Trade-off between disease resistance and crop yield: a landscape-scale mathematical modelling perspective

Determination of the rate and frequency of Natura 250 EW fungicide for the management of cedar rust from Gesho (Rhamnus prinoides) in the north west Amhara Region, Ethiopia

Rhamnus prinoides (Gesho) is grown in the homesteads of farmers in western Amhara. The leaves, twigs, and stems of Gesho are indispensable ingredients in traditional beverages. Its production has recently suffered from cedar rust caused by the fungus Gymnosporangium. To manage this disease, different fungicides have been recommended. Therefore, this research was designed to determine the rate and frequency of the use of the Natura 250 EW system for managing this disease in Gesho during 2020. Five application rates of Natura 250 EW and three spray frequencies were used as treatments to manage the disease in infected Gesho plants via the Randomized Complete Block Design (RCBD). Statistically significant differences (P ≤ 0.05) were found between treatments for most parameters. Among these 0.75 litter ha-1 treatments, two spray applications resulted in the lowest severity and greatest relative efficacy, followed by three spray applications of 0.50 litter ha-1 at Bahir Dar Zuria district. However, at Yilmana Densa district, the lowest severity and greatest relative efficacy were found for the 0.75 litter ha-1 spray, followed by the 0.50 litter ha-1 spray, compared with the other treatments. Even though 0.75 litter ha-1 had greater relative efficacy and lower disease severity than the other treatments, there was no statistically significant difference between the three sprays of 0.50 litter ha-1 at both locations. Therefore, three sprays of Natura 250 EW at 0.50 litter ha-1 in 15-day intervals should be recommended and demonstrated for the management of cedar rust disease on Gesho.

Sweet Cherry Plants Prioritize Their Response to Cope with Summer Drought, Overshadowing the Defense Response to Pseudomonas syringae pv. syringae

Disease severity and drought due to climate change present significant challenges to orchard productivity. This study examines the effects of spring inoculation with Pseudomonas syringae pv. syringae (Pss) on sweet cherry plants, cvs. Bing and Santina with varying defense responses, assessing plant growth, physiological variables (water potential, gas exchange, and plant hydraulic conductance), and the levels of abscisic acid (ABA) and salicylic acid (SA) under two summer irrigation levels. Pss inoculation elicited a more pronounced response in 'Santina' compared to 'Bing' at 14 days post-inoculation (dpi), and those plants inoculated with Pss exhibited a slower leaf growth and reduced transpiration compared to control plants during 60 dpi. During differential irrigations, leaf area was reduced 14% and 44% in Pss inoculated plants of 'Bing' and 'Santina' respectively, under well-watered (WW) conditions, without changes in plant water status or gas exchange. Conversely, water-deficit (WD) conditions led to gas exchange limitations and a 43% decrease in plant biomass compared to that under WW conditions, with no differences between inoculation treatments. ABA levels were lower under WW than under WD at 90 dpi, while SA levels were significantly higher in Pss-inoculated plants under WW conditions. These findings underscore the influence on plant growth during summer in sweet cherry cultivars that showed a differential response to Pss inoculations and how the relationship between ABA and SA changes in plant drought level responses.

Plant necrotrophic bacterial disease resistance phenotypes, QTL, and metabolites identified through integrated genetic mapping and metabolomics in Solanum species

Most food crops are susceptible to necrotrophic bacteria that cause rotting and wilting diseases in fleshy organs and foods. All varieties of cultivated potato (Solanum tuberosum L.) are susceptible to diseases caused by Pectobacterium species, but resistance has been demonstrated in wild potato relatives including S. chacoense. Previous studies demonstrated that resistance is in part mediated by antivirulence activity of phytochemicals in stems and tubers. Little is known about the genetic basis of antivirulence traits, and the potential for inheritance and introgression into cultivated potato is unclear. Here, the metabolites and genetic loci associated with antivirulence traits in S. chacoense were elucidated by screening a sequenced S. tuberosum x S. chacoense recombinant inbred line (RIL) population for antivirulence traits of its metabolite extracts. Metabolite extracts from the RILs exhibited a quantitative distribution for two antivirulence traits that were positively correlated: quorum sensing inhibition and exo-protease inhibition, with some evidence of transgressive segregation, supporting the role of multiple loci and metabolites regulating these resistance-associated systems. Metabolomics was performed on the highly resistant and susceptible RILs that revealed 30 metabolites associated with resistance, including several alkaloids and terpenes. Specifically, several prenylated metabolites were more abundant in resistant RILs. We constructed a high-density linkage map with 795 SNPs mapped to 12 linkage groups, spanning a length of 1,507 cM and a density of 1 marker per 1.89 cM. Genetic mapping of the antivirulence and metabolite data identified five quantitative trait loci (QTLs) related to quorum sensing inhibition that explained 8-28% of the phenotypic variation and two QTLs for protease activity inhibition that explained 14-19% of the phenotypic variation. Several candidate genes including alkaloid, and secondary metabolite biosynthesis that are related to disease resistance were identified within these QTLs. Taken together, these data support that quorum sensing inhibition and exo-protease inhibition assays may serve as breeding targets to improve resistance to nectrotrophic bacterial pathogens in potato and other plants. The identified candidate genes and metabolites can be utilized in marker assisted selection and genomic selection to improve soft- rot and blackleg disease resistance.

A novel natural variation in the promoter of GmCHX1 regulates conditional gene expression to improve salt tolerance in soybean

Identification and characterization of soybean germplasm and gene(s)/allele(s) for salt tolerance is an effective way to develop improved varieties for saline soils. Previous studies identified GmCHX1 (Glyma03g32900) as a major salt tolerance gene in soybean, and two main functional variations were found in the promoter region (148/150 bp insertion) and the third exon with a retrotransposon insertion (3.78 kb). In the current study, we identified four salt-tolerant soybean lines, including PI 483460B (Glycine soja), carrying the previously identified salt-sensitive variations at GmCHX1, suggesting new gene(s) or new functional allele(s) of GmCHX1 in these soybean lines. Subsequently, we conducted quantitative trait locus (QTL) mapping in a recombinant-inbred line population (Williams 82 (salt-sensitive) × PI 483460B) to identify the new salt tolerance loci/alleles. A new locus, qSalt_Gm18, was mapped on chromosome 18 associated with leaf scorch score. Another major QTL, qSalt_Gm03, was identified to be associated with chlorophyll content ratio and leaf scorch score in the same chromosomal region of GmCHX1 on chromosome 3. Novel variations in a STRE (stress response element) cis-element in the promoter region of GmCHX1 were found to regulate the salt-inducible expression of the gene in these four newly identified salt-tolerant lines including PI 483460B. This new allele of GmCHX1 with salt-inducible expression pattern provides an energy cost efficient (conditional gene expression) strategy to protect soybean yield in saline soils without yield penalty under non-stress conditions. Our results suggest that there might be no other major salt tolerance locus similar to GmCHX1 in soybean germplasm, and further improvement of salt tolerance in soybean may rely on gene-editing techniques instead of looking for natural variations.

Cassava molecular genetics and genomics for enhanced resistance to diseases and pests

Cassava (Manihot esculenta) is one of the most important sources of dietary calories in the tropics, playing a central role in food and economic security for smallholder farmers. Cassava production is highly constrained by several pests and diseases, mostly cassava mosaic disease (CMD) and cassava brown streak disease (CBSD). These diseases cause significant yield losses, affecting food security and the livelihoods of smallholder farmers. Developing resistant varieties is a good way of increasing cassava productivity. Although some levels of resistance have been developed for some of these diseases, there is observed breakdown in resistance for some diseases, such as CMD. A frequent re-evaluation of existing disease resistance traits is required to make sure they are still able to withstand the pressure associated with pest and pathogen evolution. Modern breeding approaches such as genomic-assisted selection in addition to biotechnology techniques like classical genetic engineering or genome editing can accelerate the development of pest- and disease-resistant cassava varieties. This article summarizes current developments and discusses the potential of using molecular genetics and genomics to produce cassava varieties resistant to diseases and pests.

Why Do We Need Alternative Methods for Fungal Disease Management in Plants?

Fungal pathogens pose a major threat to food production worldwide. Traditionally, chemical fungicides have been the primary means of controlling these pathogens, but many of these fungicides have recently come under increased scrutiny due to their negative effects on the health of humans, animals, and the environment. Furthermore, the use of chemical fungicides can result in the development of resistance in populations of phytopathogenic fungi. Therefore, new environmentally friendly alternatives that provide adequate levels of disease control are needed to replace chemical fungicides-if not completely, then at least partially. A number of alternatives to conventional chemical fungicides have been developed, including plant defence elicitors (PDEs); biological control agents (fungi, bacteria, and mycoviruses), either alone or as consortia; biochemical fungicides; natural products; RNA interference (RNAi) methods; and resistance breeding. This article reviews the conventional and alternative methods available to manage fungal pathogens, discusses their strengths and weaknesses, and identifies potential areas for future research.

Evolutionary Epidemiology Consequences of Trait-Dependent Control of Heterogeneous Parasites

AbstractDisease control can induce both demographic and evolutionary responses in host-parasite systems. Foreseeing the outcome of control therefore requires knowledge of the eco-evolutionary feedback between control and system. Previous work has assumed that control strategies have a homogeneous effect on the parasite population. However, this is not true when control targets those traits that confer to the parasite heterogeneous levels of resistance, which can additionally be related to other key parasite traits through evolutionary trade-offs. In this work, we develop a minimal model coupling epidemiological and evolutionary dynamics to explore possible trait-dependent effects of control strategies. In particular, we consider a parasite expressing continuous levels of a trait-determining resource exploitation and a control treatment that can be either positively or negatively correlated with that trait. We demonstrate the potential of trait-dependent control by considering that the decision maker may want to minimize both the damage caused by the disease and the use of treatment, due to possible environmental or economic costs. We identify efficient strategies showing that the optimal type of treatment depends on the amount applied. Our results pave the way for the study of control strategies based on evolutionary constraints, such as collateral sensitivity and resistance costs, which are receiving increasing attention for both public health and agricultural purposes.

Expanding growers' choice of plant disease management options can promote suboptimal social outcomes

Previous models of growers' decision-making during epidemics have unrealistically limited disease management choices to just two options. Here, we expand previous game-theoretic models of grower decision-making to include three control options: a crop that is tolerant, resistant or susceptible to disease. Using tomato yellow leaf curl virus (TYLCV) as a case study, we investigate how growers can be incentivized to use different control options to achieve socially optimal outcomes. To do this, we consider the efforts of a 'social planner' who moderates the price of crops. We find that subsidizing a tolerant crop costs the social planner more in subsidies, as its use encourages selfishness and widespread adoption. Subsidizing a resistant crop, however, provides widespread benefits by reducing the prevalence of disease across the community of growers, including those that do not control, reducing the number of subsidies required from the social planner. We then use Gini coefficients to measure equitability of each subsidization scheme. This study highlights how grower behaviour can be altered using crop subsidies to promote socially optimal outcomes during epidemics.

ANTHRACNOSE RESISTANCE GENE2 confers fungal resistance in sorghum

Sorghum is an important food and feed crop globally; its production is hampered by anthracnose disease caused by the fungal pathogen Colletotrichum sublineola (Cs). Here, we report identification and characterization of ANTHRACNOSE RESISTANCE GENE 2 (ARG2) encoding a nucleotide-binding leucine-rich repeat (NLR) protein that confers race-specific resistance to Cs strains. ARG2 is one of a cluster of several NLR genes initially identified in the sorghum differential line SC328C that is resistant to some Cs strains. This cluster shows structural and copy number variations in different sorghum genotypes. Different sorghum lines carrying independent ARG2 alleles provided the genetic validation for the identity of the ARG2 gene. ARG2 expression is induced by Cs, and chitin induces ARG2 expression in resistant but not in susceptible lines. ARG2-mediated resistance is accompanied by higher expression of defense and secondary metabolite genes at early stages of infection, and anthocyanin and zeatin metabolisms are upregulated in resistant plants. Interestingly, ARG2 localizes to the plasma membrane when transiently expressed in Nicotiana benthamiana. Importantly, ARG2 plants produced higher shoot dry matter than near-isogenic lines carrying the susceptible allele suggesting an absence of an ARG2 associated growth trade-off. Furthermore, ARG2-mediated resistance is stable at a wide range of temperatures. Our observations open avenues for resistance breeding and for dissecting mechanisms of resistance.

How the epidemiology of disease-resistant and disease-tolerant varieties affects grower behaviour

Population-scale effects of resistant or tolerant crop varieties have received little consideration from epidemiologists. When growers deploy tolerant crop, population-scale disease pressures are often unaffected. This only benefits growers using tolerant varieties, selfishly decreasing yields for others. However, resistant crop can reduce disease pressure for all. We coupled an epidemiological model with game theory to understand how this affects uptake of control. Each time a grower plants a new crop, they must decide whether to use an improved (i.e. tolerant/resistant) or unimproved variety. This decision is based on strategic-adaptive expectations in our model, with growers comparing last season's profit with an estimate of what is expected from the alternative crop. Despite the positive feedback loop promoting use of a tolerant variety whenever it is available, a mixed unimproved- and tolerant-crop equilibrium can persist. Tolerant crop can also induce bistability between a scenario in which all growers use tolerant crop and the disease-free equilibrium, where no growers do. However, due to 'free-riding' by growers of unimproved crop, resistant crop nearly always exists in a mixed equilibrium. This work highlights how growers respond to contrasting incentives caused by tolerant and resistant varieties, and the distinct effects on yields and population-scale deployment.

Optimizing Plant Disease Management in Agricultural Ecosystems Through Rational In-Crop Diversification

Biodiversity plays multifaceted roles in societal development and ecological sustainability. In agricultural ecosystems, using biodiversity to mitigate plant diseases has received renewed attention in recent years but our knowledge of the best ways of using biodiversity to control plant diseases is still incomplete. In term of in-crop diversification, it is not clear how genetic diversity per se in host populations interacts with identifiable resistance and other functional traits of component genotypes to mitigate disease epidemics and what is the best way of structuring mixture populations. In this study, we created a series of host populations by mixing different numbers of potato varieties showing different late blight resistance levels in different proportions. The amount of naturally occurring late blight disease in the mixture populations was recorded weekly during the potato growing seasons. The percentage of disease reduction (PDR) in the mixture populations was calculated by comparing their observed late blight levels relative to that expected when they were planted in pure stands. We found that PDR in the mixtures increased as the number of varieties and the difference in host resistance (DHR) between the component varieties increased. However, the level of host resistance in the potato varieties had little impact on PDR. In mixtures involving two varieties, the optimum proportion of component varieties for the best PDR depended on their DHR, with an increasing skewness to one of the component varieties as the DHR between the component varieties increased. These results indicate that mixing crop varieties can significantly reduce disease epidemics in the field. To achieve the best disease mitigation, growers should include as many varieties as possible in mixtures or, if only two component mixtures are possible, increase DHR among the component varieties.

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.

Pre-emptive Breeding Against Karnal Bunt Infection in Common Wheat: Combining Genomic and Agronomic Information to Identify Suitable Parents

Wheat (Triticum aestivum L.) is the most widely grown cereal crop in the world and is staple food to half the world's population. The current world population is expected to reach 9.8 billion people by 2050, but food production is not expected to keep pace with demand in developing countries. Significant opportunities exist for traditional grain exporters to produce and export greater amounts of wheat to fill the gap. Karnal bunt, however, is a major threat, due to its use as a non-tariff trade barrier by several wheat-importing countries. The cultivation of resistant varieties remains the most cost-effective approach to manage the disease, but in countries that are free of the disease, genetic improvement is difficult due to quarantine restrictions. Here we report a study on pre-emptive breeding designed to identify linked molecular markers, evaluate the prospects of genomic selection as a tool, and prioritise wheat genotypes suitable for use as parents. In a genome-wide association (GWAS) study, we identified six DArTseq markers significantly linked to Karnal bunt resistance, which explained between 7.6 and 29.5% of the observed phenotypic variation. The accuracy of genomic prediction was estimated to vary between 0.53 and 0.56, depending on whether it is based solely on the identified Quantitative trait loci (QTL) markers or the use of genome-wide markers. As genotypes used as parents would be required to possess good yield and phenology, further research was conducted to assess the agronomic value of Karnal bunt resistant germplasm from the International Maize and Wheat Improvement Center (CIMMYT). We identified an ideal genotype, ZVS13_385, which possessed similar agronomic attributes to the highly successful Australian wheat variety, Mace. It is phenotypically resistant to Karnal bunt infection (<1% infection) and carried all the favourable alleles detected for resistance in this study. The identification of a genotype combining Karnal bunt resistance with adaptive agronomic traits overcomes the concerns of breeders regarding yield penalty in the absence of the disease.

Combining transcriptome analysis and GWAS for identification and validation of marker genes in the Physalis peruviana-Fusarium oxysporum pathosystem

Vascular wilt, caused by the pathogen Fusarium oxysporum f. sp. physali (Foph), is a major disease of cape gooseberry (Physalis peruviana L.) in Andean countries. Despite the economic losses caused by this disease, there are few studies related to molecular mechanisms in the P. peruviana—Foph pathosystem as a useful tool for crop improvement. This study evaluates eight candidate genes associated with this pathosystem, using real-time quantitative PCR (RT-qPCR). The genes were identified and selected from 1,653 differentially expressed genes (DEGs) derived from RNA-Seq analysis and from a previous genome-wide association study (GWAS) of this plant-pathogen interaction. Based on the RT-qPCR analysis, the tubuline (TUB) reference gene was selected for its highly stable expression in cape gooseberry. The RT-qPCR validation of the candidate genes revealed the biological variation in their expression according to their known biological function. Three genes related to the first line of resistance/defense responses were highly expressed earlier during infection in a susceptible genotype, while three others were overexpressed later, mostly in the tolerant genotype. These genes are mainly involved in signaling pathways after pathogen recognition, mediated by hormones such as ethylene and salicylic acid. This study provided the first insight to uncover the molecular mechanism from the P. peruviana—Foph pathosystem. The genes validated here have important implications in the disease progress and allow a better understanding of the defense response in cape gooseberry at the molecular level. Derived molecular markers from these genes could facilitate the identification of tolerant/susceptible genotypes for use in breeding schemes.

'Resistance Mixtures' Reduce Insect Herbivory in Strawberry (Fragaria vesca) Plantations

The transition toward more sustainable plant protection with reduced pesticide use is difficult, because there is no "silver bullet" available among nonchemical tools. Integrating several plant protection approaches may thus be needed for efficient pest management. Recently, increasing the genetic diversity of plantations via cultivar mixing has been proposed as a possible method to reduce pest damage. However, previous studies have not addressed either the relative efficiency of exploiting cultivar mixing and intrinsic plant herbivore resistance or the potential utility of combining these approaches to increase cropping security. Here, using a full factorial experiment with 60 woodland strawberry plots, we tested for the relative and combined effect of cultivar mixing and intrinsic plant resistance on herbivore damage and yield. The experiment comprised two levels of diversity ("high" with 10 varieties and "low" with two varieties) and three levels of resistance ("resistant" comprising only varieties intrinsically resistant against strawberry leaf beetle Galerucella tenella; "susceptible" with susceptible varieties only; and "resistance mixtures" with 50:50 mixtures of resistant and susceptible varieties). The experiment was carried out over two growing seasons. Use of resistant varieties either alone or intermixed with susceptible varieties in "resistance mixtures" reduced insect herbivory. Interestingly, resistant varieties not only reduced the mean damage in "resistance mixtures" by themselves being less damaged, but also protected intermixed susceptible varieties via associational resistance. The effect of higher genetic diversity was less evident, reducing herbivory only at the highest level of herbivore damage. In general, herbivory was lowest in plots with high diversity that included at least some resistant varieties and highest in low diversity plots consisting only of susceptible varieties. Despite this, no significant difference in yield (fruit biomass) was found, indicating that strawberry may be relatively tolerant. Our results demonstrate that combined use of high genetic diversity and resistant varieties can help reduce pest damage and provide a useful tool for sustainable food production. "Resistance mixtures" may be particularly useful for sensitive food crops where susceptible varieties are high yielding that could not be completely replaced by resistant ones.

An ecophysiological model of plant-pest interactions: the role of nutrient and water availability

Empirical studies have shown that particular irrigation/fertilization regimes can reduce pest populations in agroecosystems. This appears to promise that the ecological concept of bottom-up control can be applied to pest management. However, a conceptual framework is necessary to develop a mechanistic basis for empirical evidence. Here, we couple a mechanistic plant growth model with a pest population model. We demonstrate its utility by applying it to the peach-green aphid system. Aphids are herbivores which feed on the plant phloem, deplete plants' resources and (potentially) transmit viral diseases. The model reproduces system properties observed in field studies and shows under which conditions the diametrically opposed plant vigour and plant stress hypotheses find support. We show that the effect of fertilization/irrigation on the pest population cannot be simply reduced as positive or negative. In fact, the magnitude and direction of any effect depend on the precise level of fertilization/irrigation and on the date of observation. We show that a new synthesis of experimental data can emerge by embedding a mechanistic plant growth model, widely studied in agronomy, in a consumer-resource modelling framework, widely studied in ecology. The future challenge is to use this insight to inform practical decision making by farmers and growers.

Current Utility of Plant Growth-Promoting Rhizobacteria as Biological Control Agents towards Plant-Parasitic Nematodes

Plant-parasitic nematodes (PPN) are among the most economically and ecologically damaging pests, causing severe losses of crop production worldwide. Chemical-based nematicides have been widely used, but these may have adverse effects on human health and the environment. Hence, biological control agents (BCAs) have become an alternative option for controlling PPN, since they are environmentally friendly and cost effective. Lately, a major effort has been made to evaluate the potential of a commercial grade strain of plant growth-promoting rhizobacteria (PGPR) as BCAs, because emerging evidence has shown that PGPR can reduce PPN in infested plants through direct and/or indirect antagonistic mechanisms. Direct antagonism occurs by predation, release of antinematicidal metabolites and semiochemicals, competition for nutrients, and niche exclusion. However, the results of direct antagonism may be inconsistent due to unknown endogenous and exogenous factors that may prevent PGPR from colonizing plant's roots. On the other hand, indirect antagonism may occur from the induced systemic resistance (ISR) that primes whole plants to better fight against various biotic and abiotic constraints, actuating faster and/or stronger defense responses (adaption), enhancing their promise as BCAs. Hence, this review will briefly revisit (i) two modes of PGPR in managing PPN, and (ii) the current working models and many benefits of ISR, in the aim of reassessing current progresses and future directions for isolating more effective BCAs and/or developing better PPN management strategy.

Identification of Stem Rust Resistance Genes in the Winter Wheat Collection from Southern Russia

The high yield potential of winter wheats cannot be realized due to disease pressure under field conditions. One of the most harmful of such diseases is stem rust, hence the constant search for sources of resistance and the development of new varieties resistant to stem rust is of great relevance. This study deals with the identification of stem rust resistance genes in a collection of winter wheats grown in Southern Russia. This genepool has not been studied yet. A total of 620 samples of winter soft wheat from various ecological and geographical zones were tested under field conditions. To identify the specific genes or alleles responsible for resistance, all samples were genotyped using PCR. As a result, the groups of resistant samples, carrying the Sr2, Sr31, Sr38 and Sr44 genes in various combinations, were identified. Most of the stem rust resistance was provided by the presence of the effective Sr44 gene. This information can be used in the future breeding work for stem rust resistance.

Rhizosphere Microbiomes Modulated by Pre-crops Assisted Plants in Defense Against Plant-Parasitic Nematodes

Plant-parasitic nematodes cause considerable damage to crop plants. The rhizosphere microbiome can affect invasion and reproductive success of plant-parasitic nematodes, thus affecting plant damage. In this study, we investigated how the transplanted rhizosphere microbiome from different crops affect plant-parasitic nematodes on soybean or tomato, and whether the plant’s own microbiome from the rhizosphere protects it better than the microbiome from fallow soil. Soybean plants growing in sterilized substrate were inoculated with the microbiome extracted from the rhizosphere of soybean, maize, or tomato. Controls were inoculated with extracts from bulk soil, or not inoculated. After the microbiome was established, the root lesion nematode Pratylenchus penetrans was added. Root invasion of P. penetrans was significantly reduced on soybean plants inoculated with the microbiome from maize or soybean compared to tomato or bulk soil, or the uninoculated control. In the analogous experiment with tomato plants inoculated with either P. penetrans or the root knot nematode Meloidogyne incognita, the rhizosphere microbiomes of maize and tomato reduced root invasion by P. penetrans and M. incognita compared to microbiomes from soybean or bulk soil. Reproduction of M. incognita on tomato followed the same trend, and it was best suppressed by the tomato rhizosphere microbiome. In split-root experiments with soybean and tomato plants, a systemic effect of the inoculated rhizosphere microbiomes on root invasion of P. penetrans was shown. Furthermore, some transplanted microbiomes slightly enhanced plant growth compared to uninoculated plants. The microbiomes from maize rhizosphere and bulk soil increased the fresh weights of roots and shoots of soybean plants, and microbiomes from soybean rhizosphere and bulk soil increased the fresh weights of roots and shoots of tomato plants. Nematode invasion did not affect plant growth in these short-term experiments. In conclusion, this study highlights the importance of the rhizosphere microbiome in protecting crops against plant-parasitic nematodes. An effect of pre-crops on the rhizosphere microbiome might be harnessed to enhance the resistance of crops towards plant-parasitic nematodes. However, nematode-suppressive effects of a particular microbiome may not necessarily coincide with improvement of plant growth in the absence of plant-parasitic nematodes.

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs quickly after resistance is deployed, resulting in significant crop losses and a continuing need to develop new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolution of pathogen populations and thus increase genetic resistance durability. These strategies mainly rely on varying different combinations of resistance sources across time (crop rotations) and space. The spatial scale of deployment can vary from multiple resistance sources occurring in a single cultivar (pyramiding), in different cultivars within the same field (cultivar mixtures) or in different fields (mosaics). However, experimental comparison of the efficiency (i.e. ability to reduce disease impact) and durability (i.e. ability to limit pathogen evolution and delay resistance breakdown) of landscape-scale deployment strategies presents major logistical challenges. Therefore, we developed a spatially explicit stochastic model able to assess the epidemiological and evolutionary outcomes of the four major deployment options described above, including both qualitative resistance (i.e. major genes) and quantitative resistance traits against several components of pathogen aggressiveness: infection rate, latent period duration, propagule production rate, and infectious period duration. This model, implemented in the R package landsepi, provides a new and useful tool to assess the performance of a wide range of deployment options, and helps investigate the effect of landscape, epidemiological and evolutionary parameters. This article describes the model and its parameterisation for rust diseases of cereal crops, caused by fungi of the genus Puccinia. To illustrate the model, we use it to assess the epidemiological and evolutionary potential of the combination of a major gene and different traits of quantitative resistance. The comparison of the four major deployment strategies described above will be the objective of future studies.

There are many recent examples which demonstrate the evolutionary potential of plant pathogens to overcome the resistances deployed in agricultural landscapes to protect our crops. Increasingly, it is recognised that how resistance is deployed spatially and temporally can impact on rates of pathogen evolution and resistance breakdown. Such deployment strategies are mainly based on the combination of several sources of resistance at different spatiotemporal scales. However, comparison of these strategies in a predictive sense is not an easy task, owing to the logistical difficulties associated with experiments involving the spread of a pathogen at large spatio-temporal scales. Moreover, both the durability of a strategy and the epidemiological protection it provides to crops must be assessed since these evaluation criteria are not necessarily correlated. Surprisingly, no current simulation model allows a thorough comparison of the different options. Here we describe a spatio-temporal model able to simulate a wide range of deployment strategies and resistance sources. This model, implemented in the R package landsepi, facilitates assessment of both epidemiological and evolutionary outcomes across simulated scenarios. In this work, the model is used to investigate the combination of different sources of resistance against fungal diseases such as rusts of cereal crops.