초록 close

Sets of weather variables for estimation of LWD were evaluated using CART(Classification AndRegression Tree) models. Input variables were sets of hourly observations of air temperature at 0.3-m and1.5-m height, relative humidity(RH), and wind speed that were obtained from May to September in 1997,1998, and 1999 at 15 weather stations in Iowa, Illinois, and Nebraska, USA. A model that included airtemperature at 0.3-m height, RH, and wind speed showed the lowest misidentification rate for wetness.The model estimated presence or absence of wetness more accurately (85.5%) than the CART/SLD model(84.7%) proposed by Gleason et al. (1994). This slight improvement, however, was insufficient to justify theuse of our model, which requires additional measurements, in preference to the CART/SLD model. Thisstudy demonstrated that the use of measurements of temperature, humidity, and wind from automatedstations was sufficient to make LWD estimations of reasonable accuracy when the CART/SLD model wasused. Therefore, implementation of crop disease-warning systems may be facilitated by application of theCART/SLD model that inputs readily obtainable weather observations.