Botanical Epidemiology Research Articles

Plant Disease Models and Forecasting: Changes in Principles and Applications Over the Last 50 Years.

This review gives a perspective of selected advances made since the middle of the 20th century in plant disease modeling, and the associated increase in the number of models published during that time frame. This progress can be mainly attributed to advances in (i) sensors and automatic environmental data collection technology, (ii) instrumentation and methods for studying botanical epidemiology, and (iii) data analytics and computer science. We review the evolution of techniques for developing data-based (empirical) models and process-based (mechanistic) models using the wheat rusts as a case study. We also describe the increased importance of knowledge about biological processes for plant disease modeling by using apple scab as a second case study. For both wheat rusts and apple scab, we describe how the models have evolved over the last 50 years by considering certain milestones that have been achieved in disease modeling. Finally, we describe how plant disease models are used as part of a multi-modeling approach to develop decision-making tools in the application of integrated pest management.

Amplifier Hosts May Play an Essential Role in Tomato Begomovirus Epidemics in Brazil.

Current control of tomato golden mosaic disease, caused in Brazil predominantly by tomato severe rugose virus (ToSRV), is dependent on both, planting resistant/tolerant hybrids and intensive insecticide sprays (two to three per week) for controlling Bemisia tabaci, the vector of ToSRV. Resistant hybrids only confer moderate resistance to infection by ToSRV and some tolerance to the disease. Insecticide sprays, although widely used, have failed in most tomato production areas in Brazil, as they are unable to reduce primary spread, i.e., infection caused by the influx of viruliferous whiteflies coming from external sources of inoculum. Severe epidemics are recurrently observed in some tomato fields in several Brazilian regions, which prompted us to postulate the existence in the agroecosystem, in some places and time, of amplifier hosts that provide the necessary force of infection for epidemics to occur, even in the absence of secondary spread in the target crop. Amplifier hosts are ideally asymptomatic, occur in high density near the target crop, and support growth of both virus and vector. Soybean and common bean are potential amplifier hosts for begomovirus in tomato crops. Our results support the hypothesis that soybean plants may play an important role as an amplifier host of ToSRV for tomato crops in the field, although this does not seem to be a frequent phenomenon. Successful amplification will depend on several factors, including the soybean cultivar, the soybean stage of development at the moment of infection, the ToSRV isolate, and the perfect synchrony between the beginning of a soybean field and the end of a ToSRV-infected crop, and, later, between the senescence of the ToSRV-infected soybean plants and the new tomato crop. The concept of amplifier hosts has been widely used in ecology of zoonoses but, to our knowledge, has never been used in botanical epidemiology.

The importance of primary inoculum and area-wide disease management to crop health and food security

In some epidemics that have devastating consequences, the primary inoculum plays an important role in both epidemic onset and intensification. This article documents the dynamics of such epidemics, and illustrates their importance using two examples: Huanglongbing of citrus and begomoviruses of tomato. The latter disease is a major constraint to tomato production in Brazil, while the former has become a threat to global citrus production and farmers’ livelihoods. In spite of their importance little is known of the characteristics of these diseases and their management. This is because classical botanical epidemiology considers two types of diseases: polycyclic diseases, where the inoculum that causes infections is produced during the epidemic in or on individual plants that had been previously infected in the course of that epidemic; or monocyclic diseases, where inoculum that causes infection is not produced in or on individual plants that had been infected in the course of the epidemic, but in the soil, on secondary hosts, or in infected crop plants of the same host in other fields. Diseases of the first type typically present a logistic disease progress curve and management is based on reducing the rate of infection, whereas diseases of the second type present a monomolecular disease progress curve and management is based on reducing the initial inoculum. This article deals with plant diseases that depart in their structure and behaviour from these two archetypes, because they borrow elements from both. We address polycyclic diseases in which the primary inoculum has a continuous and dynamic role, and in which the secondary inoculum contributes to epidemic build-up, i.e., polycyclic diseases with continuous primary spread. This epidemiological structure generates less clear-cut disease progress curves, but usually follows a monomolecular dynamic. Our focus on this type of disease is multifold because (1) this more complex, combined, pattern is actually quite common, often leading to grave plant diseases epidemics, with impacts at the farm, community, and country scales, and (2) such epidemics are among the most difficult to manage. Our analysis leads us to assess past errors and current courses of action. It allows us to recognize, in addition to the conventional tools for management with local effects, the critical importance of collective action. Collective management action – at the farm, community, or national scales – is congruent with the characteristics of many epidemics, because they also entail properties at successive and nested scales. The management of such epidemics needs to address both the primary and secondary inoculum. More importantly, these actions have to be performed in an area-wide, regional basis in order to be effective.

On a combinatorial problem in botanical epidemiology

In botanical epidemiology, one of the major problems is to study the spread of diseases within crops. Several approaches to study the patterns and temporal evolution of diseases have been discussed in the literature, e.g., statistical techniques or variogram analysis. Recently, AlSharawi, Burstein, Deadman and Umar determined the total number of ways to have ℓ isolated infected individuals among m infected plants in a row of n plants. They discussed this in a straightforward combinatorial fashion and considered several associated points, like expectation value and variance of the number of isolated infected plants. In the present paper, we derive their results with the help of generating function techniques and use this method to extend the discussion to plants arranged in a circle as well as in two rows. The dependence of the expected number of isolated infected plants on the proportion of infected plants is considered for large n in all these cases as well as in the case of an arbitrary number of rows and a simple asymptotic behavior is found. Connections to several combinatorial sequences are established.

The solution of a recursive sequence arising from a combinatorial problem in botanical epidemiology

One of the central problems in botanical epidemiology is whether disease spreads within crops in a regular pattern or follows a random process. In this study, we consider a row of n plants in which m are infected. We then develop a rigorous mathematical approach to investigate the total number of ways to obtain k isolated individuals among m infected plants. We give a recurrence relation in three parameters that describes the problem, then we find a closed-form solution, and give two different approaches to tackle the proof. Finally, we find interesting formulae for the expectation and variance of the random variable that represents the number of infected and isolated plants.

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 19th 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.

Risk Factors for Crop Health Under Global Change and Agricultural Shifts: A Framework of Analyses Using Rice in Tropical and Subtropical Asia as a Model

Plant disease epidemiology requires expansion of its current methodological and theoretical underpinnings in order to produce full contributions to global food security and global changes. Here, we outline a framework which we applied to farmers' field survey data set on rice diseases in the tropical and subtropical lowlands of Asia. Crop health risks arise from individual diseases, as well as their combinations in syndromes. Four key drivers of agricultural change were examined: labor, water, fertilizer, and land availability that translate into crop establishment method, water shortage, fertilizer input, and fallow period duration, respectively, as well as their combinations in production situations. Various statistical approaches, within a hierarchical structure, proceeding from higher levels of hierarchy (production situations and disease syndromes) to lower ones (individual components of production situations and individual diseases) were used. These analyses showed that (i) production situations, as wholes, represent very large risk factors (positive or negative) for occurrence of disease syndromes; (ii) production situations are strong risk factors for individual diseases; (iii) drivers of agricultural change represent strong risk factors of disease syndromes; and (iv) drivers of change, taken individually, represent small but significant risk factors for individual diseases. The latter analysis indicates that different diseases are positively or negatively associated with shifts in these drivers. We also report scenario analyses, in which drivers of agricultural change are varied in response to possible climate and global changes, generating predictions of shifts in rice health risks. The overall set of analyses emphasizes the need for large-scale ground data to define research priorities for plant protection in rapidly evolving contexts. They illustrate how a structured theoretical framework can be used to analyze emergent features of agronomic and socioecological systems. We suggest that the concept of "disease syndrome" can be borrowed in botanical epidemiology from public health to emphasize a holistic view of disease in shifting production situations in combination with the conventional, individual disease-centered perspective.

Botanical Epidemiology: Some Key Advances and its Continuing Role in Disease Management

Botanical Epidemiology: Some Key Advances and its Continuing Role in Disease Management

Antagonistic interactions involving plant pathogens: fitting and analysis of models to non‐monotonic curves for population and disease dynamics

summaryNonlinear models were fitted to selected data sets, obtained from published papers, in which inoculum of a fungal plant pathogen or microbial antagonist of a pathogen increased and then decreased with time. Conventional models that have been widely used in botanical epidemiology, such as the logistic, monomolecular and Weibull functions, could not be fitted to these non‐monotonic curves. Two models, the over‐damped in which Y=A+B exp (α1t +C exp (α2t), and the critically damped in which Y=A+ (B+Ct) exp (–λt), were fitted: Y is a measure of the pathogen or antagonist, t is time, A is an asymptote, B and C are locational parameters and α1, 2 and λ are rate parameters. These models are standard solutions of a second order differential equation. They have a single cycle, involving a rise and subsequent decline in the population density of the micro‐organism which ultimately tends to an asymptotic equilibrium. The over‐damped model was successful only in fitting large data‐sets and was used to describe the population dynamics of bacterial colonization of live‐ and heat‐killed conidia of Cochliobolus sativus (Ito & Kurib.). Drechs. ex Dastur as well as the population dynamics of Laetisaria arvalis Burdsall in untreated and in pasteurized soil with and without subsequent reinfestation with Pythium ultimum Trow. The critical damping model was used to describe pre‐emergence damping‐off of Rhizoctonia solani Kühn in successive crops of radish, the population dynamics of P. ultimum and low‐temperature Pythium spp. in untreated soil and pasteurized soil with L. arvalis, the population dynamics of Trichoderma viride Pers. ex S. F. Gray in plant growth media and, similarly, of Macrophomina phaseolina (Maub.) Ashby in soil and, lastly, the colonization of organic fragments by P. ultimum with and without antagonism from P. nunn Lifshitz, Stanghellini & Baker. The selected model was first fitted to the empirical progress curve for each treatment. Subsequently one or more common parameters were constrained to fit all treatments while the remaining parameters were fitted separately. None of the treatments affected the rate parameters but treatments did affect the asymptote and locational parameters. The shapes of the models are discussed in relation to initial amounts of inoculum, the initial rate of increase of inoculum and the time to achieve maximum levels of disease or microbial biomass. The over‐damping model is shown to represent the solution of a set of simple linked differential equations for two interacting populations. The derivation of these elementary models is discussed in relation to the study of biological control of plant pathogens.

Twenty-five years of botanical epidemiology

Epidemiological models in plant pathology usually belong to the family of logistic equations, describing the increase in disease intensity with time. Expansion and refinement are possible by applying dynamic simulation techniques on digital computers. Among these are models of disease increase in time and two-dimensional (horizontal) space, and spore dispersal in and over a crop in two-dimensional (vertical) space. Recently, an analytical model was developed by Van den Bosch and co-workers to describe focus expansion in time and two-dimensional (horizontal) space as a function of three biological parameters that were relatively easy to measure: gross reproduction, time kernel, and contact distribution. The model was tested using data from previous experiments not designed for this purpose and from a new experiment specifically designed for validation. The model treats focus expansion as a process with a constant radial velocity and seems valid on a small scale of a few metres and, after rescaling, on a large scale of hundreds of kilometres.

Teaching botanical epidemiology at the Agricultural University, Wageningen

Within the phytopathology curriculum the epidemiology teaching got its own place. A general outline of the curriculum, the prerequisites, and the courses is given, with details on the epidemiological courses. The student's opportunities foi practice and research are indicated. Didactical notes are given. The objectives of epidemiology teaching in Wageningen are stated in terms of the intended terminal behaviour of the phytopatologist specialized in epidemiology.