Development of strategies to increase sustainability of scab control, i.e. decrease the risks of invasion and adaptation of pathogen populations able to overcome the host resistance

2.1 Timing of pathogen adaptation to quantitative resistance  

We built and explored a stochastic model to study pathogen adaptation to the quantitative plant resistance. Quantitative resistance is thought to be more durable since it reduces pathogen density and therefore exerts less selective pressure on the pathogen population in comparison with qualitative resistance. The mechanisms underlying the quantitative resistance are poorly known that can explain the lack of theoretical studies focusing on the pathogen adaptation to this kind of resistance. Quantitative resistance can depress distinct pathogen life-traits, such as the latent period, infection efficiency, lesion size or the spore production rate. However, no study, whether theoretical or empirical, demonstrated how restoring the various pathogen traits could drive the speed of pathogen adaptation. Our stochastic framework allowed us to test numerous hypotheses about processes driving the erosion of quantitative resistance. It also provided general guidance about how to manage quantitative resistance to increase its durability. In particular, we showed that in order to decelerate the pathogen's progressive adaptation, QTLs that decrease the pathogen's ability to colonize its host must be combined with QTLs that decrease its rate of reproduction. Our theoretical framework can help breeders to develop new principles for sustainable deployment of quantitative trait loci.

In collaboration with RESPOM, we applied these principles on apple scab and showed that different QTLs can act on different life traits of the pathogen due to a different activation or repression of metabolic ways mainly involved in salicylic acid and auxin pathways, production of secondary metabolites and cell wall strengthening. Thanks to the combined effects of the individual QTLs, the pyramiding of the QTLs hindered fungal development at different stages: before the penetration of the plant cuticule, after the penetration with hypersensitivity reaction, and during the colonization and asexual reproduction. As a consequence, the pyramiding allowed to efficiently control strains of V. inaequalis that were aggressive towards the QTLs alone. In the same way, pyramiding of QTLs and R genes can increase the sustainability of disease control . However, we showed that the efficiency of this strategy in orchards depends on the genetic structure of the pathogen populations and their ability to recombine or not.

2.2 Mathematically optimized spatial arrangement of cultivars in mixtures (Rudolf Hermanns Foundation Prize 2016)

To limit both spatial and adaptive dynamics of fungal diseases we wonder how cultivars carrying quantitative resistance should be deployed in agro-ecosystems. The most natural strategy is to use them in cultivar mixtures splitting the host population into suitable and less suitable/unsuitable spatial units. However, the ability of a cultivar mixture to control a fungal disease spread highly depends on the spatial arrangement of cultivars that in one’s turn should be in concordance with disease characteristics driving its spatial dynamics. Consequently, the deployment of a cultivar mixture is an optimization problem: the objective is to minimize disease severity by varying spatial arrangement of mixture cultivars. Thus, we extended our spatially explicit host-pathogen model with an algorithm optimizing the distance between susceptible cultivars. The software associated with the built model allows following the spatio-temporal dynamics of host and pathogen densities in two-dimensional domain. It can mimic different spatial deployment strategies of cultivars varying in susceptibility and it can help to clarify the factors delaying the spread of the pathogen population. The software optimizes the spatial arrangement of mixture cultivars accounting for continuum of spatial variation in host susceptibility.

A video is available at : https://www.youtube.com/watch?v=Md--q5NLlKk&ab_channel=INRAE

2.3 Cider apple orchard of tomorrow: design, evaluation and dissemination of production systems with high environmental performance and economically viable (“Vergers de demain” 2012-2018, funded by CASDAR).

In collaboration with IFPC (French Institute of Cider Productions), we contributed to the project with the design of two “mixed” orchards including 3 and 6 cider-apple varieties, respectively. Chosen varieties were classified in three classes according to their susceptibility: resistant (R), moderately resistant (MR) and susceptible (S). Considering the level of resistance of the given varieties, we optimized the ratio between mixture components and their spatial arrangement: two derived optimal orchards, R/S and R/MR/S, were planted in 2012. The empirical observation of scab severity (2014-2016) showed 23 to 50% of disease reduction in susceptible cultivar in R/S optimized orchard. Moreover, the optimal introduction of a moderately resistant cultivar into R/S mixture did not perturb its performance. We conclude that the most straightforward way to design a performant mixture is to optimize spatial arrangement of the cultivars of differing susceptibility (article in preparation). The significance of this work is that it demonstrates that such an optimization can increase the range of cultivars that can compose a performant mixture. Modelling coupled with empirical study allows us to contribute to the formulation of general principles of the mixture design that could help to develop sustainable agro-ecosystems exerting low selective pressure on the pathogen populations.

2.4 Integration of apple resistant cultivars in low-input systems

Developing appropriate strategies which integrate resistant cultivars into crop systems is needed to increase the efficiency and durability of the resistance, whatever the kind of resistance. Therefore, in collaboration with the Experimental Horticultural Unit (UEH, INRAE, Angers), we evaluated the relevance of the association of control methods for two kinds of resistances: (i) partial resistance in the apple cultivar Reine des Reinettes and (ii) major resistance (Rvi6) in the apple cultivar Ariane. We showed that the removal of leaf litter in autumn together with spraying of fungicides in the case of moderate or high risks of scab infection resulted in a sustainable control of scab on Reine des Reinettes over a five-year period and delayed the breakdown of the major resistance Rvi6 of Ariane by virulent isolates. This strategy allowed a 50% reduction of fungicides sprayings compared to the susceptible cultivar Gala conducted with the current rules of integrated fruit production.

2.5 Development of a molecular tool to monitor and map virulences (funded by SATT Ouest valorisation, CREATIVE funded by CASDAR, 2019-2021)

Allelic variation analysis of virulent strains overcoming the Rvi6 gene in Europe indicated that all alleles identified in orchards, except one, were present in the wild and that no new contemporary molecular event at this locus appeared to occur in orchards. This strongly suggests that we have an exhaustive list of existing virulent alleles. Based on this finding, we are developping an epidemic survey tool based on the PCR technique allowing detection of the Rvi6 virulent strains in orchards using spores’ traps (invention disclosure in 2018, patent funded by Satt Ouest Valorisation, ongoing redaction). Such an epidemic survey tool is expected by growers who want to know if the Rvi6 virulence is present in their orchards before using fungicides and before making the decision to plant Rvi6 cultivars.

A video is available at: https://www.youtube.com/watch?v=rXXBqgm-lLw&ab_channel=INRAE

All together our results highlight the role of gene flow between divergent populations in the emergence of new forms of diseases in agrosystems and wild habitats as summarized in Figure 4.

                Figure 4. Summary of studies performed in ECOFUN on populations of Venturia inaequalis infecting Malus spp (POMI) and Pyracantha spp. (PYR)