1.5 Prediction of disease outbreaks Introduction Principles of disease forecasting Forecasting the amount of initial inoculum Forecasting the rate of pathogen proliferation Forecasting host response Concluding remarks

Why do we need to predict disease outbreaks Why do we need to predict disease outbreaks? or What are the uses of disease forecasts ? For making strategic decisions Prediction of the risks involved in planting a certain crop. Deciding about the need to apply strategic control measures (soil treatment, planting a resistant cultivar, etc.) Time Disease intensity For making tactical decisions Deciding about the need to implement disease management measure ?

The disease pyramid grower host environment pathogen

The principles of disease forecasting are based on: The nature of the pathogen Effects of the environment The response of the host to infection Activities of the growers

The disease pyramid grower host environment disease pathogen

Disease severity (logit) Time Disease severity (%) Monocyclic pathogens Time Disease severity (%) Polycyclic pathogens Time Disease severity (logit) Initial disease rate

Complete only one disease cycle in a growing season Monocyclic pathogens Complete only one disease cycle in a growing season (100 - y) QR dy dt Q = amount of initial inoculum R = infection efficacy of the inoculum y = disease intensity

0.7oC -1.1oC Wilt disease in maize induced by Erwinia stewartii Prediction of a monocyclic pathogen that complete only one disease cycle in a growing season - indirect prediction Wilt disease in maize induced by Erwinia stewartii Severe infections occur after moderate winters. Mild infections occur after cold winters. Average Temp. in December, January and February 0.7oC High probability for severe epidemic -1.1oC Low probability for severe epidemic

Low probability for severe epidemic Consequences from predicting the severity of Erwinia stewartii in maize on grower’s action Low probability for severe epidemic Sow maize as planned High probability for severe epidemic Do not sow maize at all Sow only resistant cultivars

Wilt disease in sugar beat induced by Sclerotium rolfsii Prediction of a monocyclic pathogen that complete only one disease cycle in a growing season - direct prediction Wilt disease in sugar beat induced by Sclerotium rolfsii No. of sclerotia in soil sample Disease severity Sclerotia Soil Soil sample

Few sclerotia in the soil sample Consequences from predicting the severity of S. rolfsii in sugar beat on grower’s actions Few sclerotia in the soil sample Sow sugar beat as planned Many sclerotia in the soil sample Do not sow sugar beat at all Sow only resistant cultivars Apply soil treatment

Complete only one disease cycle in a growing season Monocyclic pathogens Complete only one disease cycle in a growing season Q = amount of initial inoculum R = infection efficacy of the inoculum y = disease intensity (100 - y) QR dy dt

The disease pyramid grower host environment disease pathogen

Apple scab induced by Venturia inaequalis Prediction of a polycyclic pathogen that complete very few disease cycles in a growing season Apple scab induced by Venturia inaequalis 1. Amount of initial inoculum is high (ascospores) 2. Only young leaves are susceptible 3. Film of water on the leaves and proper temperatures are needed for infection Temperature (oC) Duration of RH>90% (hrs) No disease Mod. disease Severe disease mild disease

Duration of RH>90% (hrs) Consequences from predicting the occurrence of infections of apples by V. inaequalis on grower’s actions Decision concerning the need for fungicide spraying is made daily during the beginning of the season Temperature (oC) Duration of RH>90% (hrs) No disease Mod. disease Severe disease mild disease High dose of systemic fungicide Systemic fungicide Protectant fungicide No control

Complete several disease cycles in a growing season Polycyclic pathogens Complete several disease cycles in a growing season r y dy dt (100 - y) r = apparent infection rate y = disease intensity

Prediction of a polycyclic pathogen - the time of disease onset Sunflower rust induced by Puccinia helianthi 1. The rate of disease progress (apparent infection rate) is not affected by the environment 2. Epidemics in different fields vary only in the time of disease onset Time Disease severity (%)

Prediction of a polycyclic - the time of disease onset Sunflower rust induced by Puccinia helianthi 3. One assessment of the disease, at any time, may be used for future disease prediction Time Disease severity (%) Critical severity

The critical time model Consequences from predicting the time for critical severity on rust management in sunflower Time Disease severity (%) Critical severity The critical time model Time for critical severity (days) Yield loss (%)

Why the environment did not affect P. helianthi? spore germination establishment lesion formation reproductive growth spore formation spore dissemination Time Disease severity (%)

Effects of the environment on P. helianthi life cycle germination (%) Temperature (oC) 10 25 spore dissemination establishment spore germination Duration of wetness (hours) germination (%) 2 6 reproductive growth lesion formation

Effects of the environment on P. helianthi life cycle spore dissemination spore formation spore germination Latent period (days) Temperature (oC) 10 35 Latent period reproductive growth establishment lesion formation

Effects of the environment on P. helianthi life cycle No. of spores Temperature (oC) 5 38 spore dissemination Induction of light spore formation spore germination Relative humidity (%) No. of spores 70 95 Wetness duration (hrs) No. of spores reproductive growth establishment lesion formation

Effects of the environment on pathogens spore dissemination spore formation spore germination Time Disease severity (%) reproductive growth establishment lesion formation

Effects of the environment on pathogens Rain Periods of high relative humidity High or low temperatures Hail Sand storms Environmental factors Environmental factor Time Disease severity (%)

Measurement of weather parameters Variability over distances Precision of measurement Temperature Rain Relative humidity Leaf wetness Radiation intensity Cloudiness Wind Low precision High precision Low variability High variability

Where to put the weather sensors? Weather station

Prediction of weather parameters Precision of prediction Parameter Variability over distances Temperature Rain Relative humidity Leaf wetness Radiation intensity Cloudiness Wind Low precision High precision Low variability High variability

Prediction of a polycyclic pathogen - the time of disease onset Potato late blight induced by Phytophthora infestans 1. Amount of initial inoculum is very low (infected tubers). 2. Disease progress rate may be very high. Time Disease severity (%) 3. Potential loss - high. 4. Preventive sprays are highly effective. 5. The time of disease onset is governed by the environment.

Prediction of the time of late blight onset Hyre’s system Late blight appears 7-14 days after accumulation of 10 “rain favorable-days” since emergence. Average Temp. in the last five days 7.2oC 25.5oC “A rain-favorable day” Rain quantity in the last five days 30 mm and

Prediction of the time of late blight onset Wallin’s system Late blight appears 7-14 days after accumulation of 18-20 “severity values” since emergence. Temperature Hours with RH>90% 7.2 - 11.6 11.7 - 15.0 15.1 - 26.6 15 12 9 16-18 13-15 10-12 19-21 22-24 25+ 22+ 19+ Severity values 0 1 2 3 4

Severity values during the last 7 days Recommendation for action Prediction of the subsequent development of late blight and determining the need for spraying N W 7d 5d <3 3 4 5 6 >6 <4 >4 Severity values during the last 7 days N N W 7d 7d 5d N W 7d 5d 5d 5d No. rain-favorable days during the last 7 days No spray late blight warning 7-day spraying schedule 5-day spraying schedule Recommendation for action

The disease pyramid grower host environment disease pathogen

Potato early blight induced by Alternaria solani Prediction of disease development in relation to host response to the pathogen Potato early blight induced by Alternaria solani 1. Amount of initial inoculum is very high (infected plant debris) 2. The pathogen develops at a wide range of conditions 3. Potential loss - low 4. Disease progress is governed by the response of the host Time Host resistance

Age related resistance Time Host resistance Res. Suc. emergence Vegetative phase tuber initiation Reproductive phase harvest The source-sink relationships of the plant determines its response to the pathogen

Supplement control measures Consequences from predicting the age related resistance of potatoes on management of early blight Time Host resistance Res. Suc. emergence tuber initiation harvest No need to control Supplement control measures

The disease pyramid farmer host environment disease pathogen

Effects of grower’s actions on the epidemic Irrigation Fertilization Heating Ventilating Spraying Harvesting Grower’s actions Time Disease severity (%)

Prediction of disease outbreaks based on the environment and grower actions Botrytis rot in basil induced by Botrytis cinerea Time Disease severity (%)

Botrytis rot in basil induced by Botrytis cinerea 1. The pathogen invades the plants through wounds that are created during harvest. 2. The wounds are healed within 24 hours and are not further susceptible for infection. 3. A drop of water is formed (due to root pressure) on the cut of the stem. 4. If humidity is high, the drop remains for several hours.

Botrytis rot in basil induced by Botrytis cinerea Time Disease severity (%) rain Harvests 5. During rain, growers do not open the side opening of the greenhouses. 6. Disease outbreaks occur when harvest is done during a rainy day.

Consequences from predicting grey mold outbreaks in basil on disease management Time Disease severity (%) rain Harvests To minimize the occurrence of infection, harvesting should be avoided during rainy days. If harvesting is done during rainy days, apply a fungicide spray once, soon after harvest

Concluding remarks The principles of disease forecasting should be based on: The nature of the pathogen (monocyclic or polycyclic) Effects of the environment on stages of pathogen development The response of the host to infection (age-related resistance) Activities of the growers that affect the pathogen or the host