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Land and Water



Multifunctional Decision Support System for Agricultural practices (S.E.DE.M.A.)


April 2009 – April 2011

Financed by

European Regional Development Fund (ERDF)


1. 2. 3. 4.

SysMan Informatics Projects and Services s.r.l. – Italy, coordinator Mediterranean Agronomic Institute of Bari (CIHEAM-MAIB) - Italy National Research Council – Institute of Food Production Science (CNR-ISPA) - Italy STC Science Technology Consulting s.r.l. – Italy

Main objective

To design (at a pre-industrial stage) a multifunctional decision support system for the management of agricultural practices at farm level, through the integration of different “modules” (irrigation scheduling, fertilizer application and pest control); To integrate the simulation models and knowledge coming from agricultural literature and practices with the more advanced technologies available in computer science, irrigation systems and agro-meteorology; To develop a computer-based information “platform” able to receive, integrate and process heterogeneous data coming from different sources (e.g. on-field weather and plant/soil sensors, soil/crop research databases, high resolution forecasting weather data, remote controlled devices); To test the main algorithms developed on the basis of deterministic and fuzzy logic models, with respect to their effectiveness to simulate water and nutrient balance and to support irrigation scheduling as well as fertilizer application; To evaluate the overall applicability and usefulness of the system for farmers and technicians, as well as the reliability of the information provided to final users by means of web services and/or professional (rugged tablet, computers) or user-friendly (smart-phone) electronic devices; To enable users for the automation and remote control of irrigation system equipments (hydrants, electric valves).

MAIB activities

To contribute in the design of the decision support system for the management of agricultural practices at farm level. To develop the irrigation module of DSS including the soil water balance model, crop growth routine, irrigation scheduling strategy and crop-response-to-water function. To contribute in the design of the algorithms applied for the forecasting of weather data and consecutive decision support related to the irrigation water supply. To test the performances of the irrigation module using available experimental data, in order to calibrate model parameters and to validate model for specific local agro-pedo-climatic conditions;

Project web page

projects sheets 23  
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