Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/5319

Title: A Business Intelligence Approach to Support a Greenhouse Tomato Crop Grey Mould Disease Early Warning System
Authors: Neto, Miguel
Baptista, Fátima
Navas, L.M.
Ruiz, G.
Editors: Mildorf, Thomas
Charvat jr, Karel
Keywords: warning system
botrytis
Issue Date: 2012
Publisher: Czech Centre for Science and Society
Citation: MIGUEL DE CASTRO NETO, FÁTIMA BAPTISTA, LUIS MANUEL NAVAS and GONÇALO RUIZ. 2012. A Business Intelligence Approach to Support a Greenhouse Tomato Crop Grey Mould Disease Early Warning System. Pp 175-184. In ICT for Agriculture, Rural Development and Environment. Eds. Thomas Mildorf and Karel Charvat jr. Czech Centre for Science and Society. 332 pp. ISBN: 978-80-905151-0-9
Abstract: This paper presents a Business Intelligence architecture proposal, including data sources, data warehouse, business analytics, and information delivery, to launch an early warning system for greenhouse tomato crop grey mould disease. Tomato is a very important crop in the Mediterranean region in general and in Portugal in particular being the production for fresh consumption made essentially in greenhouses. Botrytis cinerea Pers.: Fr. is the causal agent of grey mould disease and is one of the most important diseases affecting greenhouse tomato crops, high relative humidity and the presence of free water on the plant surfaces have been recognized as favourable to the development of this disease. The availability of a early warning system providing to the tomato grower alerts with information of the potential favoured conditions for the disease appearance in its early stages or even before can have a very positive impact in reducing the economic and environmental impacts due to a more rational and efficient disease control management. Today we have the necessary technology to build and launch an Internet based early warning system for grey mould disease in greenhouse tomato crop supported by a wireless sensor network adopting a Business Intelligence approach. From the research conducted until the moment the proposed solution is viable and the next step will be to validate it in the field in different locations and with distinct greenhouses conditions.
URI: http://hdl.handle.net/10174/5319
Type: bookPart
Appears in Collections:MED - Publicações - Capítulos de Livros
ERU - Publicações - Capítulos de Livros

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