Sébastien Saint-Jean

Impacts of plant growth and architecture on pathogen processes and their consequences for epidemic behaviour

As any epidemic on plants is driven by the amount of susceptible tissue, and the distance between organs, any modification in the host population, whether quantitative or qualitative, can have an impact on the epidemic dynamics. In this paper we examine using examples described in the literature, the features of the host plant and the use of crop management which are likely to decrease diseases. We list the pathogen processes that can be affected by crop growth and architecture modifications and then determine how we can highlight the principal ones. In most cases, a reduction in plant growth combined with an increase in plant or crop porosity reduces infection efficiency and spore dispersal. Experimental approaches in semi-controlled conditions, with concomitant characterisation of the host, microclimate and disease, allow a better understanding and analysis of the processes impacted. Afterwards, the models able to measure and predict the effect of plant growth and architecture on epidemic behaviour are reviewed.

Using virtual 3-D plant architecture to assess fungal pathogen splash dispersal in heterogeneous canopies: a case study with cultivar mixtures and a non-specialized disease causal agent

BACKGROUND AND AIMS Recent developments in plant disease management have led to a growing interest in alternative strategies, such as increasing host diversity and decreasing the use of pesticides. Use of cultivar mixtures is one option, allowing the spread of plant epidemics to be slowed down. As dispersal of fungal foliar pathogens over short distances by rain-splash droplets is a major contibutor to the spread of disease, this study focused on modelling the physical mechanisms involved in dispersal of a non-specialized pathogen within heterogeneous canopies of cultivar mixtures, with the aim of optimizing host diversification at the intra-field level. METHODS Virtual 3-D wheat-like plants (Triticum aestivum) were used to consider interactions between plant architecture and disease progression in heterogeneous canopies. A combined mechanistic and stochastic model, taking into account splash droplet dispersal and host quantitative resistance within a 3-D heterogeneous canopy, was developed. It consists of four sub-models that describe the spatial patterns of two cultivars within a complex canopy, the pathway of rain-splash droplets within this canopy, the proportion of leaf surface area impacted by dispersal via the droplets and the progression of disease severity after each dispersal event. KEY RESULTS Different spatial organization, proportions and resistance levels of the cultivars of two-component mixtures were investigated. For the eight spatial patterns tested, the protective effect against disease was found to vary by almost 2-fold, with the greatest effect being obtained with the smallest genotype unit area, i.e. the ground area occupied by an independent unit of the host population that is genetically homogeneous. Increasing both the difference between resistance levels and the proportion of the most resistant cultivar often resulted in a greater protective effect; however, this was not observed for situations in which the most resistant of the two cultivars in the mixture had a relatively low level of resistance. CONCLUSIONS The results show agreement with previous data obtained using experimental approaches. They demonstrate that in order to maximize the potential mixture efficiency against a splash-dispersed pathogen, optimal susceptible/resistant cultivar proportions (ranging from 1/9 to 5/5) have to be established based on host resistance levels. The results also show that taking into account dispersal processes in explicit 3-D plant canopies can be a key tool for investigating disease progression in heterogeneous canopies such as cultivar mixtures.

Effects of wheat varietal resistance level and rainfall characteristics on splash dispersal of Septoria tritici blotch

Septoria tritici blotch is an important splash-dispersed disease, causing high yield losses in Europe. Plant disease propagation results from spore dispersal and susceptibility of plant tissues. An experiment was performed in order to study differents aspects of the disease dispersal cycle. Three wheat varieties with contrasted resistance levels were grown in greenhouse conditions until flowering. Plant canopies of each variety received rains of two different raindrop diameter distributions generated by a rain simulator. A linear inoculum source consisting of an aqueous suspension of spores was placed in the middle of each canopy. Horizontal and vertical spore fluxes were measured using traps composed of microscope slides. Varietal resistance was assessed in parallel. After incubation, leaves sampled in canopies were collected and scanned. Spore traps slides were photographed using a microscope combined with a digital camera. Disease area measurement and automatic spore counting were achieved using an image analysis software. Both disease and spore fluxes decreased with the distance from the inoculum source and lower mean raindrop diameter. Disease levels depended on variety and leaf level. Vertical and horizontal gradients of spore fluxes and disease varied in function of rain type and variety. Combining all these results made it possible to disentangle components of splash-dispersed disease propagation for a single dispersal event.

A white paper on global wheat health based on scenario development and analysis

Scenario analysis constitutes a useful approach to synthesize knowledge and derive hypotheses in the case of complex systems that are documented with mainly qualitative or very diverse information. In this article, a framework for scenario analysis is designed and then, applied to global wheat health within a timeframe from today to 2050. Scenario analysis entails the choice of settings, the definition of scenarios of change, and the analysis of outcomes of these scenarios in the chosen settings. Three idealized agrosystems, representing a large fraction of the global diversity of wheat-based agrosystems, are considered, which represent the settings of the analysis. Several components of global changes are considered in their consequences on global wheat health: climate change and climate variability, nitrogen fertilizer use, tillage, crop rotation, pesticide use, and the deployment of host plant resistances. Each idealized agrosystem is associated with a scenario of change that considers first, a production situation and its dynamics, and second, the impacts of the evolving production situation on the evolution of crop health. Crop health is represented by six functional groups of wheat pathogens: the pathogens associated with Fusarium head blight; biotrophic fungi, Septoria-like fungi, necrotrophic fungi, soilborne pathogens, and insect-transmitted viruses. The analysis of scenario outcomes is conducted along a risk-analytical pattern, which involves risk probabilities represented by categorized probability levels of disease epidemics, and risk magnitudes represented by categorized levels of crop losses resulting from these levels of epidemics within each production situation. The results from this scenario analysis suggest an overall increase of risk probabilities and magnitudes in the three idealized agrosystems. Changes in risk probability or magnitude however vary with the agrosystem and the functional groups of pathogens. We discuss the effects of global changes on the six functional groups, in terms of their epidemiology and of the crop losses they cause. Scenario analysis enables qualitative analysis of complex systems, such as plant pathosystems that are evolving in response to global changes, including climate change and technology shifts. It also provides a useful framework for quantitative simulation modeling analysis for plant disease epidemiology.

Cultivar architecture modulates spore dispersal by rain splash: A new perspective to reduce disease progression in cultivar mixtures

Cultivar mixtures can be used to improve the sustainability of disease management within farming systems by growing cultivars that differ in their disease resistance level in the same field. The impact of canopy aerial architecture on rain-splash dispersal could amplify disease reduction within mixtures. We designed a controlled conditions experiment to study single splash-dispersal events and their consequences for disease. We quantified this impact through the spore interception capacities of the component cultivars of a mixture. Two wheat cultivars, differing in their aerial architecture (mainly leaf area density) and resistance to Septoria tritici blotch, were used to constitute pure stands and mixtures with 75% of resistant plants that accounted for 80% of the canopy leaf area. Canopies composed of 3 rows of plants were exposed to standardized spore fluxes produced by splashing calibrated rain drops on a linear source of inoculum. Disease propagation was measured through spore fluxes and several disease indicators. Leaf susceptibility was higher for upper than for lower leaves. Dense canopies intercepted more spores and mainly limited horizontal spore transfer to the first two rows. The presence of the resistant and dense cultivar made the mixed canopy denser than the susceptible pure stand. No disease symptoms were observed on susceptible plants of the second and third rows in the cultivar mixture, suggesting that the number of spores intercepted by these plants was too low to cause disease symptoms. Both lesion area and disease conditional severity were significantly reduced on susceptible plants within mixtures on the first row beside the inoculum source. Those reductions on one single-splash dispersal event, should be amplified after several cycle over the full epidemic season. Control of splash-dispersed diseases within mixtures could therefore be improved by a careful choice of cultivars taking into consideration both resistance and architecture.

Les espaces périurbains : entre pollution des villes et pollution des champs aux échelles régionale et locale

Les territoires periurbains, zones de transition entre les zones urbaines et rurales, sont soumis a de nombreuses pollutions a la fois gazeuses et particulaires. Ces pollutions proviennent de sources locales comme les activites residentielles, le trafic routier et les activites agricoles, mais egalement de sources regionales issues des activites urbaines et des emissions des zones (pseudo-)naturelles adjacentes. Cet article presente une synthese des differentes sources de pollution affectant la qualite de l’air en milieu periurbain. Il est evident que les pollutions purement anthropiques ne peuvent etre dissociees de celles issues du fonctionnement des ecosystemes (pseudo-)naturels dans ces espaces. Enfin, les enjeux vis-a-vis de l’agriculture periurbaine, fortement presente et en developpement du fait d’une volonte de consommer des productions locales, sont discutes.

Sharing efforts for modelling plant systems: from publications to reusable software components

Plant models become increasingly complex and their implementation often implies the use of advanced techniques in computer science. This evolution has been accompanied by the production of dedicated plant modelling tools, such as simulation platforms, that facilitate research in this field. However, much less sharing is observed for plant models themselves, that is for computer programs produced by scientists to address their specific questions. Yet, these programs could be highly valuable for other researchers, to avoid redundant development of similar code or to help non-specialists to simulate parts of a complex system. Model descriptions found in academic publications, even combined with code sources, are generally not sufficient for model reuse. Most difficulties come from the heterogeneity of language used, the structure of the programs, the download and installation procedures, the accessibility to the source code of the model, and the availability of documentation. The OpenAlea initiative (http://openalea.gforge.inria.fr) has been launched to address these problems by providing plant modellers with collaborative tools and guidelines to increase software quality, hence re-usability of their models. The Alinea pilot project further tested these concepts in a sample community of ecophysiologists and biophysicists. Based on this experience, we illustrate pros and cons of the approach and discuss future direction of progress. We foresee three steps towards a better re-usability of models: a better interoperability of existing tools and simulation platforms, the emergence of design patterns for plant modelling, and the definition of standardised data structures.