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Greenhouses shelter the crop from unfavourable environmental conditions and the covering largely contributes to creating beneficial growing conditions inside. There is no perfect greenhouse cover for all combinations of crop and climatic regions. Usually a greenhouse cover has permanent optical properties determining the amount of solar radiation entering the greenhouse. Consequently during crop growth, the amount and quality (spectrum, direct/diffuse ratio) of the solar radiation is not ideal for the crop. Growers try to compensate for this by using different additional techniques such as temporary coatings, screens (mobile or fixed, etc.) and heating or cooling. New materials are currently being developed, whose optical properties can be (almost) instantaneously changed (materials with switchable properties). This will allow growers to gain real-time control on the quantity and quality of the light entering the greenhouse to match crop requirement. The present study uses advanced simulation models to predict the potential of covers with switchable properties to improve tomato yield and use of resources in different climatic regions (mild winter and tropical) and with different greenhouse types (artisan and industrial type). Results indicate that covers with switchable properties have advantages over permanent properties for most combinations of filter type/location. Only in very extreme tropical climates will covering materials with permanent filter properties have advantages. Furthermore, simulations models can play a major role in optimising the switchable filter design. • No single type of greenhouse cover has optimum performance in every climate & location. • Switching radiometric properties looks promising for high light demand crops. • Switchable materials have no advantage over permanent filters in tropical climates. • Simulation could be a powerful tool to determine optimum radiometric properties. • Simulation should include specific combination of crop, greenhouse location & type. [ABSTRACT FROM AUTHOR]

Computational fluid dynamics (CFD) was used to study the effect of greenhouse sidewall vents on buoyancy-driven natural ventilation, which is the most difficult situation for greenhouse cooling. A CFD model was validated and then used to compare roof ventilation with combined roof and sidewall vents. The effects of the distance between opposing sidewall vents and the presence of anti-insect screens were investigated and quantified. In a 20 span greenhouse with a distance of 152m between the sidewalls, combining roof and sidewall vents gave a ventilation rate per unit ground area that was twice that with only roof vents. In a 3 span greenhouse with 22.8m between sidewalls but with the same roof vent area per unit ground area, seven times more ventilation was obtained with combined ventilation compared to only roof ventilation. In the 7 and 20 span greenhouses with roof ventilation, 79% and 48.3%, respectively, of the cross sectional area had a temperature difference between inside and outside the greenhouse greater than 4°C, whereas with combined ventilation, these areas were 23.4% and 36.1%. In the latter case, these hot areas were located in the centre of the houses. These results show that, with buoyancy-driven ventilation, the contribution of the sidewall vents is important even for quite large greenhouses but is more critical for greenhouses with a small number of spans. Numerical simulations with an anti-insect screen having a porosity of 25% showed that the air exchange rate with combined ventilation was reduced by 77–87%, depending on greenhouse size. These reductions were much larger than those obtained for wind-driven ventilation. It was concluded that, to maximise ventilation when wind speeds are low, combined roof and sidewall ventilation should be used. Also, large greenhouses should be relatively narrow to make better use of the sidewall vents. [Copyright &y& Elsevier]

A computational fluid dynamics (CFD) model for simulating greenhouse night-time climate and condensation is presented. The model was applied to a four-span plastic covered greenhouse. Film condensation was simulated by applying a user defined function (UDF) added to the commercial CFD package. The CFD model was verified by comparing CFD predictions with experimental measurements. The effect of cover temperature on greenhouse humidity was then determined by the CFD model and compared to experimental results. Root mean square values for the differences between the CFD and experimental values of internal temperature and humidity showed there was good agreement between. The results showed the importance of heat transfer losses by radiation, particularly for low values of soil heat flux (SHF). They also showed the roof was the coolest surface in the greenhouse, and therefore the sink for the water vapour produced by the crop. For each configuration (SHF 10, 25, 50 and 100Wm−2 and equivalent sky temperature 263K, 273K and 276K), the condensation rate curves and relative humidity (RH) evolution are presented. It was observed that all the condensation rate curves had the same characteristic shape and could be represented by a single logistic function. The response of the CFD model to a step-change in the water vapour source (night-time transpiration from the crop) was then analysed. It was observed that the model predicted the same steady-state temperature, RH and condensation rate independent of the time when the water vapour source was enabled. The CFD condensation model is intended to be used for the design of strategies for humidity control, particularly in unheated greenhouses. [ABSTRACT FROM AUTHOR]

An economic model was developed as a key component of a model-based method to design greenhouses for a broad range of climatic and economic conditions. This economic model was linked to an existing greenhouse climate-crop yield model to calculate the annual Net Financial Result (NFR) of a greenhouse. The aim of this study was to identify – among ten predefined design alternatives – the greenhouse with the highest annual NFR for tomato production under southern Spanish conditions. The basic designs were either the parral greenhouse, or a multi-tunnel, possibly fitted with any combination of heating, fogging and CO2 enrichment. Results demonstrated that the multi-tunnel, fitted with only a fogging system was most profitable, followed by the multi-tunnel with heating, CO2 enrichment and fogging. However, the difference in NFR between such a design and a simple parral was small with respect to the difference in investment. A sensitivity analysis of the NFR of the two technology extremes shows that tomato price, the fraction of marketable yield and the Photosynthetically Active Radiation (PAR) transmission of the cover had the largest bearing on NFR. With increasing technology level, the NFR depended less on outdoor climate and more on tomato price. This indicates that a low-tech greenhouse diminishes the risk of variations among price paths in different years, whereas a high-tech greenhouse covers better the “weather risk”. The best design was also affected by climate management and the joint impact of climate modification techniques. These results demonstrated that a model-based design approach can cope with multi-factorial design aspects. [ABSTRACT FROM AUTHOR]