| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1711551 | Biosystems Engineering | 2011 | 17 Pages |
Greenhouse design is an optimisation problem that might be solved by a model-based greenhouse design method. A sensitivity analysis of a combined greenhouse climate-crop yield model of tomato was done to identify the parameters, i.e. greenhouse design parameters, outdoor climate and climate set-points, that most strongly influence greenhouse performance. The analysis was performed for a low-tech greenhouse in Almeria, Spain, and a high-tech greenhouse in Texas, USA. A single-variate sensitivity analysis showed that outdoor climate has the strongest impact on the performance of the greenhouse system, followed by greenhouse design parameters and greenhouse climate set-points. The high impact of the outdoor conditions stresses the need to select a proper location for the greenhouse. Concerning the design parameters, the analysis revealed different results for the two locations and greenhouses studied. This emphasises that a ‘custom made’ approach to greenhouse design should be followed exploiting local conditions. In both cases, structures with a higher PAR transmission and a NIR-selective whitewash should be used. Seasonal patterns in the model sensitivity of for instance PAR, NIR and FIR emission coefficients of the cover indicate that a greenhouse with adjustable cover parameters will be advantageous over a design with fixed greenhouse cover parameters, as is usually implemented. A multi-variate sensitivity analysis revealed strong joint effects of parameters on crop yield. A joint increase of the PAR transmission and temperature set-point for ventilation favoured the crop yield for both greenhouses, stressing a simultaneous approach to both design and control of greenhouse systems.
► We apply a sensitivity analysis to a combined greenhouse climate-crop yield model. ► A greenhouse in Almeria, Spain and a greenhouse in Texas, USA are analysed. ► Outdoor climate has the strongest impact on greenhouse performance. ► PAR remains the main limiting factor for greenhouse production systems. ► Seasonal patterns of sensitivity show the need for adjustable cover parameters.
