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Improving Greenhouse Irrigation Through A Sensor-Based Decision Support System

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dc.contributor.advisor Youbin, Zheng
dc.contributor.author Henderson, Scott
dc.date.accessioned 2017-12-21T21:25:58Z
dc.date.available 2017-12-21T21:25:58Z
dc.date.copyright 2017-12
dc.date.created 2017-12-14
dc.date.issued 2017-12-21
dc.identifier.uri http://hdl.handle.net/10214/12117
dc.description.abstract To automate greenhouse irrigation, microclimate variations of the greenhouse environment and plant water requirements must be understood. Variation in greenhouse microclimate was monitored and quantified using pan evaporation (Bosman, 1990). The growing substrate volumetric water content (VWC) and growth performance of two crops, basil (Ocimum basilicum 'Genovese Gigante') and bellflower (Campanula portenschlagiana ‘Get Mee’), were monitored. The variation was not significantly related to growth performance, indicating plants can tolerate a range of growing substrate VWC for acceptable growth performance. Thresholds of 0.25 m3·m-3 for basil and 0.15 m3·m-3 for bellflower were determined to be the optimal growing substrate VWC at which irrigation should occur. A decision support system (DSS) was designed to control irrigation of a crop of bellflower at a commercial greenhouse, alongside the grower’s crop. At the end of the production cycle, the plants managed by the DSS the same quality as those managed by the commercial grower. en_US
dc.language.iso en en_US
dc.subject Research Subject Categories en_US
dc.subject Environmental Science en_US
dc.subject Automation en_US
dc.subject Greenhouse en_US
dc.subject Irrigation en_US
dc.subject Ornamental production en_US
dc.subject Vegetable production en_US
dc.subject Greenhouse management en_US
dc.title Improving Greenhouse Irrigation Through A Sensor-Based Decision Support System en_US
dc.type Thesis en_US
dc.degree.programme Environmental Sciences en_US
dc.degree.name Master of Science en_US
dc.degree.department School of Environmental Sciences en_US
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