POMOSAT - ‘An Orchard System for Monitoring and Modeling Apple Scab (Venturia Inaequalis)’

نویسنده

  • Romica TRANDAFIR
چکیده

Apple scab, Venturia inaequalis, is the most serious fungal disease of apple in Romania. The fungus attacks foliage, blossoms and fruits by defoliating trees and rendering fruit unmarketable. In addition, to cultivated apple, apple scab also attacks flowering crabapple, mountain ash and firethorn.. A simple system for apple growers to monitor environmental weather data (temperature and leaf wetness particularly) to be used in models for predicting apple scab infection periods would make their fungicide application(s) more timely and accurate, thereby potentially reducing pesticide use, improving disease control, and saving money. Additionally, raw weather data and model output can now be easily shared regionally via the Internet to be used by neighboring growers. Such a system has recently become feasible with the availability of inexpensive electronic weather data monitors, personal computer (PC) based models, e-mail delivered weather data and models by commercial services(s), and grower familiarity with PC’s and the Internet. In this paper I present apple scab related with our project objectives: 1. Establish a series of onsite weather stations that collect data, which can be used in models to predict apple scab infection periods. Such models will help growers determine the need (or lack of) for fungicide sprays to control apple scab based on accurate environmental information previously unavailable to them. 2. Post weather and apple scab infection period information from these orchards on the Voinesti Fruit Grower’s Association web site (http://www.pomosat.ro) for neighboring growers access and use in helping them make fungicide application decisions. 3. Compare weather data collected by onsite weather stations in trial orchards to ANMH-Weather information, particularly when used in models to predict apple scab infection periods. Survey trial growers to ascertain their preference, and be able to make recommendations to other growers based on their preference.

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تاریخ انتشار 2008