

28. Impulsive model and hyperparasite-based biocontrol of coffee leaf rust propagation

Author

Djuikem, Clotilde, Grognard, Frédéric, Touzeau, Suzanne, Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Côte d'Azur (UCA), Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Gaston Bergé Sénégal-Université d'Antananarivo-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université Badji Mokhtar - Annaba [Annaba] (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Yaoundé I, Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), EPITAG, Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), and Université Nice Sophia Antipolis (1965 - 2019) (UNS)

Subjects
[SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS]
Abstract

International audience; Coffee is one of the most widely consumed beverages in the world. Its cultivation is an important factor of social and economic stability. However, its production is affected by several diseases. Coffee leaf rust (CLR), a cryptogamic disease caused by the fungus Hemileia vastatrix, is the most serious coffee leaf disease known to date. It causes damages that induce severe yield losses. Its control mainly relies on good cultural practices, fungicides, resistant cultivars and biocontrol using hyperparasites (such as the fungus Lecanicillium lecanii). Fungicides are widely used, but have a harmful ecological impact. Coffee being a perennial plant, planting resistant cultivars implies to renew the plantation, which is very costly. Hyperparasites could hence be a good alternative, but careful analysis is needed for their deployment to be successful in the long term.Our goal is to understand and control the propagation of CLR, deploying hyperparasites. Depending on the country and climate, coffee trees produce berries throughout the year or seasonally. We consider the latter case, with a periodic coffee harvest at the end of the rainy season and limited growth during the dry season. Therefore, we developed an impulsive model to describe CLR propagation in the coffee plantation during the rainy season and its survival between rainy seasons. Floquet theory is used to prove the stability of the periodic disease free solution and numerical simulations are performed to illustrate theoretical results. To implement biological control, new discontinuities are introduced in the model to represent the release of hyperparasites. Floquet theory and numerical simulations are then combined to determine parameter values for which the periodic disease free solution is stable and which correspond to successful biocontrol deployment.

Published
2021

29. When and how to fallow: first steps towards banana crop yield improvement through optimal and sustainable control of a soilborne pest

Author

Tankam Chedjou, Israël, Grognard, Frédéric, Tewa, Jean-Jules, Touzeau, Suzanne, Département de Mathématiques Université de Yaoundé 1, Université de Yaoundé I [Yaoundé], Laboratoire International de Recherche en Informatique et Mathématiques Appliquées (LIRIMA), Université de Yaoundé I [Yaoundé]-Université Badji Mokhtar - Annaba [Annaba] (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Côte d'Azur (UCA), Ecole Nationale Supérieure Polytechnique [Yaoundé] (ENSP), Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), EPITAG, Département de Mathématiques Université de Yaoundé 1 = Department of Mathematics [Yaoundé, Cameroon], Université de Yaoundé I, Université de Yaoundé I-Université Badji Mokhtar Annaba (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), Ecole Nationale Supérieure Polytechnique de Yaoundé (ENSPY), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Université de Yaoundé I-Université Badji Mokhtar - Annaba [Annaba] (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université d'Antananarivo-Université Gaston Bergé Sénégal-Centre National de la Recherche Scientifique et Technologique (CNRST), and Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Gaston Bergé Sénégal-Université d'Antananarivo-Université Joseph Ki-Zerbo [Ouagadougou] (UJZK)-Université Badji Mokhtar - Annaba [Annaba] (UBMA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Yaoundé I

Subjects
2. Zero hunger, pest management, semi-discrete model, epidemiological model, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], burrowing nematode, west management, yield optimization
Abstract

International audience; The main hindrance to banana crop yields is the burrowing nematode Radopholus similis, a microscopic worm that feeds and develops in plant roots. R. similis is an obligatory parasite that fortunately resists badly in the absence of its host. Hence, the deployment of fallows is an efficient way to keep its populations low enough in the soil to have good economic returns on banana bunches. The banana plant is a perennial plant which reproduces itself by budding from its roots, but after a fallow period, a nematode-free sucker needs to be planted to provide for the next cropping season. Fallow is a recommended cropping practice to reduce nematode infestation, but it comes at the cost of nematode-free suckers. Moreover, fallows reduce the time devoted to growing bananas on a given time horizon and may reduce the total yield. A trade-off should then be found between fallow deployment to reduce pest infestation and economic returns. The questions that emerge are when to leave room for the natural reproduction of the banana plant, and when to deploy the fallow? How long to deploy the fallow if applicable? On the basis of mathematical models this paper attempts to answer the questions.

Published
2021
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31. A thermal trade-off between viral production and degradation drives phytoplankton-virus population dynamics

Author

DEMORY, David, WEITZ, Joshua, BAUDOUX, A-C, TOUZEAU, Suzanne, SIMON, Natalie, RABOUILLE, Sophie, SCIANDRA, Antoine, BERNARD, Olivier, Georgia Institute of Technology [Atlanta], Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), School of Mathematics - Georgia Institute of Technology, Adaptation et diversité en milieu marin (ADMM), Institut national des sciences de l'Univers (INSU - CNRS)-Station biologique de Roscoff (SBR), Institut Sophia Agrobiotech (ISA), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Côte d'Azur (UCA), Laboratoire d'Océanographie Microbienne (LOMIC), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Banyuls (OOB), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Simons Foundation (SCOPE award grant no. 329108). 721231, Inria Challenge OceanIA (Artificial Intelligence and Modeling for Understanding Oceans and Climate Change), ANR-12-BSV7-0006,REVIREC,Résistance aux prasinovirus analysée par la transcriptomique et la recombinaison(2012), Adaptation et diversité en milieu marin (AD2M), Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Nice Sophia Antipolis (... - 2019) (UNS), Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Banyuls (OOB), and Simons Foundation (SCOPE award grant no. 329108).

Subjects
ocean warming, modelling, viruses, [SDV]Life Sciences [q-bio], fungi, phytoplankton, temperature, virus, trade-off
Abstract

International audience; Marine viruses interact with microbial hosts in dynamic environments shaped by variation in abiotic factors, including temperature. However, the impacts of temperature on viral infection of phytoplankton are not well understood. Here we coupled mathematical modelling with experiments to explore the effect of temperature on virus-phytoplankton interactions. Our model shows the negative consequences of high temperatures on infection and suggests a temperature-dependent threshold between viral production and degradation. Modelling long-term dynamics in environments with different average temperatures revealed the potential for long-term host-virus coexistence, epidemic free or habitat loss states. We generalised our model to variation in global sea surface temperatures corresponding to present and future seas and show that climate change may differentially influence virus-host dynamics depending on the virus-host pair. Temperature-dependent changes in the infectivity of virus particles may lead to shifts in virus-host habitats in warmer oceans, analogous to projected changes in the habitats of macro-, microorganisms and pathogens.

Published
2021
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38. Additional file 5 of How to prevent viremia rebound? Evidence from a PRRSv data-supported model of immune response

Author

Go, Natacha, Touzeau, Suzanne, Zeenath Islam, Belloc, Catherine, and Doeschl-Wilson, Andrea

Abstract

Model description & Sensitivity analyses. The file provides a complete description of the dynamic model representing the within-host dynamics induced by a primary PRRSv infection in a naive pig. It specifies the modelling assumptions and includes all model equations. The file also describes the global sensitivity analyses performed to assess the impact of model parameters on the viral dynamics. Corresponding aims, methods and results are presented. (PDF 710 kb)

Published
2019
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39. An agricultural control of Radopholus similis in banana plantations

Author

Tankam Chedjou, Israël, Touzeau, Suzanne, Grognard, Frédéric, Mailleret, Ludovic, Tewa, Jean-Jules, Université de Yaoundé, Biological control of artificial ecosystems (BIOCORE), Laboratoire d'océanographie de Villefranche (LOV), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-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), Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), and COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
integrated pest management, plant-parasitic nematode, optimisation, [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, epidemiological model, tropical agriculture
Abstract

Radopholus similis is the major parasitic nematode of banana and plantain plants worldwide. R. Similis feeds on the root tissues and causes damages going from simple root lesions, reducing the crop yield, to the fall of seedlings. Hence, R. similis is one of the most regulated plant pests. Its control mainly relies on toxic nematicides, but with limited efficiency. Our global aim is to design more efficient and sustainable control strategies, including alternative methods to nematicides. Our approach is based on a hybrid model describing the plant-nematode interactions over several cropping seasons. During the inter-season, in the absence of host, the pest population undergoes a rapid decay. A longer inter-season duration reduces the pest population the following season, which is correlated with the seasonal crop yield. However, longer inter-season durations also decrease the number of cropping seasons during a fixed time horizon, and potentially the multi-seasonal yield. An optimisation problem is therefore formulated to determine the inter-season duration that maximises the multi-seasonal yield. Two cases are considered: a fixed or a variable inter-season duration. The existence of an optimal solution is proven and its location is computed. Numerical simulations are provided to illustrate our results.

Published
2018

40. Evolution of populations of Leptosphaeria maculans, a fungal pathogen of oilseed rape, under resistance selection pressure: insights from two decades of surveys in France

Author

Balesdent, Marie-Helene, Plissonneau, Clémence, Carpentier, Florence, Coudard, Laurent, Touzeau, Suzanne, Leflon, Martine, Ermel, Magali, Delourme, Régine, Le Meur, Loïc, Rouxel, Thierry, BIOlogie et GEstion des Risques en agriculture (BIOGER), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Institut Sophia Agrobiotech (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Biological control of artificial ecosystems (BIOCORE), Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-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), Terres Inovia, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, InVivo AgroSolutions (IAS), Groupe Roullier. FRA., Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, 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
[SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology
Abstract

National audience; Leptosphaeria maculans is responsible for the stem canker, a major disease of oilseed rape (Brassica napus). Specific resistance genes are used in commercial varieties to control the disease. The effectiveness of a given resistance gene is a function of the frequency of the corresponding avirulent allele in field populations of the pathogen. After the release of the oilseed rape resistance gene Rlm1 in the 1990’s in France, a very rapid increase in the frequency of isolates virulent towards this gene was observed [1]. More recently, a new resistance gene, Rlm7, was introduced into commercial hybrid varieties, at a time when most (>99.5%) of the L. maculans isolates possessed the corresponding avirulent allele AvrLm7 [2]. Since 2000, the frequency of isolates virulent against Rlm7 has been monitored in populations of L. maculans in either experimental fields with increased selection pressure, or at a national scale in more standard agronomic situations. While a rapid increase in frequency of virulent isolates was observed in an experimental field at Grignon that had minimum tillage and continuous oilseed rape cropping (36% of isolates virulent after 3 years; [3]), the breakdown of the Rlm7 gene appeared much less rapid than that observed previously for Rlm1 at the national level in France (less than 20% of isolates virulent after 10 years of widespread use of Rlm7. Among the possible reasons for this unexpected durability of Rlm7, the role of the negative interaction between AvrLm7 and AvrLm3 [4] was explored here. A detailed knowledge of molecular mechanisms responsible for virulence against Rlm3 and Rlm7 was obtained and suggested that pyramiding of the two resistance genes could have a negative impact on Rlm7 durability while the use of both resistance genes in different varieties could have slowed down the breakdown. These population and molecular information are currently used in an epidemiological model to test our hypotheses. References [1] Rouxel T, et al (2003). Eur J Plant Pathol 109:871-881. [2] Balesdent MH, et al (2006). Eur J Plant Pathol 114:53-65. [3] Daverdin G, et al (2012).. PLoS Pathog 8: e1003020. [4] Plissonneau C, et al (2016) New Phytol 209:1613-1624

Published
2018

41. How to prevent viremia rebound? Evidence from a PRRSv data-supported model of immune response

Author

Go, Natacha, Touzeau, Suzanne, Islam, Zeenath, Belloc, Catherine, Doeschl-Wilson, Andrea, Biologie, Epidémiologie et analyse de risque en Santé Animale (BIOEPAR), Institut National de la Recherche Agronomique (INRA), Biological control of artificial ecosystems (BIOCORE), 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)-Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), The Roslin Institute, Institut Sophia Agrobiotech (ISA), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Recherche Agronomique (INRA), ANR-10-BINF-07 (MIHMES), ANR-10-BINF-0007,MIHMES,Modélisation multi-échelle, de l'Intra-Hôte animal à la Métapopulation, des mécanismes de propagation d'agents(2010), European Project: 633184,H2020,H2020-SFS-2014-2,SAPHIR(2015), Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), ANR: 10-BINF-0007,MIHMES,Modélisation multi-échelle, de l'Intra-Hôte animal à la Métapopulation, des mécanismes de propagation d'agents(2010), Institut National de la Recherche Agronomique (INRA)-École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS), Biotechnology and Biological Sciences Research Council (BBSRC), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV.BA.MVSA]Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health, Swine, Models, Immunological, Apoptosis, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Immunological model, ABC-like optimisation method, lcsh:Biology (General), [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, PRRSv, [SDV.IMM]Life Sciences [q-bio]/Immunology, Animals, Porcine respiratory and reproductive syndrome virus, Viremia, Rebounder viremia profile, lcsh:QH301-705.5, Research Article
Abstract

Background Understanding what determines the between-host variability in infection dynamics is a key issue to better control the infection spread. In particular, pathogen clearance is desirable over rebounds for the health of the infected individual and its contact group. In this context, the Porcine Respiratory and Reproductive Syndrome virus (PRRSv) is of particular interest. Numerous studies have shown that pigs similarly infected with this highly ubiquitous virus elicit diverse response profiles. Whilst some manage to clear the virus within a few weeks, others experience prolonged infection with a rebound. Despite much speculation, the underlying mechanisms responsible for this undesirable rebound phenomenon remain unclear. Results We aimed at identifying immune mechanisms that can reproduce and explain the rebound patterns observed in PRRSv infection using a mathematical modelling approach of the within-host dynamics. As diverse mechanisms were found to influence PRRSv infection, we established a model that details the major mechanisms and their regulations at the between-cell scale. We developed an ABC-like optimisation method to fit our model to an extensive set of experimental data, consisting of non-rebounder and rebounder viremia profiles. We compared, between both profiles, the estimated parameter values, the resulting immune dynamics and the efficacies of the underlying immune mechanisms. Exploring the influence of these mechanisms, we showed that rebound was promoted by high apoptosis, high cell infection and low cytolysis by Cytotoxic T Lymphocytes, while increasing neutralisation was very efficient to prevent rebounds. Conclusions Our paper provides an original model of the immune response and an appropriate systematic fitting method, whose interest extends beyond PRRS infection. It gives the first mechanistic explanation for emergence of rebounds during PRRSv infection. Moreover, results suggest that vaccines or genetic selection promoting strong neutralising and cytolytic responses, ideally associated with low apoptotic activity and cell permissiveness, would prevent rebound. Electronic supplementary material The online version of this article (10.1186/s12918-018-0666-7) contains supplementary material, which is available to authorized users.

Published
2018
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42. Principal process analysis of biological models

Author

Touzeau, Suzanne, Ropers, Delphine, Gouzé, Jean-Luc, and Casagranda, Stefano

Subjects
Dynamical systems, Biological networks, Process analysis, Model reduction, Parameter sensitivity analysis, Circadian clock
Abstract

Background: Understanding the dynamical behaviour of biological systems is challenged by their large number of components and interactions. While efforts have been made in this direction to reduce model complexity, they often prove insufficient to grasp which and when model processes play a crucial role. Answering these questions is fundamental to unravel the functioning of living organisms.[br/] Results: We design a method for dealing with model complexity, based on the analysis of dynamical models by means of Principal Process Analysis. We apply the method to a well-known model of circadian rhythms in mammals. The knowledge of the system trajectories allows us to decompose the system dynamics into processes that are active or inactive with respect to a certain threshold value. Process activities are graphically represented by Boolean and Dynamical Process Maps. We detect model processes that are always inactive, or inactive on some time interval. Eliminating these processes reduces the complex dynamics of the original model to the much simpler dynamics of the core processes, in a succession of sub-models that are easier to analyse. We quantify by means of global relative errors the extent to which the simplified models reproduce the main features of the original system dynamics and apply global sensitivity analysis to test the influence of model parameters on the errors.[br/] Conclusion: The results obtained prove the robustness of the method. The analysis of the sub-model dynamics allows us to identify the source of circadian oscillations. We find that the negative feedback loop involving proteins PER, CRY, CLOCK-BMAL1 is the main oscillator, in agreement with previous modelling and experimental studies. In conclusion, Principal Process Analysis is a simple-to-use method, which constitutes an additional and useful tool for analysing the complex dynamical behaviour of biological systems.

Published
2018

44. Modélisation du portage des salmonelles dans un élevage porcin

Author

Guillaumont, Justine, Bidot, Caroline, and Touzeau, Suzanne

Subjects
modèle dynamique en temps discret, modèle stochastique, couplage démographie & épidémiologie, porc, Salmonelles, conduite den bandes, discrete time dynamical model, stochastic model, coupling demography & epidemiology, Pig, Salmonella, batch management
Abstract

Ce rapport décrit un modèle de simulation stochastique représentant la dynamique des populations de truies et de porcs dans un troupeau naisseur engraisseur et la transmission indirecte des Salmonelles au sein de ce troupeau. Ce modèle a été initialement développé pendant la thèse de doctorat d'Amandine Lurette Il a ensuite a été repris et étandu dans le cadre du stage de Justine Guillaumont, pour intégrer les différentes conduites en bandes rencontrées en Bretagne. L'effet du mélange de bandes et du type de conduite ont été évalués à partir de ce modèle., This report describes a stochastic simulation model which represents both the pig and sow population dynamics in a farrow-to- finish herd and the indirect Salmonella transmission within this herd. This model was initially developed during Amandine Lurette's PhD thesis . It was then picked up and extended as part of Justine Guillaumont's traineeship to integrate the various batch management systems encountered in Brittany. The effect of batch mixing and management systems were assessed using this model.

Published
2017

47. A multi-seasonal model of plant-nematode interactions and its use for durable plant resistance deployment

Author

Nilusmas, Samuel, Mercat, Mathilde, Perrot , Thomas, Touzeau, Suzanne, Djian-Caporalino, Caroline, Castagnone, Philippe, Mailleret, Ludovic, Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), UMR 1355 ISA Institut Sophia Agrobiotech, Université de Nice Sophia-Antipolis (UNSA), Biological control of artificial ecosystems (BIOCORE), Laboratoire d'océanographie de Villefranche (LOV), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), and 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)

Subjects
resistance, [SDV]Life Sciences [q-bio], fungi, [SDE]Environmental Sciences, food and beverages, epidemiology
Abstract

Root-knot nematodes of the genus Meloidogyne are soil-borne, little mobile, polyphagous pests which threaten important sheltered crops such as vegetables or small fruits. They attack plant roots to feed and reproduce and have a major impact on crop yield. Most eco-friendly plant protection strategies are based on the use of resistant crops. The emergence of virulent nematode variants, which are adapted to the resistance, challenges the durability of such methods. Because virulent root-knot nematodes exhibit a reduced fitness on non-resistant crops, combining both resistant and non-resistant plants can help increase the efficacy and sustainability of resistance-based nematode control. Since nematodes have poor intrinsic dispersal ability, the association between resistant and non-resistant plants should rely on crop rotation over cropping seasons, rather than on spatial arrangements. We proposed a semi-discrete model describing the population dynamics of plant roots and of nematodes within and over cropping seasons. This model, inspired by epidemiological concepts, was fitted to literature data on the within cropping season dynamics of non-resistant plants and avirulent nematodes; it was then extended to also account for resistant plants and virulent parasites. The model was used to compute optimal crop rotation strategies with respect to the minimization of an epidemiological criterion called AUDPC to increase crop yield over different time horizons (between 2 and 40 cropping seasons).

Published
2016

48. Towards a better understanding of the within-host dynamics to PRRSv: insights from a modelling approach

Author

Go, Natacha, Belloc, Catherine, Bidot, Caroline, Touzeau, Suzanne, Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas] (MaIAGE), Institut National de la Recherche Agronomique (INRA), Biologie, Epidémiologie et analyse de risque en Santé Animale (BIOEPAR), Université Nantes Angers Le Mans (LUNAM), Roslin Institute, University of Edinburgh, Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Biological control of artificial ecosystems (BIOCORE), Laboratoire d'océanographie de Villefranche (LOV), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-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), INRA, AgroParisTech, ABIES, and French Research Agency, program Investments for the future, project ANR-10-BINF-07 (MIHMES)

Subjects
[SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, [INFO]Computer Science [cs], [MATH]Mathematics [math]
Abstract

PRRSv is responsible for significant worldwide production losses and its control is a major challenge for the swine industry. Vaccination, the main control measure, does not allow to eradicate the infection and only confers a partial protection to the host. This lack of efficiency is mainly due to the strong variability in PRRSv strain virulence, which induces highly variable within-host dynamics. Consequently, there is a real need to better understand the interactions between the virus and the immune response in order to improve PRRSv control. To tackle this issue, a dynamic and deterministic modelling approach was chosen. We developed an original immunological model consisting in an integrative representation of the within-host dynamics. It describes the immune mechanisms at the between-cell scale, including the innate response, the activation and orientation of the adaptive response and their complex regulations by the major cytokines. By the definition of parameter sets based on published experimental and modelling studies, this approach allowed us to explore various scenarios in terms of host susceptibility, strain virulence, as well as dose and duration of viral exposure. Our first results show that similar infection durations associated with contrasted immune dynamics can be explained by the consideration of the immune mechanisms affected by the strain virulence. They provide new insights to explain apparent inconsistencies between experimental data. We then showed that the exposure, whose effect is often neglected, has an impact on the within-host dynamics, which varies depending on the virulence level. Finally, the within-host dynamics induced by the infection of a vaccinated pig is currently under exploration, opening up promising leads to improve vaccine efficiency. All these results provide new insights to guide further experimental and modelling approaches and they offer promising prospects to improve PRRSv control at the herd level by an immuno-epidemiological modelling approach.

Published
2015

50. Modelling the infection and immune dynamics induced by PRRSv: influence of strain virulence and host exposure

Author

Go, Natacha, Bidot, Caroline, Belloc, Catherine, Touzeau, Suzanne, Unité de recherche Mathématiques et Informatique Appliquées (MIA), Institut National de la Recherche Agronomique (INRA), UMR 1300 Biologie, Epidémiologie et Analyse du Risque, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire, Agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Biologie, Epidémiologie et Analyse du Risque (BioEpAR)-Santé animale (S.A.), Institut Sophia Agrobiotech [Sophia Antipolis] (ISA), Institut National de la Recherche Agronomique (INRA)-Université Nice Sophia Antipolis (... - 2019) (UNS), and Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
General Mathematics, [SDV]Life Sciences [q-bio], Autre (Sciences de l'ingénieur), PRRSv, Automatic Control Engineering, Exposure, Immune response, mathematical model, Mathématiques générales, Automatique
Abstract

The immune mechanisms which determine the infection severity and duration induced by pathogens targeting pulmonary macrophages are poorly known. To explore the impact of such pathogens, it is indispensable to integrate the various immune mechanisms and to take into account the variability in pathogen virulence, host susceptibility, and host exposure to the pathogen. In this context, we developed an original ODE model representing the infection and immune dynamics induced by such a pathogen. Compared to previous modelling studies, we detailed the macrophage-pathogen interactions, the innate immune response, and the cytokine regulations. The adaptive immune response included the main functions of the cellular, humoral, and regulatory orientations. The model obtained has 14 state variables: the pathogen; four effectors of the innate response, consisting of three macrophage states (susceptible, phagocyting, and infected) and the natural killers; three effectors of the adaptive response, representing the cellular, humoral and regulatory responses; seven cytokine groups, consisting of the major pro-inflammatory, the innate antiviral and the immuno-regulatory (IFNg, IL12, IL10, TGFb) cytokines. The main processes integrated in the model are: the pathogen phagocytosis by the macrophages; the macrophage infection; the pathogen excretion by infected macrophages; the recruitment and decay/migration of the macrophages; the activation and decay/migration of the other effectors; the cytokine productions by the immune cells and their decay; the cytokine regulations.We calibrated our model for the Porcine Respiratory and Reproductive Syndrome virus (PRRSv), a major concern for the swine industry. We extracted value ranges for the model parameters from modelling and experimental studies on respiratory pathogens. A sensitivity analysis was used to identify the most influential parameters and to define a realistic reference scenario.We first used our model to explore the influence of strain virulence and host susceptibility on the infection duration and immune dynamics. We obtained contrasted results, suggesting hypotheses to explain the apparent contradictions between published results: high levels of antiviral cytokines and a dominant cellular response were associated with either short, the usual assumption, or long infection durations. In addition, we extracted some synthetic and original elements from our work to characterise immune mechanisms and their impact on the infection duration. We then used our model to explore the impact of host exposure on the infection duration and severity for various levels of strain virulence. We tested several exposure functions to account for experimental inoculations or natural infections. We found that: (i) high exposures induced high viral peaks; (ii) prolonged exposures and high virulences induced prolonged infections; and (iii) the viral peak determined the immune response activation and the adaptive response orientation, whereas the virulence determined the relative levels of adaptive antiviral and immuno-modulatory cytokines (IL10, TGFb).In conclusion, this integrative model provides a powerful framework to go beyond experimental constraints. It could be used to help designing efficient vaccination strategies. It could also provide a base for an immuno-epidemiological model, by identifying the key mechanisms (exposure x immune response) that are responsible for the infection severity and duration.Anglais

Published
2014

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