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Modeling Infection of Strawberry Flowers by Botrytis cinerea Using Field Data.

X Xu, D C Harris, A M Berrie

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    |October 24, 2008
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    Summary
    This summary is machine-generated.

    This study monitored strawberry flower infections by Botrytis cinerea, finding that weather conditions, particularly daytime vapor pressure deficit and nighttime temperature, are key predictors for disease management.

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    Area of Science:

    • Plant Pathology
    • Agricultural Meteorology
    • Mycology

    Background:

    • Strawberry flower infections by Botrytis cinerea (gray mold) pose significant challenges to crop yield.
    • Understanding the relationship between environmental factors, inoculum levels, and disease incidence is crucial for effective disease management.

    Purpose of the Study:

    • To develop and compare predictive models for strawberry flower infection by Botrytis cinerea.
    • To identify the key meteorological variables influencing disease development.
    • To assess the potential of weather-based models for disease management strategies.

    Main Methods:

    • Monitoring of Botrytis cinerea infection incidence in unsprayed strawberry field plots over three years.
    • Collection of meteorological data (daytime vapor pressure deficit, nighttime temperature) and airborne conidia counts.
    • Development and evaluation of three modeling approaches: inoculum-based, weather-based, and combined models.

    Main Results:

    • All developed models demonstrated satisfactory fit to observed infection data.
    • Higher inoculum levels correlated with increased infection rates.
    • Weather-based models provided more accurate predictions than inoculum-only models.
    • Combined models offered marginal improvement over weather-only models.
    • Daytime vapor pressure deficit and nighttime temperature were identified as the most influential weather variables, with low daytime vapor pressure deficit and high nighttime temperature favoring infection.

    Conclusions:

    • Weather-based models, particularly those incorporating daytime vapor pressure deficit and nighttime temperature, show strong potential for predicting strawberry gray mold incidence.
    • These models can serve as valuable tools to assist in the strategic management of Botrytis cinerea in strawberry cultivation.
    • The consistent relationship between environmental variables and infection across years supports the reliability of these predictive approaches.