In the framework of the on-going research project E-Crops, several Precision Agriculture (PA) technologies are under development and testing in Italy for different agricultural systems and fields of application, at both farm and district scales. All data and information provided by these PA technologies are integrated in a common cloud platform and elaborated by a new DSS (Decision Support System), developed by ICT companies and research institutions, with the effective involvement of relevant agricultural stakeholders for preliminary field testing of software functions. The paper provides a general description of the DSS platform, in relation to: i) general software architecture; ii) key technologies and data integrated (weather data, remote sensing, soil-plant sensors, crop imaging, etc.); iii) main software modules and interfaces (Web/App); iv) list of relevant fields of application (irrigation, fertilization, disease control, yield and quality management, climate analysis, etc.), with related data sources, algorithms and approaches (model-driven vs data-driven). Finally, the following examples of application are briefly described: a) mapping fertilization requirements for open-field crops, by integrating remote sensing data, geo-spatial information and models of crop-soil nutrient balance; b) monitoring of water status and irrigation requirements of greenhouse crops, by comparing sensor-based with model-based indicators; c) estimating fruit load and quality in horticultural crops, by integrating biometric parameters, image analysis, on-field sampling and laboratory analytical data processing.
E-Crops DSS: software architecture, technologies, main functions, and examples of application
Montesano F;
2023-01-01
Abstract
In the framework of the on-going research project E-Crops, several Precision Agriculture (PA) technologies are under development and testing in Italy for different agricultural systems and fields of application, at both farm and district scales. All data and information provided by these PA technologies are integrated in a common cloud platform and elaborated by a new DSS (Decision Support System), developed by ICT companies and research institutions, with the effective involvement of relevant agricultural stakeholders for preliminary field testing of software functions. The paper provides a general description of the DSS platform, in relation to: i) general software architecture; ii) key technologies and data integrated (weather data, remote sensing, soil-plant sensors, crop imaging, etc.); iii) main software modules and interfaces (Web/App); iv) list of relevant fields of application (irrigation, fertilization, disease control, yield and quality management, climate analysis, etc.), with related data sources, algorithms and approaches (model-driven vs data-driven). Finally, the following examples of application are briefly described: a) mapping fertilization requirements for open-field crops, by integrating remote sensing data, geo-spatial information and models of crop-soil nutrient balance; b) monitoring of water status and irrigation requirements of greenhouse crops, by comparing sensor-based with model-based indicators; c) estimating fruit load and quality in horticultural crops, by integrating biometric parameters, image analysis, on-field sampling and laboratory analytical data processing.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.