A methodology for model-based greenhouse design: Part 4, economic evaluation of different greenhouse designs: A聽Spanish case

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• 作者：Bram H.E. Vanthoor^a ; ^b ; ^{bvanthoor@hortimax.com} ; Juan C. Gá ; zquez^c ; Juan J. Magá ; n^c ; Marc N.A. Ruijs^a ; ^d ; Esteban Baeza^c ; Cecilia Stanghellini^a ; Eldert J. van Henten^a ; ^b ; ^{eldert.vanhenten@wur.nl} ; Pieter H.B. de Visser^a
• 刊名：Biosystems Engineering
• 出版年：2012
• 期刊代码：112_15375110
• 类别：abs
• 出版时间：April, 2012
• 卷：111
• 期：4
• 页码：336-349
• 文件大小：449 K

摘要

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 鈥渨eather risk鈥? 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.