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作者机构:Univ Florida Gainesville FL USA Univ Florida Gulf Coast Res & Educ Ctr Wimauma FL USA
出 版 物:《COMPUTERS AND ELECTRONICS IN AGRICULTURE》 (农用计算机与电子设备)
年 卷 期:2011年第75卷第1期
页 面:169-175页
核心收录:
学科分类:09[农学] 0901[农学-作物学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:USDA-Risk Management Agency (USDA-RMA)
主 题:Climate Simulation modeling Decision support system Web-based interface Google Maps
摘 要:Florida produces about 16 million flats of strawberries every year, 15% of berries produced in the U.S. and virtually all the berries grown in the winter. Fungicides are applied on a weekly schedule to control Anthracnose and Botrytis fruit rot from December through March. Different predictive models for these diseases were evaluated and systems developed to time fungicide applications that reduced the number of sprays by about 50%. The models utilized leaf wetness and temperature during the wet period to predict disease outbreaks. The most effective models were embedded in a web-based tool developed for use by growers to schedule their fungicide applications. This internet-based forecasting system to predict these diseases, the Strawberry Advisory System (SAS), was implemented on the AgroClimate website using weather data from the Florida Agricultural Weather Network. Growers can select the location closest to their plantings and SAS will provide a prediction of disease incidence and recommendations for fungicide applications. Users can also be provided warnings of the need to spray via email or text messages. In preliminary trials, SAS has been successful in eliminating many unnecessary fungicide applications and has proven user friendly. (C) 2010 Elsevier B.V. All rights reserved.