Validation of Potato Early Blight Disease Forecast Models for Colorado Using Various Sources of Meteorological Data.

Abstract

Disease forecasts from regional or remotely sensed meteorological data free growers from infield weather data monitoring and may improve disease forecast implementation. This study was initiated to validate potato early blight forecast models in Colorado and to determine the influence of sources of meteorological data on forecast accuracy. Hourly temperatures were recorded by Campbell Scientific CR-10, Pessl Instruments μMetos Model MCR300, and Spectrum Technologies Model 450 WatchDog weather stations and data loggers within potato fields, field-specific temperature estimations generated by mPOWER3/EMERGE from off-site weather stations, and regional COAGMET CR-10 weather stations. Mean hourly temperature deviations between mPOWER3/EMERGE or in-field stations and COAGMET varied from 0.93°C greater to 1.11°C less than COAGMET observations. Initial appearance of early blight lesions was predicted using a 300 physiological day threshold in commercial fields in each year from 1998 to 2001 and in experimental plots in each year from 1997 to 2001 as determined by COAGMET meteorological observations. All sources of meteorological data generated early blight forecasts within 6 days of each other across all locations and years. COAGMET weather stations should free potato growers and integrated pest management personnel from collecting in-field microclimatic data and speed the implementation of disease forecasting.