1. General Model Information

Name: powdery mildew disease forecast model for grapes

Acronym: GRAPE_MILDEW


Main medium: terrestrial
Main subject: agriculture
Organization level: Population
Type of model: not specified
Main application: decision support/expert system
Keywords: grape, Powdery mildew, Uncinula necator, forecast, phenology, degree-day

Contact:

Doug Gubler

Department of Plant Pathology, University of California, Davis.
phone:
fax:
email: ipmig@ucdavis.edu

Author(s):

Thomas, C.S., Gubler, W.D. and Leavitt, G.

Abstract:

Model Description: This model contains two stages based on pathogen biology, an ascospore and a conidial stage. Check with your local Cooperative Extension agent to determine if both stages are important in your area. Ascospore stage. To determine ascospore infection risk levels, the model calculates the daily average temperature and measures the hours of leaf wetness. The model modifies the Mills table developed for apple scab ascospore infection by predicting infection based on 2/3 of the hours of required wetness .

Model Description

Model Validation: Since 1995 validation work has been conducted in multiple growing regions of California. In 1997, California PestCast is sponsoring validation projects in additional table and wine grape areas and in raisin grapes. The model is also being validated in New York, Washington, and Oregon; Germany, Austria, and Australia.

Model Implementation: This model is being implemented by University of California Extension Plant Pathologist Doug Gubler, growers, Cooperative Extension advisors, and licensed consultants in several grape-growing counties in California. Disease risk indices for many California weather stations are available on a WWW site in the Department of Plant Pathology, University of California, Davis.


II. Technical Information

II.1 Executables:

Operating System(s):

II.2 Source-code:

Programming Language(s):

II.3 Manuals:



II.4 Data:



III. Mathematical Information


III.1 Mathematics


III.2 Quantities

Plant phenology, pathogen phenology


III.2.1 Input

Environmental: Hourly average temperature, daily maximum temperature, hourly leaf wetnessduration.

Calculated: Daily average temperature; daily value of number of hours that 70<=T<=85 F.

III.2.2 Output


IV. References

Thomas, C.S., Gubler, W.D. and Leavitt, G. 1994. Field testingof a powdery mildew disease forecast model on grapes in California. Phytopathology 84:1070(abstr.).

Weber E., Gubler, D. and Derr, A. 1996 Powdery Mildew Controlled with Fewer FungicideApplications Practical Winery & Vineyard January/February 1996.



V. Further information in the World-Wide-Web


VI. Additional remarks

Information and remarks about the application of this model


Last review of this document by: T.Gabele 19.08.1997
Status of the document:
last modified by Tobias Gabele Wed Aug 21 21:44:44 CEST 2002

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