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

Abstract

Previous studies in coastal California suggested that morning leaf wetness duration and temperature immediately after the prolonged leaf wetness period affect infection of lettuce by the downy mildew pathogen, Bremia lactucae. In this study, spatial analysis tools in a geographic information system were used to interpolate disease assessment data and then relate them to weather variables measured in 1995 and 1997 at weather stations in the Salinas Valley. Among the variables monitored at these weather stations, midday temperature (10:00 A.M. to 2:00 P.M.) was related most strongly to the interpolated downy mildew incidence in a circular area (radius = 5 km) around each station (r = 0.52, P < 0.0001); the higher the midday temperature, the lower the disease incidence. High humidity and prolonged morning leaf wetness duration also were associated with high downy mildew incidence. Cluster analysis resulted in distinct regions with different midday temperatures, which overlapped well (92.2% of the total area) with regions distinguished in previous cluster analyses of downy mildew incidence. Clusters of morning relative humidity showed similar patterns, although they overlapped less well with clusters of disease incidence. These results confirmed that midday temperature is an important determining factor for lettuce downy mildew, and its effects should be incorporated into a disease warning system for coastal California. Cluster analyses based on the effects of temperature have great potential for use in regional downy mildew risk assessment.