SUSTAGRI: Academic contents

More information on the Master´s degree

Learning outcomes

LO1. To know the types of data that are necessary or generated in and for agricultural activity.
LO2. Know the main sensors and types of images obtained by remote sensing and be able to process them and perform time series analysis based on the information obtained from them.
LO3. Know the basics of geographic information systems applied to agronomy as well as the tools to incorporate them for use in decision making, diagnosis, other tools, etc.
LO4. Know the main applications of remote sensing in agriculture, including crop identification inferring soil and water properties, crop monitoring and detection of anomalies.
LO5. To know the most important hardware linked to various sensors, actuators and loT and te main architectures and communication protocols and their agricultural applictions (agrimet sensors, soil moisture probes, soil nutrient sensors, plant-based sensors, proximal sensors).
LO14. To be able to generate, capture, manage, store, transfer, analyse and interpret all types of information from in situ or remote sensing sensors for direct exploitation or for use as inputs to other tools.
LO15. To be able to develop software in an autonomous way that allows the management of databases coming from in situ sensors or remote sensing for their direct exploitation or for their use as inputs to other tools.

LO6. To understand the components of precision agriculture: Data, Global Navigation Systems, Managing variability, Decision support sistems, and Precision machinery.
LO7. To know about soils, soil properties, fertility, soil water, soil analysis, and surveys.
LO8. To understand spatial variability, geostatistics, spatial interpolation, and inference.
LO9. To know about soil preparation, seeding machinery, variable rate fertilization equipment, and precision technoligies for crop protection and harvesting.
LO10. To understand preventive decision making and reactive management using real-time data.
LO16. To be able to apply precision agriculture to enhance farm profitability and promote sustainability.
LO17. To be able to deal with soil variability, make decisions, and apply variable rate philosophy.
LO18. To understand global navigation systems, RTK, differential corrections, and optimization of routes.
LO19. To be able to integrate data from varied sources and use digital tools for data integration and decision support systems.
LO20. To be able to design and plan a farm to be treated as precision agriculture.

LO11. Know how to model crop water requirements using advanced approaches and technologies.
LO12. Learn to model for sustainable irrigation, assessing impacts and implementing best management practices such as vegetative filters as a sustainable tool for water and sediment management.
LO13. Know the most important European agri-environmental legislation, with special focus on soil conservation, agricultural waters, sustainable agriculture and irrigation.
LO21. Be able to process available information to use spatially distributed water balance models for optimized water application.
LO22. Be proficient in smart design and management of irrigation systems, employing mathematical modelling and operational strategies.
LO23. Be able to make decisions to implement smart irrigation activities, including. Irrigation automation and scheduling; precision irrigation, variable dosage.
LO24. To be able to share technology and transfer for entrepreneurship, focusing on commercialization and innovation diffusion.

LO25. Independently develop, present and defend an original professional project before a university tribunal, demonstrating the synthesis and application of knowledge, skills and competences acquired throughout the master degree.