Analyses of the Relationships Between Lettuce Downy Mildew and Weather Variables Using Geographic Information System...

Area of Science:

• Plant pathology
• Agricultural meteorology
• Geographic Information Systems (GIS)

Background:

• Lettuce downy mildew (Bremia lactucae) infection in coastal California is influenced by leaf wetness and post-wetness temperature.
• Previous research indicated a link between environmental factors and disease outbreaks.

Purpose of the Study:

• To spatially analyze downy mildew incidence in relation to weather variables in the Salinas Valley.
• To identify key meteorological factors influencing Bremia lactucae spread and severity.

Main Methods:

• Utilized GIS for spatial interpolation of disease assessment data.
• Correlated interpolated disease incidence with weather station data (temperature, humidity, leaf wetness).
• Employed cluster analysis to identify distinct climatic and disease regions.

Main Results:

• Midday temperature (10 AM-2 PM) showed the strongest negative correlation with downy mildew incidence (r = 0.52).
• Higher midday temperatures correlated with lower disease incidence.
• Prolonged morning leaf wetness and high humidity were associated with increased disease incidence.
• Cluster analysis revealed distinct temperature regions that largely overlapped with downy mildew incidence regions.

Conclusions:

• Midday temperature is a critical factor in determining lettuce downy mildew risk in coastal California.
• Incorporating midday temperature into a disease warning system is recommended.
• Temperature-based cluster analysis shows potential for regional downy mildew risk assessment.