Microclimate prediction for dynamic greenhouse climate control

Greenhouse energy-saving and biocide reduction can be achieved through dynamic greenhouse climate control with computerized model-based regimes. This can be optimized when next to greenhouse macroclimate (i.e., the aerial environment) also, the crop microclimate is predicted. The aim of this article was to design and apply a simple deterministic microclimate model for dynamic greenhouse climate control concepts. The model calculates crop temperature and latent heat of evaporation in different vertical levels of a dense canopy of potted plants. The model was validated with data attained from experiments on dynamic or nondynamic (regular) controlled greenhouse cultivation. Crop temperature was with a 95% confidence interval of 2 degrees C or 2.4 degrees C for sunlit or shaded leaves, respectively, accurately predicted in a simple greenhouse with predefined climate set points. With a more dynamic greenhouse control also including assimilation lighting and screens, the prediction quality decreased but still had a 95% confidence interval of crop temperature prediction of 3.8 degrees C for sunlit leaves. Simulations showed that controlling greenhouse temperature according to the predicted crop temperature rather than according to the air temperature can save energy. Energy-saving is highest during winter and 12% energy saving was attained during January under Danish climate conditions.