UC IPM Online UC ANR home page UC IPM home page

UC IPM Home

SKIP navigation

 

Research and IPM

Models: Diseases

Crop: Celery

Disease: Septoria Late Blight
Pathogen: Septoria apiicola

Note: Before using a model that was not field tested or validated for a specific location, the model should be tested for one or more seasons under local conditions to verify that it will work in this location. See "Validation Work" below.

Model 1 of 3

Model developer and citation

Lacy, M. L. 1994. Influence of leaf wetness periods on infection of celery by Septoria apiicola and use in timing sprays for control. Plant Dis. 78:975-979.

Sensor location

Within crop row at a height of 0.3 m.

Input variables

Environmental: Leaf wetness duration.

Model description

The prediction of infection risk is based on twelve hours or longer of leaf wetness.

Action threshold

According to the model, initiate the first treatment after 12 or more hours of continuous leaf wetness. The timing of subsequent treatments is also based on 12 or more hours of leaf wetness, after a minimum of a seven-day spray interval.

Model validation

Lacy, M. L. 1994. Influence of leaf wetness periods on infection of celery by Septoria apiicola and use in timing sprays for control. Plant Dis. 78:975-979.

Model implementation

The model is still in validation phase.

Current limitations

The original model does not include temperature as an input variable, because temperature is not a limiting factor in disease development in Michigan, where the model was developed. However, temperature could possibly be a factor in other locations if temperatures below 10C or above 30C are experienced.

Related work

Mathieu, D. and A. C. Kushalappa. 1993. Effects of temperature and leaf wetness duration on the infection of celery by Septoria apiicola. Phytopathology 83:1036-1040.

Top of page

Model 2 of 3

Model developer and citation

Mathieu, D., and A. C. Kushalappa. 1993. Effects of temperature and leaf wetness duration on the infection of celery by Septoria apiicola. Phytopathology 83:1036-1040.

Sensor location

Not specified.

Input variables

Environmental: Air temperature, leaf wetness duration.

Model description

The model predicts the proportion of the maximum number of lesions (PML) as a function of duration of leaf wetness and temperature during wet periods. Disease severity values (DSVs) were then calculated from predicted PML values using cluster analysis. Accumulation of DSVs begins when celery transplants have recovered from transplant shock. After canopy closure, accumulation of DSVs ends, and the model reverts to a weekly application of treatments.

Action threshold

DSV action threshold has not been developed for this model. After canopy closure, the model reverts to a weekly application of treatments.

Model validation

Not known.

Model implementation

Not known.

Current limitations of model

This model needs to be validated in the field and action thresholds need to be determined.

Future directions of model

Development of a forecasting model to initiate fungicide applications; incorporation of interrupted leaf wetness and high relative humidity into the model.

Related work

Mudita I. W., and A. C. Kushalappa 1993. Ineffectiveness of the first fungicide application at different initial disease incidence levels to manage Septoria blight in celery. Phytopathology 77: 1081-1084.

Top of page

Model 3 of 3

Model developer and citation

Modifications by Campbell Soup Company.

Pitblado, R. E. 1992. The development and implementation of TOM-CAST: A weather-timed fungicide spray program for field tomatoes. Ministry of Agriculture and Food, Ontario, Canada.

Madden L., Pennypacker, S. P., and McNab, A. A. 1978. FAST, a forecast system for Alternaria solani on tomato. Phytopathology 68:1354-1358.

Sensor location

Within canopy.

Input variables

Environmental: Air temperature, leaf wetness duration.

Calculated: Mean air temperature during the leaf wetness period.

Model description

Disease severity values (DSV) are calculated as a function of hours of leaf wetness and average air temperature during leaf wetness. The DSV is based on the FAST early blight model of tomato. After treatment the DSV accumulations reset to zero.

Action threshold

According to the model, initiate first treatment when 25 DSVs have accumulated. Subsequent treatments should occur each time 25 DSVs have accumulated.

Model validation

The model is being validated by Phil Phillips of the University of California, in Santa Barbara Co., Ventura Co., and by Campbell Soup Company in Sacramento Co.

Model implementation

Bolkan, H. A., and Reinert, W. R. 1994. Developing and implementing IPM strategies to assist farmers: an industry approach. Plant Dis. 78:545-550.

Top of page


Statewide IPM Program, Agriculture and Natural Resources, University of California
All contents copyright © 2005 The Regents of the University of California. All rights reserved.

For noncommercial purposes only, any Web site may link directly to this page. FOR ALL OTHER USES or more information, read Legal Notices. Unfortunately, we cannot provide individual solutions to specific pest problems. See our Home page, or in the U.S., contact your local Cooperative Extension office for assistance.

Agriculture and Natural Resources, University of California

Accessibility   /DISEASE/DATABASE/celeryblight.html revised: March 28, 2005. Contact webmaster.