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Knowledge based support systems, to assist crop management decisions, are required to ensure that the treatments applied are economically advantageous and environmentally acceptable. The knowledge base may contain predictive models for various aspects of crop management such as crop growth, disease susceptibility, nutrient and irrigation requirements. Agrometerological data is an essential input to the knowledge base and there is a need to develop a standardized format for this that will allow interfacing with predictive models and farm management systems. Work is being done to select and integrate some well tested predictive models with agrometerological data networks to create interactive decision support systems for farm management.
Software is being developed for 3 crops, namely, wine graphs, apples and wheat that can be used to improve the accuracy of farmers' weather related decisions, in particular, the timing and frequency of chemical applications and irrigation. Formats of meterological data used in agrometerological networks have been collected and compared. A programme is being developed for transferring data from weather stations to microcomputers via telephone lines for storing the data in a structural query language (SQL) database. Predictive models have been surveyed for wine graphes, apples, wheat and irrigation and some of these are being adapted for implementation. These include models for evapotranspiration, water balance and plant development and models covering a range of vine diseases. In particular, the model of risk analysis for plasmopara viticola is being developed for the north of Italy.
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