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

National-scale investigation reveals the dominant role of phyllosphere fungal pathogens in sorghum yield loss

Fungal plant pathogens threaten crop production and sustainable agricultural development. However, the environmental factors driving their diversity and nationwide biogeographic model remain elusive, impacting our capacity to predict their changes under future climate scenarios. Here, we analyzed potential fungal plant pathogens from 563 samples collected from 57 agricultural fields across China. Over 28.0% of fungal taxa in the phyllosphere were identified as potential plant pathogens, compared to 22.3% in the rhizosphere. Dominant fungal plant pathogen groups were Cladosporium (in the phyllosphere) and Fusarium (in the rhizosphere), with higher diversity observed in the phyllosphere than in rhizosphere soil. Deterministic processes played an important role in shaping the potential fungal plant pathogen community assembly in both habitats. Mean annual precipitation and temperature were the most important factor influencing phyllosphere fungal plant pathogen richness. Significantly negative relationships were found between fungal pathogen diversity and sorghum yield. Notably, compared to the rhizosphere, the phyllosphere fungal plant pathogen diversity played a more crucial role in sorghum yield. Together, our work provides novel insights into the factors governing the spatial patterns of fungal plant pathogens in the crop microbiome, and highlights the potential significance of aboveground phyllosphere fungal plant pathogens in crop productivity.

Modeling the Impact of Proportion, Sowing Date, and Architectural Traits of a Companion Crop on Foliar Fungal Pathogens of Wheat in Crop Mixtures

Diversification of cropping systems is a lever for the management of epidemics. However, most research to date has focused on cultivar mixtures, especially for cereals, even though crop mixtures can also improve disease management. To investigate the benefits of crop mixtures, we studied the effect of different crop mixture characteristics (i.e., companion proportion, sowing date, and traits) on the protective effect of the mixture. We developed a SEIR (Susceptible, Exposed, Infectious, Removed) model of two damaging wheat diseases (Zymoseptoria tritici and Puccinia triticina), which were applied to different canopy components, ascribable to wheat and a theoretical companion crop. We used the model to study the sensitivity of disease intensity to the following parameters: wheat-versus-companion proportion, companion sowing date and growth, and architectural traits. For both pathogens, the companion proportion had the strongest effect, with 25% of companion reducing disease severity by 50%. However, changing companion growth and architectural traits also significantly improved the protective effect. The effect of companion characteristics was consistent across different weather conditions. After decomposing the dilution and barrier effects, the model suggested that the barrier effect is maximized for an intermediate proportion of companion crop. Our study thus supports crop mixtures as a promising strategy to improve disease management. Future studies should identify real species and determine the combination of host and companion traits to maximize the protective effect of the mixture. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Management of Septoria Tritici Blotch Using Cultivar Mixtures

Septoria tritici blotch (STB) is among the most devastating diseases in European wheat production. In recent years, there has been increased interest in using cultivar mixtures as part of an integrated control strategy against diseases. This study investigated different cultivar mixtures for their ability to control STB across three years and at seven trial sites in Denmark with a range of fungicide strategies, yielding a total of 194 individual cultivar mixture combinations. The mixtures were composed of two, three, or four cultivars that were either similar or contrasting in their susceptibility to STB. Across all trials, the cultivar mixtures reduced disease severity significantly, by 14% compared with the component cultivars grown in monoculture. The reductions were larger when the disease pressure was high and when the mixtures included more cultivars. Mixtures composed of four cultivars reduced disease severity significantly, by 24%. Across all trials, cultivar mixtures significantly increased yield by 2% compared with the component cultivars grown in monoculture. The yield increase was significant for plots treated with one or two fungicide applications, and cultivar mixtures increased yield significantly, by 4.4% in untreated plots. The yield increase was smaller for mixtures with a high proportion of resistant cultivars. Based on the results from this study, cultivar mixtures can contribute positively to an integrated pest management (IPM) strategy, by reducing disease severity for STB and increasing yield. The most pronounced benefits from cultivar mixtures were found in fields with moderate to low fungicide input, under conditions with high disease pressure, when combining four cultivars with varying susceptibilities.

Functional-Structural Plant Models Mission in Advancing Crop Science: Opportunities and Prospects

Functional-structural plant models (FSPMs) have been evolving for over 2 decades and their future development, to some extent, depends on the value of potential applications in crop science. To date, stabilizing crop production by identifying valuable traits for novel cultivars adapted to adverse environments is topical in crop science. Thus, this study will examine how FSPMs are able to address new challenges in crop science for sustainable crop production. FSPMs developed to simulate organogenesis, morphogenesis, and physiological activities under various environments and are amenable to downscale to the tissue, cellular, and molecular level or upscale to the whole plant and ecological level. In a modeling framework with independent and interactive modules, advanced algorithms provide morphophysiological details at various scales. FSPMs are shown to be able to: (i) provide crop ideotypes efficiently for optimizing the resource distribution and use for greater productivity and less disease risk, (ii) guide molecular design breeding via linking molecular basis to plant phenotypes as well as enrich crop models with an additional architectural dimension to assist breeding, and (iii) interact with plant phenotyping for molecular breeding in embracing three-dimensional (3D) architectural traits. This study illustrates that FSPMs have great prospects in speeding up precision breeding for specific environments due to the capacity for guiding and integrating ideotypes, phenotyping, molecular design, and linking molecular basis to target phenotypes. Consequently, the promising great applications of FSPMs in crop science will, in turn, accelerate their evolution and vice versa.

Models of Plant Resistance Deployment

Owing to their evolutionary potential, plant pathogens are able to rapidly adapt to genetically controlled plant resistance, often resulting in resistance breakdown and major epidemics in agricultural crops. Various deployment strategies have been proposed to improve resistance management. Globally, these rely on careful selection of resistance sources and their combination at various spatiotemporal scales (e.g., via gene pyramiding, crop rotations and mixtures, landscape mosaics). However, testing and optimizing these strategies using controlled experiments at large spatiotemporal scales are logistically challenging. Mathematical models provide an alternative investigative tool, and many have been developed to explore resistance deployment strategies under various contexts. This review analyzes 69 modeling studies in light of specific model structures (e.g., demographic or demogenetic, spatial or not), underlying assumptions (e.g., whether preadapted pathogens are present before resistance deployment), and evaluation criteria (e.g., resistance durability, disease control, cost-effectiveness). It highlights major research findings and discusses challenges for future modeling efforts.

Precipitation increases the abundance of fungal plant pathogens in Eucalyptus phyllosphere

Understanding the current and future distributions of plant pathogens is critical to predict the plant performance and related economic benefits in the changing environment. Yet, little is known about the roles of environmental drivers in shaping the profiles of fungal plant pathogens in phyllosphere, an important habitat of microbiomes on Earth. Here, using a large-scale investigation of Eucalyptus phyllospheric microbiomes in Australia and the multiple linear regression model, we show that precipitation is the most important predictor of fungal taxonomic diversity and abundance. The abundance of fungal plant pathogens in phyllosphere exhibited a positive linear relationship with precipitation. With this empirical dataset, we constructed current and future atlases of phyllosphere plant pathogens to estimate their spatial distributions under different climate change scenarios. Our atlases indicate that the abundance of fungal plant pathogens would increase especially in the coastal regions with up to 100-fold increase compared with the current abundance. These findings advance our understanding of the distributions of fungal plant pathogens in phyllospheric microbiomes under the climate change, which can improve our ability to predict and mitigate their impacts on plant productivity and economic losses.

Warming affects foliar fungal diseases more than precipitation in a Tibetan alpine meadow

The effects of global change on semi-natural and agro-ecosystem functioning have been studied extensively. However, less well understood is how global change will influence fungal diseases, especially in a natural ecosystem. We use data from a 6-yr factorial experiment with warming (simulated using infrared heaters) and altered precipitation treatments in a natural Tibetan alpine meadow ecosystem, from which we tested global change effects on foliar fungal diseases at the population and community levels, and evaluated the importance of direct effects of the treatments and community-mediated (indirect) effects (through changes in plant community composition and competence) of global change on community pathogen load. At the population level, we found warming significantly increased fungal diseases for nine plant species. At the community level, we found that warming significantly increased pathogen load of entire host communities, whereas no significant effect of altered precipitation on community pathogen load was detected. We concluded that warming influences fungal disease prevalence more than precipitation does in a Tibetan alpine meadow. Moreover, our study provides new experimental evidence that increases in disease burden on some plant species and for entire host communities is primarily the direct effects of warming, rather than community-mediated (indirect) effects.

Contrasting plant height can improve the control of rain-borne diseases in wheat cultivar mixture: modelling splash dispersal in 3-D canopies

Background and Aims

Growing cultivars differing by their disease resistance level together (cultivar mixtures) can reduce the propagation of diseases. Although architectural characteristics of cultivars are little considered in mixture design, they could have an effect on disease, in particular through spore dispersal by rain splash, which occurs over short distances. The objective of this work was to assess the impact of plant height of wheat cultivars in mixtures on splash dispersal of Zymoseptoria tritici, which causes septoria tritici leaf blotch.

Methods

We used a modelling approach involving an explicit description of canopy architecture and splash dispersal processes. The dispersal model computed raindrop interception by a virtual canopy as well as the production, transport and interception of splash droplets carrying inoculum. We designed 3-D virtual canopies composed of susceptible and resistant plants, according to field measurements at the flowering stage. In numerical experiments, we tested different heights of virtual cultivars making up binary mixtures to assess the influence of this architectural trait on dispersal patterns of spore-carrying droplets.

Key Results

Inoculum interception decreased exponentially with the height relative to the main inoculum source (lower diseased leaves of susceptible plants), and little inoculum was intercepted further than 40 cm above the inoculum source. Consequently, tall plants intercepted less inoculum than smaller ones. Plants with twice the standard height intercepted 33 % less inoculum than standard height plants. In cases when the height of suscpeptible plants was doubled, inoculum interception by resistant leaves was 40 % higher. This physical barrier to spore-carrying droplet trajectories reduced inoculum interception by tall susceptible plants and was modulated by plant height differences between cultivars of a binary mixture.

Conclusions

These results suggest that mixture effects on spore dispersal could be modulated by an adequate choice of architectural characteristics of cultivars. In particular, even small differences in plant height could reduce spore dispersal.

Crop Fertilization Impacts Epidemics and Optimal Latent Period of Biotrophic Fungal Pathogens

Crop pathogens are known to rapidly adapt to agricultural practices. Although cultivar resistance breakdown and resistance to pesticides have been broadly studied, little is known about the adaptation of crop pathogens to fertilization regimes and no epidemiological model has addressed that question. However, this is a critical issue for developing sustainable low-input agriculture. In this article, we use a model of life history evolution of biotrophic wheat fungal pathogens in order to understand how they could adapt to changes in fertilization practices. We focus on a single pathogen life history trait, the latent period, which directly determines the amount of resources allocated to growth and reproduction along with the speed of canopy colonization. We implemented three fertilization scenarios, corresponding to major effects of increased nitrogen fertilization on crops: (i) increase in nutrient concentration in leaves, (ii) increase of leaf lifespan, and (iii) increase of leaf number (tillering) and size that leads to a bigger canopy size. For every scenario, we used two different fitness measures to identify putative evolutionary responses of latent period to changes in fertilization level. We observed that annual spore production increases with fertilization, because it results in more resources available to the pathogens. Thus, diminishing the use of fertilizers could reduce biotrophic fungal epidemics. We found a positive relationship between the optimal latent period and fertilization when maximizing total spore production over an entire season. In contrast, we found a negative relationship between the optimal latent period and fertilization when maximizing the within-season exponential growth rate of the pathogen. These contrasting results were consistent over the three tested fertilization scenarios. They suggest that between-strain diversity in the latent period, as has been observed in the field, may be due to diversifying selection in different cultural environments.

How Knowledge of Pathogen Population Biology Informs Management of Septoria Tritici Blotch

Zymoseptoria tritici (previously Mycosphaerella graminicola) causes Septoria tritici blotch (STB) on wheat. The population biology of Z. tritici has been exceptionally well characterized as a result of intensive studies conducted over nearly 30 years. These studies provided important insights into the biology, epidemiology and evolutionary history of Z. tritici that will prove useful for management of STB. The well-documented, rapid adaptation of Z. tritici populations to fungicide applications and deployment of wheat cultivars carrying both major gene and quantitative resistance reflects the high evolutionary potential predicted by the large effective population size, high degree of gene flow and high levels of recombination found in field populations of Z. tritici globally. QST studies that assessed the global diversity for several important quantitative traits confirmed the adaptive potential of field populations and laid the groundwork for quantitative trait loci (QTL) mapping studies. QTL mapping elucidated the genetic architecture of each trait and led to identification of candidate genes affecting fungicide resistance, thermal adaptation, virulence, and host specialization. The insights that emerged through these analyses of Z. tritici population biology can now be used to generate actionable disease management strategies aimed at sustainably reducing losses due to STB. The high evolutionary potential found in field populations of Z. tritici requires deployment of a corresponding dynamically diverse set of control measures that integrate cultural, chemical, biological and resistance breeding strategies. In this review, we describe and prioritize STB control strategies based on current knowledge of Z. tritici population biology and propose a future research agenda oriented toward long-term STB management.

Functional-structural plant models: a growing paradigm for plant studies

A number of research groups in various areas of plant biology as well as computer science and applied mathematics have addressed modelling the spatiotemporal dynamics of growth and development of plants. This has resulted in development of functional-structural plant models (FSPMs). In FSPMs, the plant structure is always explicitly represented in terms of a network of elementary units. In this respect, FSPMs are different from more abstract models in which a simplified representation of the plant structure is frequently used (e.g. spatial density of leaves, total biomass, etc.). This key feature makes it possible to build modular models and creates avenues for efficient exchange of model components and experimental data. They are being used to deal with the complex 3-D structure of plants and to simulate growth and development occurring at spatial scales from cells to forest areas, and temporal scales from seconds to decades and many plant generations. The plant types studied also cover a broad spectrum, from algae to trees. This special issue of Annals of Botany features selected papers on FSPM topics such as models of morphological development, models of physical and biological processes, integrated models predicting dynamics of plants and plant communities, modelling platforms, methods for acquiring the 3-D structures of plants using automated measurements, and practical applications for agronomic purposes.