Application scenarios

Application scenarios

 

This Learning Object is part of Master AGRITECH EU – Digital Agriculture for Sustainable Development, an Italian one-year specialisation programme organised by University of Pisa, University of Macerata, National Research Council (CNR) and Quinn Consortium (Consorzio Quinn)

For more information about the programme and to enroll here

It is possible to enroll for the whole programme or for the single Learning Object (Module) you are interested in

Module details

Presentation of application scenarios in the fields of Agronomy, Agricultural Engineering (Agricultural Hydraulics and Mechanics), Defense (Plant Pathology), Plant Production (Arboriculture and Greenhouse Cultivation), and Animal Production (Animal Science).


Proposer: University of Pisa (UNIPI)

Organization: University of Pisa (UNIPI), National Reasearch Council (CNR), University of Macerata (UNIMC)

Duration: 60h

ECTS: 11

Shortcut access code: No

Year of pubblication: 2026

Topics

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Delivery methods: On Line

Teaching methods: Lectures, Working Group

Languages:

Learning objectives
  • Herbaceous crops
  • Tree crops
  • Animal husbandry
  • Greenhouse crops
  • Wildlife management
  • Supply chain traceability systems

     
  • Principles of precision viticulture and olive growing

    Precision viticulture and olive growing under climate change


    Description: Principles of precision viticulture and olive growing: farmers needs, digital solutions and field zoning in a climate change scenario
    Duration: 4h
    Teacher: Caruso (DISAAA - Department of Agriculture Food and Environment)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Site Specific Weed Management

    SSWM: a case study


    Description: This unit examines how digital technologies — including remote sensing, AI, and precision application systems — enable site-specific identification and targeted management of weeds, reducing herbicide use and improving crop sustainability.
    Duration: 2h
    Teacher: Silvestri (DISAAA - Department of Agriculture Food and Environment)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Automation and robotics in agriculture

    Automation and robotics in weed control and plant protection


    Description: Introduction farm machinery, automation in vegetables and AI,automation in vineyard and automation in landscape,sport,urban green areas
    Duration: 6h
    Teacher: Fontanelli, Luglio, Gagliardi, Fontani (DISAAA - Department of Agriculture Food and Environment)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Variable Rate Application (VRA I)

    VRA of fertilizers from satellite data


    Description: VRA of fertilizers from satellite data
    Duration: 4h
    Teacher: Soccolini, Schilardi (AGRICOLUS)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Smart tools for livestock

    Architecture, technical characteristics, functioning and importance in monitoring animal welfare, behaviour and performance


    Description: Developing smart tools for livestock pest monitoring (stable flies and tabanids): trap development and hands on data analysis. Sensors in livestock farming systems: architecture, technical characteristics, functioning and importance in monitoring animal welfare, behaviour and performance
    Duration: 4h
    Teacher: Mantino (DISAAA - Department of Agriculture Food and Environment)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Bioinspired and smart tools for behavioral research in insect science

    This unit examines smart and bioinspired technologies used to study insect behavior for pest management and sustainable agriculture


    Description: This unit explores bioinspired and smart tools — including sensors, robots, and AI-driven systems — applied to the study of insect behavior, with implications for pest management and sustainable agriculture
    Duration: 8h
    Teacher: Benelli (DISAAA - Department of Agriculture Food and Environment)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Sensors management

    Agrohydrological sensors and models for soil and plant water status monitoring


    Description: This unit covers the principles of sensor management in agricultural environments, addressing the selection, deployment, calibration, and integration of sensing devices to ensure reliable and efficient data collection in the field.
    Duration: 8h
    Teacher: Rallo (DISAAA - Department of Agriculture Food and Environment)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Influence of the climate parameters

    This unit explores how climate factors affect crop growth and productivity, and how digital technologies can be used to monitor and manage their variability


    Description: This unit examines how climate parameters — such as temperature, humidity, and rainfall — influence crop growth and agricultural productivity, and how digital technologies can help monitor and respond to their variability
    Duration: 8h
    Teacher: Incrocci (DISAAA - Department of Agriculture Food and Environment), Kocian (DI - Department of Computer Science), Affinito (EVJA)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Introduction to advanced technologies for Plant Pathology

    This unit presents advanced digital technologies used to detect, monitor, and manage plant diseases in modern agriculture


    Description: This unit introduces advanced digital technologies — including remote sensing, AI, and imaging tools — applied to the early detection, monitoring, and management of plant diseases in modern agricultural systems.
    Duration: 8h
    Teacher: Cotrozzi, Landi (DISAAA - Department of Agriculture Food and Environment)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

    •  
  • Data analysis

    This unit examines how data analysis is used in agriculture to turn field data into useful insights for decision-making


    Description: This unit explores how data analysis techniques are applied to real-world agricultural scenarios, enabling students to extract meaningful insights from field data to support informed decision-making
    Duration: 8h
    Teacher: Mele, Mantino (DISAAA - Department of Agriculture Food and Environment)
    Delivery method: On Line
    Teaching method: Lectures, Working Group

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