Estimation of leaf wetness duration for greenhouse roses using a dynamic greenhouse climate model in Zimbabwe

Leaf wetness duration (LWD) is one of the most critical parameters involved in the development of plant diseases, since many pathogens require the presence of free water on plant organs to infect foliar tissue. For this reason LWD monitoring is extremely important in crop protection, particularly through the use of weather-related disease forecasting models. Because of the difficulties involved in the measurement of leaf wetness duration, simulation models, based on agrometeorological parameters, are often used as alternatives to field measurement. Furthermore, in greenhouse crop production, these LWD models can be used in predictive control of the greenhouse climate as to suppress the development and propagation of infectious plant diseases. In this study, the Gembloux Dynamic Greenhouse Climate Model (GDGCM) was applied to derive estimates of LWD and hence potential disease incidence, for a rose crop in a naturally ventilated Azrom type greenhouse in Zimbabwe. The model LWD estimates were compared both with data measured by sensors and with visual inspections of LWD conducted during the period May 2007-April 2008. When the GDGCM outputs were used to estimate LWD, the best agreement between measured and predicted LWDs (RMSE = 3.2 h d(-1)) were obtained when LWD was calculated as the number of hours that the dew point depression of the air remained below 2.3 degrees C (for wetness onset) and 2.5 degrees C (for drying off). The good agreement between measured and predicted LWD showed that the GDGCM can be used to predict LWD with acceptable accuracy. This could be of considerable value in helping to predict possible outbreaks of certain climate related diseases, like downy mildew, powdery mildew and botrytis. This information can be used by growers to decide on the optimal precautions to take to prevent possible epidemics of these diseases. C) 2013 Elsevier B.V. All rights reserved.