PLP 6404 Epidemiology of Plant Diseases Spring Lecture 23-24: Epidemiology and disease management strategies

Transcription

1 PLP 6404 Epidemiology of Plant Diseases Spring 2015 Ariena van Bruggen, modified from Katherine Stevenson Lecture 23-24: Epidemiology and disease management strategies Lecture 23. Principles of Plant Disease Management 1. Exclusion Quarantines and inspections Chrysanthemum white rust Karnal bunt Citrus canker Phytophthora ramorum Citrus greening Plum pox European larch canker Ralstonia solanacearum r 3, bv 2 Gladiolus rust Potato wart disease Pathogen-free propagative material 2. Avoidance Alter planting or harvest date 3. Eradication aimed at the pathogen Cultural Physical Biological Chemical (e.g. methyl bromide) 4. Resistance Cross protection Induced resistance (SAR) Plant defense activators (e.g. Actigard) Cultural (to improve plant growth) Resistant varieties 5. Protection aimed at the plant Chemical Biological 6. Therapy Systemic fungicides Removal of diseased tissue 1

2 Antibiotics Epidemiological Strategies in Plant Disease Management Three epidemiological strategies: 1. eliminate or reduce Y 0 2. reduce the rate (r) of disease development 3. shorten the duration (time) of the epidemic Lecture 24. Reducing Initial inoculum 1. Reduce the amount of initial inoculum Reducing the amount of initial inoculums by: sanitation - anything that reduces the amount of initial inoculum before the crop is planted (before the epidemic is initiated) Examples: - treatment of seed with hot water or chemicals to kill seedborne pathogens - seed indexing and certification for control of seedborne viruses - potato seed certification - crop rotation - elimination of alternate hosts - deep plowing of crop refuse to enhance decomposition of debris and reduce overwintering populations of pathogens chemical or physical eradication Examples: - fumigation - removal of infected trees - flooding - heat treatment 2

3 vertical resistance (qualitative, race specific) Examples: - as long as there is no new race that can overcome the resistance, the inoculums can be considered locally eradicated 2. Reduce the efficacy of initial inoculum microclimate alteration (temperature, moisture, UV etc.) alteration of soil reaction (ph) or organic matter (competition) alteration of planting density or pruning The Sanitation Ratio Vanderplank derived what he called the sanitation ratio to calculate the benefit in time of the delay of the epidemic brought about by reducing the initial disease a specified amount. Field 1 Field 2 If we only consider the early part of an epidemic, we can use the exponential model to describe the amount of disease as a function of time in the two fields as follows: Field 1 (without sanitation): Field 2 (with sanitation): y = y 0 e rt y s =y 0S e rt Ratio of disease in the two fields: y / y s = y 0 / y 0s = sanitation ratio The effect of sanitation remains proportionally the same throughout the course of the epidemic. The effect of sanitation on disease development: 3

4 y Without sanitation With sanitation ts (time delay) t The delay, t s, can be calculated as the time it takes for y s to increase to y: The delay in time [ t] can also be calculated as: t = ln (y 0 / y 0s ) / r Example: 10-fold reduction in initial disease was from y 0 = 0.01 to y 0s = by sanitation, and r = 0.23, the delay [ t] would be: t = ln (y 0 / y 0s ) / r t = ln (0.01/ 0.001)/ 0.23 t = ln (10) / 0.23 t = 2.30/ 0.23 t = 10 days Calculate the rest of the examples for yourself Example: Lettuce mosaic virus Days to harvest (t s ): 70 Disease threshold at harvest (y): 1% Rate parameter (r): 0.12 (per day) How low must the frequency of infected seed be to keep from exceeding the 1% disease threshold at harvest? [calculate y s ] 4

5 Since we know that y/y s = y 0 /y 0s, then we can express the time delay in terms of the sanitation ratio,: y 0 /y 0s Example: if y 0 /y 0s = 5 and r = 0.2, what is the time delay (t s )? The time delay varies inversely with r : A general equation to determine t s based on models other than the exponential model: where r* is the rate parameter from the model, and y 0 * and y 0s * are the appropriate linearizing transformations for y. Example: logistic disease increase y o y os t s = 1/r (ln ( 1-y 0 ) ln ( 1-y 0s )) Note: This relationship holds if r is not affected by the changes in y 0. However, for some diseases, a decrease in y 0 results in an increase in r. Examples: Plaut, J. L, and Berger, R. D Infection rates in three pathosystem epidemics initiated with reduced disease severities. Phytopathology 71:

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7 Similar results were obtained independently by other researchers for Southern corn leaf blight (Gregory, L. V., et al Phytopathol. Z. 100: ) and powdery mildew of wheat (Rouse, D. I., et al Phytopathol. Z. 100: ). The increase in r counteracts the benefits from sanitation in terms of the time delay, t s. Berger: Vanderplank's sanitation ratio equation to determine the time delay represents the maximum possible time delay, and that for most pathosystems, less delay is most likely. And even though epidemics may go faster when the initial amount of disease is reduced, and the final disease levels may be similar, there is still some gain from the sanitation practice. 7