A novel approach for real time forecasting and mapping of potato late blight in Cyprus

Potato production is one of the most important sectors of the agricultural economy in Cyprus. Late blight (Phytoph-thora infestans) is the most destructive disease of potato, causing severe losses especially in humid years. To prevent yield losses potato producers apply fungicides based on empirical...

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Bibliographic Details
Published inPhytopathologia mediterranea Vol. 48; no. 2; p. 341
Main Authors Tsaltas, D, Pittas, L, Neophytou, G, Fellas, P, Hadjimitsis, D, Laghos, A, Ioannou, N
Format Journal Article
LanguageEnglish
Published 01.08.2009
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Summary:Potato production is one of the most important sectors of the agricultural economy in Cyprus. Late blight (Phytoph-thora infestans) is the most destructive disease of potato, causing severe losses especially in humid years. To prevent yield losses potato producers apply fungicides based on empirical and calendar information. This approach is of moderate effectiveness and frequently leads to excessive pesticide use, with negative inpact to the environment and human health. In the context of a 3-year research project aiming to introduce to Cyprus a late blight forecasting scheme, during 2007-2008 a network of agrometeorological stations was established in the potato growing area of Kokkinochoria. These stations broadcast wirelessly the micro-environmental conditions, and forecasting models are run to suggest respective spraying schemes. The forecasting schemes are compared to the conventional control practice with a view to develop a prognosis system that would achieve a significant reduction of fungicide application combined with satisfactory control of late blight. The data from the weather stations and the results of the forecast schemes will be incorporated on a web-based Geographic Information System (GIS) platform that will eventually be freely accessible to agronomists and growers. This platform is expected to enhance the dissemination of information while providing new possibilities to researchers for the development of more detailed prognosis models, adjusted to local conditions.
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ISSN:0031-9465