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Plant Disease Epidemiology
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Epidemic and Epidemiology
Epidemic A phenomenon when a pathogen spreads to and affects many individuals within a population over a relatively large area and within a relatively short time. (The dynamics of change in plant disease in time and space.)
Epidemiology
The study of epidemics and the factors that influence them.
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Elements of an Epidemic 1. 2. 3.
Host Pathogen Environment Interactions of the 3 main components are described by the disease triangle.
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The Disease Triangle
Source: Agrios (2005)
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Elements of an Epidemic (cont’) Host factors
1.
Levels of genetic resistance or susceptibility of host Degree of genetic uniformity of host in a particular field Type of crops
i.
ii.
iii.
Annual crops & foliar or fruit diseases develop much more rapidly (in weeks) Perennial woody diseases take longer time to develop (in years)
Age of host plants
iv.
Some plants are susceptible only during growth period & become resistant during mature period
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Elements of an Epidemic (cont’) Pathogen factors
2.
Levels of virulence Quantity of inoculum near hosts Type of reproduction of the pathogen
i. ii. iii.
Polycyclic or monocyclic pathogens
Ecology of the pathogen
iv.
Depends on the type of pathogen
Mode of spread of the pathogen
v.
Air-borne, soil-borne, vector-borne
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Elements of an Epidemic (cont’) Environmental factors
3.
Moisture
i.
Rain, dew, high humidity Dominant factor in diseases caused by oomycetes, fungi, bacteria & nematodes
Temperature
ii.
Affects disease cycles of pathogens
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Elements of an Epidemic (cont’)
Disease development is also affected by Time 5. Humans Interactions of the 5 components are described by the disease pyramid. 4.
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The Disease Pyramid
Source: Agrios (2005)
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Elements of an Epidemic (cont’) Time factors
4.
Season of the year Duration & frequency of favorable temp. & rains Appearance of vectors, etc.
Human factors
5.
Site selection & preparation Selection of propagative materials Cultural practices Disease control measures
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Patterns of Epidemics 1. 2.
Disease-progress curve Disease-gradient or dispersal curve
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Patterns of Epidemics (cont’) Disease-progress curve
1.
Shows the progress of an epidemic over time, e.g., numbers of lesions, numbers of diseased plants, etc. Also allows disease forecasting & selection of the best control strategy for the particular disease & time. Basic epidemic patterns i. Saturation-type curve: monocyclic diseases ii. Sigmoid curve: polycyclic diseases
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Patterns of Epidemics (cont’) Monocyclic diseases
1.
Examples: root diseases, wilt diseases Long disease cycle (complete 1 cycle/year)
Polycyclic diseases
2.
Examples: leaf rust, leaf blight, leaf spot, mosaic Short disease cycle (produce many generations in 1 growing season, 2-30 cycles/year)
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Patterns of Epidemics (cont’) 1.
Disease-progress curve (cont’)
Three monocyclic diseases of different epidemic rates.
Polycyclic disease, such as late blight of potato. Source: Agrios (2005)
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Patterns of Epidemics (cont’) Disease-gradient or dispersal curve
2.
The amount of disease is greater near the source of inoculum The amount of disease decreases with increasing distance from the source
Source: Agrios (2005)
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Comparison of Epidemic Models Parameter
Policyclic Model
Monocyclic Model
Reproduction High reproduction & Low reproduction & death rate death rate Inoculum dispersal
Wind-borne, vectors Soil-borne
Examples
Leaf rust, leaf blight, leaf spot, powdery mildew, mosaic
Root diseases, foot rot, wilt diseases
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Comparison of Epidemic Models (cont’) Parameter
Polycyclic Model
Monocyclic Model
Control measure
Stop pathogen reproduction: spray fungicides, use resistant varieties
Reduce initial inoculum: destroy diseased plants or debris
Epidemic rate (r)
E.g.: potato late blight, r = 0.30.5/day
E.g.: Verticillium wilt, r = 0.02/day
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Comparison of Epidemics
Compare
Using epidemic (infection) rate (r)
Same disease: at different times, different locations, under different management practices Different diseases The amount of disease increase per unit of time (per day, week or year).
r derive from disease progress curve transformed mathematically into straight lines.
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Epidemiology and Disease Management Monocyclic Model x = QRt x = disease incidence Q = initial inoculum R = infection rate t = time To reduce disease incidence, x, at any point in the epidemic: 1. 2. 3.
Reduce initial inoculum, Q Reduce rate of infection, R Reduce duration of epidemic, t Source: Arneson (2001)
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Epidemiology and Disease Management (cont’) Polycyclic Model x = x0ert x = disease incidence e = natural logarithm x0= initial inoculum r = infection rate t = time To reduce disease incidence, x, at any point in the epidemic: 1. 2. 3.
Reduce initial inoculum, x0 Reduce rate of infection, r Reduce duration of epidemic, t Source: Arneson (2001)
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Measurement of Plant Disease and Yield Loss Disease incidence
1.
The number of plant units that are diseased in relation to the total number of units examined Commonly used to measure the spread of a disease
Disease severity
2.
The amount of plant tissue that is diseased Measured using assessment scales or by determining the area under a disease progress curve (AUDPC)
Yield loss
3.
The proportion of yield that the grower will not be able to harvest due to disease Results in economic loss
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New Tools in Epidemiology Molecular tools
1.
Polymerase Chain Reaction (PCR), Enzyme Linked Immunosorbant Assay (ELISA), DNA Fingerprinting, etc. For rapid & accurate detection & identification of pathogens
Data management
2.
Geographic Information System (GIS), Global Positioning System (GPS), Remote Sensing, etc. To assist in disease control strategies
Disease modeling & forecasting
3.
To predict the probability of outbreaks
