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Repository for the UNIBO data production of the ICT-AGRI SHEET project



What is the purpose of the SHEET project?
Purpose of SHEET (Sunburn and HEat prediction in canopies for Evolving a warning Tech solution - https://ictagrifood.eu/node/44656) project is to develop risk prediction models for heat damage in the fruit production and transfer the model in a functional mobile application on the smart phone.

Global radiation and temperature rise cause huge risks for the fruit production already affecting the fruit quality, storability, and increasingly results in food waste. Experimental data will capture apple, grape, and sweet cherry production in varying elevation, global radiation, and precipitation.

The project SHEET is part of the ERA-NET Cofund ICT-AGRI-FOOD, with funding provided by national sources and co-funding by the European Union’s Horizon 2020 research and innovation program, Grant Agreement number 862665.

Which type of data will produce the project?
Experimental data will capture seasonal weather data as well as fruit temperature, fruit sunburn (SB) occurrence and SB symptoms level, in varying climatic condition, on apple, cherry and grape fruit species.

More information regarding the SHEET project outcomes from all the partners can be found HERE


This page will remain under development / update until the end of 2024

Involved people at UniBo

Institution: University of Bologna

Full Name contact role
Brunella Morandi [email protected] Project Head and research on apple physiology
Luigi Manfrini [email protected] Research on apple physiology
Alexandra Boini [email protected] Research on apple physiology
Crisitano Franceschini [email protected] Research on apple physiology
Michele Gullino --- Research on apple physiology
Gianmarco Bortolotti [email protected] Research on apple physiology and tech development
Mirko Piani [email protected] Data management - tech development - Programmer
Dario Mengoli [email protected] Data management - tech development - Programmer
Nicolò Omodei [email protected] Data management - tech development - Programmer
Simone Rossi [email protected] Data management - tech development - Programmer
Ilaria FIlippetti [email protected] Research on grape physiology
Gianluca Allegro [email protected] Research on grape physiology
Daniela Sangiorgio [email protected] Research on grape physiology
Chiara Pastore [email protected] Research on grape physiology

Project timeline and results obtained

The SHEET project has been programmed to start in 2021 and to end in 2024.

2021- 2022

2022 - 2023

2023 - 2024

2024

  • Realease of Open Acces Apple Fruit position and temperature data [documentation here]: After the last season of data collection, a chomprehensive dataset of the climatic, physiological and fruit quality (Apple) data collected during the project was released.
    It contains data of the trial site in Cadriano (Bologna, Italy) - at the experimental farm of the University of Bologna (44.54824 °N, 11.41449 °E) - organized by years (2021, 2022, and 2023) and related to:

    • continuos weather data, continuos microclimatic data of orchard conditions tested (2021 and 2022 only)
    • discrete radiation measurements of the illumination condition of each tested treatment,
    • continuos measurements of apple fruit surface temperature collected with thermocouples
    • discrete measurements of apple fruit surface temperature collected with handheld thermal camera (2022, 2023 only)
    • 3D position of the fruit monitored for surface temperature,
    • discrete measurements of apple fruit surface temperature and position collected with an RGB-D/ Thermal scanning platform prototype (2022 only),
    • discrete measurement reporting the moment of sunburn damage occurrence, its level, L*a*b* chroma and Hue color information, and DA-meter index values.
  • Realease of SHEET project - Unibo Computer Vision Final Repository[documentation here]: The repository contains all the computer-vision related datasets and models developped during the project. The repository contains:

    • YOLOv5 models for apple fruit, grape cluster, and tree trunk detections
    • YOLOv8 models for colse fruit detection + sunburn symptomps classification
    • Annotated datasets used for the training of each model
    • Code scripts used to manage data and train the models

Pubblications

Fundings

This work was supported by the SHEET European project. The project SHEET (Sunburn and heat prediction in canopies for evolving a warning tech solution) is part of the ERA-NET co-funded ICT-AGRI-FOOD, with funding provided by national sources (Italian Ministry of the University and Research) and co-funding by the European Union’s Horizon 2020 research and innovation program, Grant Agreement number 862665. https://ictagrifood.eu/node/44656

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