Predicting Microdochium Patch on Creeping Bentgrass

Microdochium patch is a major cool‐season disease affecting creeping bentgrass (Agrostis stolonifera L.) on golf courses, yet prediction tools are limited to help properly time fungicide applications for control. The objective of this study was to create a predictive model using growth chamber studies to determine the effects of air temperature and leaf wetness duration on the development of Microdochium nivale on creeping bentgrass turf. ‘Penncross’ creeping bentgrass plants were inoculated with leaves infected with M. nivale and maintained in growth chambers while exposed to temperatures of 8, 12, 16, and 20°C at leaf wetness durations of 24, 36, 48, and 60 h. Digital images of diseased plants were measured for percentage area infected using Assess image analysis software. The effects of temperature and leaf wetness duration on disease were significant. Disease severity increased with temperature and leaf wetness durations. Among treatments, the most disease was measured at 20°C, 60 h (46.3% disease). Analysis of variance using orthogonal polynomial contrasts and regression analysis determined the relationships among temperature and leaf wetness duration to disease. The polynomial model included linear and quadratic terms for temperature and leaf wetness duration. The adjusted coefficient of determination for the fitted model was 0.70. The model may be tested in the field and used to help predict outbreaks of Microdochium patch on creeping bentgrass turf.