Dynamics of primary and secondary infection in take-all epidemics

ABSTRACT Using a combination of experimentation and mathematical modeling, the effects of initial (particulate) inoculum density on the dynamics of disease resulting from primary and secondary infection of wheat by the take-all fungus, Gaeumannomyces graminis var. tritici, were tested. A relatively high inoculum density generated a disease progress curve that rose monotonically toward an asymptote. Reducing the initial inoculum density resulted in a curve that initially was monotonic, rising to a plateau, but which increased sigmoidally to an asymptotic level of disease thereafter. Changes in the infectivity of particulate inoculum over time were examined in a separate experiment. Using a model that incorporated terms for primary and secondary infection, inoculum decay, and host growth, we showed that both disease progress curves were consistent with consecutive phases dominated, respectively, by primary and secondary infection. We examined the spread of disease from a low particulate inoculum density on seminal and adventitious root systems separately. Although seminal roots were affected by consecutive phases of primary and secondary infection, adventitious roots were affected only by secondary infection. We showed that the characteristic features of disease progress in controlled experiments were consistent with field data from crops of winter wheat. We concluded that there is an initial phase of primary infection by G. graminis var. tritici on winter wheat as seminal roots grow through the soil and encounter inoculum, but the rate of primary infection slows progressively as inoculum decays. After the initial phase, there is an acceleration in the rate of secondary infection on both seminal and adventitious roots that is stimulated by the increase in the availability of infected tissue as a source of inoculum and the availability of susceptible tissue for infection.     

An Epidemiological Analysis of the Role of Disease-Induced Root Growth in the Differential Response of Two Cultivars of Winter Wheat to Infection by Gaeumannomyces graminis var. tritici

ABSTRACT Epidemiological modeling combined with parameter estimation of experimental data was used to examine differences in the contribution of disease-induced root production to the spread of take-all on plants of two representative yet contrasting cultivars of winter wheat, Ghengis and Savannah. A mechanistic model, including terms for primary infection, secondary infection, inoculum decay, and intrinsic and disease-induced root growth, was fitted to data describing changes in the numbers of infected and susceptible roots over time at a low or high density of inoculum. Disease progress curves were characterized by consecutive phases of primary and secondary infection. No differences in root growth were detected between cultivars in the absence of disease and root production continued for the duration of the experiment. However, significant differences in disease-induced root production were detected between Savannah and Genghis. In the presence of disease, root production for both cultivars was characterized by stimulation when few roots were infected and inhibition when many roots were infected. At low inoculum density, the transition from stimulation to inhibition occurred when an average of 5.0 and 9.0 roots were infected for Genghis and Savannah, respectively. At high inoculum density, the transition from stimulation to inhibition occurred when an average of 4.5 and 6.7 roots were infected for Genghis and Savannah, respectively. Differences in the rates of primary and secondary infection between Savannah and Genghis also were detected. At a low inoculum density, Genghis was marginally more resistant to secondary infection whereas, at a high density of inoculum, Savannah was marginally more resistant to primary infection. The combined effects of differences in disease-induced root growth and differences in the rates of primary and secondary infection meant that the period of stimulated root production was extended by 7 and 15 days for Savannah at a low and high inoculum density, respectively. The contribution of this form of epidemiological modeling to the better management of take-all is discussed.     

Effect of crop growth and canopy filtration on the dynamics of plant disease epidemics spread by aerially dispersed spores

Most mathematical models of plant disease epidemics ignore the growth and phenology of the host crop. Unfortunately, reports of disease development are often not accompanied by a simultaneous and commensurate evaluation of crop development. However, the time scale for increases in the leaf area of field crops is comparable to the time scale of epidemics. This simultaneous development of host and pathogen has many ramifications on the resulting plant disease epidemic. First, there is a simple dilution effect resulting from the introduction of new healthy leaf area with time. Often, measurements of disease levels are made pro rata (per unit of host leaf area or total root length or mass). Thus, host growth will reduce the apparent infection rate. A second, related effect, has to do with the so-called "correction factor," which accounts for inoculum falling on already infected tissue. This factor accounts for multiple infection and is given by the fraction of the host tissue that is susceptible to disease. As an epidemic develops, less and less tissue is open to infection and the initial exponential growth slows. Crop growth delays the impact of this limiting effect and, therefore, tends to increase the rate of disease progress. A third and often neglected effect arises when an increase in the density of susceptible host tissue results in a corresponding increase in the basic reproduction ratio, R(0), defined as the ratio of the total number of daughter lesions produced to the number of original mother lesions. This occurs when the transport efficiency of inoculum from infected to susceptible host is strongly dependent on the spatial density of plant tissue. Thus, crop growth may have a major impact on the development of plant disease epidemics occurring during the vegetative phase of crop growth. The effects that these crop growth-related factors have on plant disease epidemics spread by airborne spores are evaluated using mathematical models and their importance is discussed. In particular, plant disease epidemics initiated by the introduction of inoculum during this stage of development are shown to be relatively insensitive to the time at which inoculum is introduced.     

Epidemiology and chemical control of take-all on seminal and adventitious roots of wheat

ABSTRACT Epidemiological modeling is used to examine the effect of silthiofam seed treatment on field epidemics of take-all in winter wheat. A simple compartmental model, including terms for primary infection, secondary infection, root production, and decay of inoculum, was fitted to data describing change in the number of diseased and susceptible roots per plant over thermal time obtained from replicated field trials. This produced a composite curve describing change in the proportion of diseased roots over time that increased monotonically to an initial plateau and then increased exponentially thereafter. The shape of this curve was consistent with consecutive phases of primary and secondary infection. The seed treatment reduced the proportion of diseased roots throughout both phases of the epidemic. However, analysis with the model detected a significant reduction in the rate of primary, but not secondary, infection. The potential for silthiofam to affect secondary infection from diseased seminal or adventitious roots was examined in further detail by extending the compartmental model and fitting to change in the number of diseased and susceptible seminal or adventitious roots. Rates of secondary infection from either source of infected roots were not affected. Seed treatment controlled primary infection of seminal roots from particulate inoculum but not secondary infection from either seminal or adventitious roots. The reduction in disease for silthiofam-treated plants observed following the secondary infection phase of the epidemic was not due to long-term activity of the chemical but to the manifestation of disease control early in the epidemic.     

Modeling and analysis of disease-induced host growth in the epidemiology of take-all

ABSTRACT Epidemiological modeling, together with parameter estimation to experimental data, was used to examine the contribution of disease-induced root growth to the spread of take-all in wheat. Production of roots from plants grown in the absence of disease was compared with production of those grown in the presence of disease and the precise form of diseaseinduced growth was examined by fitting a mechanistic model to data describing change in the number of infected and susceptible roots over time from a low and a high density of inoculum. During the early phase of the epidemic, diseased plants produced more roots than their noninfected counterparts. However, as the epidemic progressed, the rate of root production for infected plants slowed so that by the end of the epidemic, and depending on inoculum density, infected plants had fewer roots than uninfected plants. The dynamical change in the numbers of infected and susceptible roots over time could only be explained by the mechanistic model when allowance was made for disease-induced root growth. Analysis of the effect of disease-induced root production on the spread of disease using the model suggests that additional roots produced early in the epidemic serve only to reduce the proportion of diseased roots. However, as the epidemic switches from primary to secondary infection, these roots perform an active role in the transmission of disease. Some consequence of disease-induced root growth for field epidemics is discussed.     

Temporal and Spatial Dynamics of Primary and Secondary Infection by Armillaria ostoyae in a Pinus pinaster Plantation

ABSTRACT Epidemiological investigations were performed in a 3-ha maritime pine (Pinus pinaster) plantation established on a site heavily infested by Armillaria ostoyae. Geostatistics were used to examine the density and the distribution of the initial inoculum. Disease dynamics were monitored for 17 years after planting. On the whole site, the cumulative mortality rate reached 35% over this period, plateauing at 12 years. Disease progress curves differed according to the density of the initial inoculum, although in all the cases, the Gompertz model described the epidemics well. The epidemiological contributions of both primary (initially colonized stumps) and secondary inoculum (newly dead pines) were evaluated by analyzing their spatial relation to annual mortality. Newly dead pines acted as secondary inoculum from year 3 and their role increased with time. When the initial inoculum density was low, the contribution of secondary inoculum to epidemic development increased faster and halted sooner than when the density of primary inoculum was high. Regardless of its density, the primary inoculum acted throughout the dynamic phase of the epidemic. When the inoculum density was low, the probability of mortality during the first 6 years of the epidemic depended on the tree distance from the nearest stumps colonized by Armillaria sp. When the inoculum density was high, the probability of mortality was higher and not related to the distance between trees and colonized stumps.     

Field studies of anthracnose symptoms and pathogen infection in different phases of the persimmon growing season

Anthracnose is the main disease of persimmon and is caused by Colletotrichum spp. The study of field epidemiology is essential for the development of efficient management of this disease. In this study, we investigated infection by Colletotrichum spp. throughout the persimmon growing season to understand the host–pathogen interactions better. We observed the production of primary inoculum of persimmon anthracnose and described how epidemics progress from secondary infections during the fruit crop season. The field study was carried out in an organic orchard with three susceptible persimmon cultivars, Fuyu, Kakimel and Jiro, for three consecutive seasons. Our results indicate that the pathogen survives in 1-year-old shoots, which are the sources of primary inoculum. Later that growing season, the inoculum reaches flowers and new shoots, developing symptoms and producing the secondary inoculum. Fruit drop was also observed, with or without symptoms of anthracnose, throughout the plant cycle. In some of the symptomless fruit, collected from the plant and from the ground where they had fallen, latent infections of Colletotrichum spp. were detected. Shoots, flowers, immature and ripened fruit remained infected throughout the growing season, producing conidia that could lead to new secondary infections within and among plants. The incidence of anthracnose in fruit at harvest and postharvest proved to be less relevant for disease management. Practices for chemical and cultural control of the disease throughout the persimmon growing season are discussed.     

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.     

Modelling the progress of light leaf spot (Pyrenopeziza brassicae) on winter oilseed rape (Brassica napus) in relation to leaf wetness and temperature

A compartmental model was developed to describe the progress with time of light leaf spot ( Pyrenopeziza brassicae ) on leaves of winter oilseed rape ( Brassica napus ) during the autumn in the UK. Differential equations described the transition between the four compartments: healthy susceptible leaves, infected symptomless leaves, sporulating symptomless leaves and leaves with necrotic light leaf spot lesions, respectively. The model was fitted to data on the progress of light leaf spot on winter oilseed rape at a single site during the autumn of the 1990–1991 season. Model parameters were used to describe rates of leaf appearance, leaf death, infection by airborne ascospores (primary inoculum) and infection by splash-dispersed conidiospores (secondary inoculum). Infection was dependent on sufficient leaf wetness duration. The model also included delay terms for the latent period between infection and sporulation and the incubation period between infection and the appearance of necrotic light leaf spot lesions. This modified SEIR model formulation gave a reasonable fit to the experimental data. Sensitivity analysis showed that varying the parameter accounting for the rate of infection by ascospores affected the magnitude of the curves after the start of the epidemic, whilst including a parameter for conidiospore infection improved the fit to the data. Use of ascospore counts from different sites and different years showed variation in spore release patterns sufficient to affect model predictions.     

Temporal and spatial aspects of the epidemiology of sorghum downy mildew on maize

The development of systemic disease from primary inoculum sources of sorghum downy mildew was studied on field-grown maize in Thailand. Data were recorded five times, from the first appearance of disease until 5 weeks after plant emergence. The incidence of diseased plants decreased with increasing distance from the primary inoculum sources, and the slope of the gradient flattened as the epidemic progressed. The steepest gradient of disease incidence was observed downwind. The progress in time and spread in space of disease about primary foci is described by three non-linear models which fit the data equally well. However, the resulting gradients at wider distances are different. With two models the gradients decrease asymptotically to zero with increasing distance, whilst the other model leads to negative values above a certain distance. The rates of isopath movement of all models decrease with time, but the effect of distance on the isopathic rate is different; the rate can decrease, stay constant or increase with distance.     

Spatial and temporal spread of powdery mildew (Erysiphe pisi) in peas (Pisum sativum) varying in quantitative resistance

A field experiment was conducted to assess the progress in time and spread in space of powdery mildew (caused by Erysiphe pisi ) in pea ( Pisum sativum ) cultivars differing in resistance to the disease. Disease severity (proportion of leaf area infected) was measured in 19 × 23 m plots of cultivars Pania and Bolero (both susceptible) and Quantum (quantitatively resistant). Inoculum on infected plants was introduced into the centre of each plot. Leaves (nodes) were divided into three groups within the canopy (lower, middle, upper) at each assessment because of the large range in disease severity vertically within the plants. Disease severity on leaves at upper nodes was less than 4% until the final assessment 35 days after inoculation. Exponential disease progress curves were fitted to disease severity data from leaves at middle nodes. The mean disease relative growth rate was greater on Quantum than on Pania or Bolero, but it was delayed, resulting in an overall lower disease severity on Quantum. Gompertz growth curves were fitted to disease progress on leaves at lower nodes. Disease progress on Quantum was delayed compared with Pania and Bolero. The average daily rates of increase in disease severity from Gompertz curves did not differ between the cultivars on these leaves. Disease gradients in the plots from the inoculum focus to 12 m were detected at early stages of the epidemic, but the effects of background inoculum inputs and the rate of disease progress meant that these gradients decreased with time as the disease epidemic intensified. Spread was rapid, and there were no statistically significant differences between cultivar isopathic rates (Pania 2.2, Quantum 2.9 and Bolero 4.0 m d⁻¹).     

Simulation of Epidemics Caused by Venturia inaequalis (Cooke) Aderh.1

We discuss simulation of apple scab epidemics based on analog computer models, multivariate regression analyses, and systems analyses. Details of underlying models and their scope for applications are emphasized. Monomolecular growth functions by Bertalanffy and Gompertz in analog computers permit fast simulation of disease progress curves. The models derived from multivariate analyses of field experiments on apple scab epidemics simulate closely the changes in infection rates. EPIVEN, our comprehensive and self–generating simulator of apple scab epidemics is reviewed and compared to a reduced model, also based on elements of the system “apple scab epidemic”.     

Characterization of early leaf spot suppression by strip tillage in peanut

ABSTRACT Epidemics of early leaf spot of peanut (Arachis hypogaea), caused by Cercospora arachidicola, are less severe in strip-tilled than conventionally tilled fields. Experiments were carried out to characterize the effect of strip tillage on early leaf spot epidemics and identify the primary target of suppression using a comparative epidemiology approach. Leaf spot intensity was assessed weekly as percent incidence or with the Florida 1-to-10 severity scale in peanut plots that were conventionally or strip tilled. The logistic model, fit to disease progress data, was used to estimate initial disease (y(0)) and epidemic rate (r) parameters. Environmental variables, inoculum abundance, and field host resistance were assessed independently. For experiments combined, estimated y(0) was less in strip-tilled than conventionally tilled plots, and r was comparable. The epidemic was delayed in strip-tilled plots by an average of 5.7 and 11.7 days based on incidence and severity, respectively. Tillage did not consistently affect mean canopy temperature, relative humidity, or frequency of environmental records favorable for infection or spore dispersal. Host response to infection was not affected by tillage, but infections were detected earlier and at higher frequencies with noninoculated detached leaves from conventionally tilled plots. These data suggest that strip tillage delays early leaf spot epidemics due to fewer initial infections; most likely a consequence of less inoculum being dispersed to peanut leaves from overwintering stroma in the soil.     

Epidemiological studies on cercospora leaf spot of sugar beet

In the glasshouse, inoculation of sugar beet with Cercospora beticola followed by 16 h of high humidity produced visible disease only with at least four conidia per cm² of leaf area. Disease became more severe after increasing periods of high humidity in the range of 0–24 h. In the field, spraying plants with water enhanced disease spread from a focus. Disease progress curves were sigmoid. Apparent infection rate declined towards the end of the season, possibly because of high temperature. In approximate agreement with prediction, epidemic development was delayed when initial inoculum was reduced. Reduced infection, resulting from either reduced initial inoculum or delayed inoculation, decreased the adverse effect of disease on sugar yield.     

Modulation of primary and secondary infections in epidemics of carrot cavity spot through agronomic management practices

The relative importance of primary and secondary infections (auto- and alloinfections) in the development of a carrot cavity spot (CCS) epidemic caused by Pythium spp. were investigated. Three cropping factors: fungicide application, soil moisture and planting density, were selected as the key variables affecting the disease tetrahedron. Their effects on: (i) disease measurements at a specific time, (ii) the areas under the disease progress curves (AUDPCs) and (iii) a time-dependent parameter in a pathometric incidence-severity relationship, were studied. Mefenoxam applications 5 and 9 weeks after sowing reduced the intensity of a field CCS epidemic that involved both primary and secondary infections. In microcosm experiments, mefenoxam reduced secondary infections by Pythium violae obtained by transplanting infected carrot roots and slowed disease progress (1·6 lesions per root in treated versus 5·8 lesions in non-treated microcosms). A deficit of soil moisture limited the movement of Pythium propagules to host tissue, and thus reduced primary infections in the field; it also promoted the healing of lesions, limiting lesion expansion and the potential for alloinfections (6·8–7·5 lesions per root in irrigated plots compared with 2·4 lesions in non-irrigated plots). A negative relationship between the mean root-to-root distance and the rate of alloinfections was established in microcosms; a reduction in mean planting density was also effective in limiting CCS development (0·5, 1·6 and 2·0 lesions per root in microcosms containing 8, 16 and 31 roots, respectively). An integrated disease management system based on a combination of cultural methods, such as optimized fungicide application, date of harvest versus soil moisture content, and host density versus planting pattern, may make a useful contribute to the control of CCS.     

Trends in Theoretical Plant Epidemiology

We review trends and advances in three specific areas of theoretical plant epidemiology: models of temporal and spatial dynamics of disease, the synergism of epidemiology and population genetics, and progress in statistical epidemiology. Recent analytical modelling of disease dynamics has focused on SIR (susceptible–infected–removed) models modified to include spatial structure, stochasticity, and multiple management-related parameters. Such models are now applied routinely to derive threshold criteria for pathogen invasion or persistence based on pathogen demographics (e.g., Allee effect or fitness of fungicide-resistant strains) and/or host spatial structure (e.g., host density or patch size and arrangement). Traditionally focused on the field level, the scale of analytical models has broadened to range from individual plants to landscapes and continents; however, epidemiological models for interactions at the cellular level, e.g., during the process of virus infection, are still rare. There is considerable interest in the concept of scaling, i.e., to what degree and how data and models from one scale can be transferred to another (smaller or larger) scale. Despite assertions to the contrary, the linkages between epidemiology and population genetics are alive and well as exemplified by recent efforts to integrate epidemiological parameters into population genetics models (and vice versa) and by numerous integrated studies with an applied focus (e.g., to quantify sources and types of primary and secondary inoculum). Statistical plant epidemiology continues to rely heavily on the medical and ecological fields for inspiration and conceptual advances, as illustrated by the recent surge in papers utilizing ROC (receiver operating characteristic), Bayesian, or survival analysis. Among these, Bayesian analysis should prove especially fruitful given the reliance on uncertain and subjective information for practical disease management. However, apart from merely adopting statistical tools from other disciplines, plant epidemiologists should be more proactive in exploring potential applications of their concepts and procedures in rapidly expanding disciplines such as statistical genetics or bioinformatics. Although providing the scientific basis for disease management will always be the raison d’être for plant epidemiology, a broader perspective will help the discipline to remain relevant as more resources are being devoted to genomic and ecosystem-level science.     

Alternative inoculum sources for fire blight: the potential role of fruit mummies and non‐host plants

Fire blight is the most damaging bacterial disease in apple production worldwide. Cankers and symptomless infected shoots are known as sites for the overwintering of Erwinia amylovora, subsequently providing primary inoculum for infection in the spring. In the present work, further potential sources of inoculum were investigated. Real‐time PCR assays covering a 3‐year‐period classified 19·9% of samples taken from fruit mummies as positive. Bacterial abundance in fruit mummies during autumn, winter and spring was up to 10⁹ cells per gram of tissue and correlated well with later infection rates of blossoms. Blossoms of non‐host plants growing close to infected trees were also shown to be colonized by E. amylovora and to enable epiphytic survival and propagation of bacteria. The results indicate a potential role of fruit mummies and buds in overwintering and as a source of primary inoculum for dissemination of the pathogen early in the growing season. Non‐host blossoms may also serve as an inoculum source in the build‐up of the pathogen population. Both aspects may contribute significantly to the epidemiology of E. amylovora. The significance of infected rootstocks as an inoculum source is also discussed. Fruit mummies might be used to determine pathogen pressure in an orchard before the beginning of the blooming period.     

Wintering of the biotrophic fungus Puccinia lagenophorae within the annual plant Senecio vulgaris: implications for biological weed control

Epidemics of the obligate biotrophic fungus Puccinia lagenophorae might be used to control populations of the annual plant, groundsel, Senecio vulgaris . Insight into the mechanisms of survival of P. lagenophorae over winter may help to explain the number of inoculum sources, and their strength (assessed by number and size of pustules), present in an S. vulgaris population in spring, indicating the probability and rate of progress of a subsequent epidemic. Results of the study indicated survival of the rust as mycelium within the host over winter. Survival outside the host is unlikely, because aecidiospores lost their capacity to germinate over winter and teliospores have not been reported to be infectious. Survival of S. vulgaris plants over winter was reduced by rust infection in autumn. The mortality of S. vulgaris was 30–100% depending on the date of infection. All plants infected early in autumn died but those infected late in autumn were more likely to survive. In turn, poor survival of the host impacted on the survival of P. lagenophorae over winter. Consequently, the results of the study suggest that no inoculum sources, or only a few weak ones, are present in vulgaris populations in spring. This suggestion was supported by observations of an S. vulgaris population at a ruderal site. Therefore, research on biological weed control should focus on increasing the negative impact of P. lagenophorae on S. vulgaris populations while augmenting the probability of survival of the rust over winter to start new epidemics in spring.     

Contribution of molecular studies to botanical epidemiology and disease modelling: grapevine downy mildew as a case-study

After being accidentally introduced from the USA at the end of the 19^th century, downy mildew caused by Plasmopara viticola (Berk. et Curt.) Berlese et De Toni became one of the most damaging diseases affecting Vitis vinifera in Europe. Downy mildew causes both direct and indirect losses and can lead to severe reduction of yield. Our understanding of the life cycle and epidemiology of P. viticola has been recently altered by molecular studies that revealed that the overwintering inoculum (i.e., the oospores) does more than initiate disease, as was previously thought. A mechanistic model was developed for predicting the entire chain of processes leading to primary infections, and this primary infection model was linked to other models of secondary infection cycles. The model for primary infections defines the length of the primary inoculum season and a seasonal oospore dose consisting of several cohorts of oospores that progressively mature. The model was evaluated by means of Bayesian analysis in both Italy and eastern Canada, and showed high sensitivity, specificity, and accuracy both for potted plants and vineyards. Fungicide applications are necessary to control downy mildew because preventive agronomic practices are not very effective, including host resistance. The use of warning systems based on weather-driven models leads to a reduction in the use and cost of chemicals and a reduction in their environmental impact.