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CORDIS

Soil Quality Analysis Tool: Implementing Smart Farming Applications using EO Data, Soil Sensors & Robotics

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

D2.6: User manual for System using SQAT Robots (öffnet in neuem Fenster)

A technical user manual detailing procedures for field use of both robots used by the SQAT smart soil mapping system. (Leader: EV ILVO, M18/M33, R, PU)

D1.1 Management & coordination plan (öffnet in neuem Fenster)

a strategic document defining the management structure and operating procedures, as well as their implementation (including measure, KPIs and milestones). The plan will also contain a categorization of risks, with specific mitigation measures and approaches.

D1.2 Gender equality & ethics management plan (öffnet in neuem Fenster)

the document will enclose detailed strategies on how the project will ensure gender equality and proper ethics management in its activities (Lead: ABE, M03, ETHICS, PU)

D2.1: Use case implementation plans (öffnet in neuem Fenster)

A document detailing specific activities across a timeline for deployment of the use cases. It will also define the evaluation methodology to be used (Leader: ABE, M03, R, PU)

D4.2: Data governance principles: (öffnet in neuem Fenster)

A report providing a tailored solution of data goverance principles for SQATand a set of measures to apply them to use cases (Leader: FarmEye, M06, Report, PU)

D5.1: Exploitation, dissemination, and communication strategy (öffnet in neuem Fenster)

A document detailing the project’s strategic approach to exploitation, dissemination, and communication activities, on the basis of KPI-driven objectives, target and audience differentiation (Leader: ABE, M03, Report, PU)

D4.1: Data Management Plan (öffnet in neuem Fenster)

A data management plan document in line with the FAIR principles to promote project data to be findable, accessible, interoperable and reusable (Leader: FarmEye, M08, DMP, PU)

D5.2: Communication kit and project website (öffnet in neuem Fenster)

A package of materials for partners to use to promote the project and the project website. (Leader: ABE, M03, DEC, PU)

D2.5: Lightweight and heavy-duty sampler device with proximity sensors (öffnet in neuem Fenster)

An electro-mechanical arm attachable to robotic platforms for soil sampling in different soil conditions. (Leader: ILT-OST, M18, OTHER, PU)

Veröffentlichungen

Overfitting due to data leakage in soil sensor calibration: Examples from lab-based and in-situ soil NIR spectroscopy (öffnet in neuem Fenster)

Autoren: José Correa, Hamed Tavakoli, Sebastian Vogel, Robin Gebbers
Veröffentlicht in: Computers and Electronics in Agriculture, Ausgabe 239, 2025, ISSN 0168-1699
Herausgeber: Elsevier BV
DOI: 10.1016/J.COMPAG.2025.110920

Multi-Source Data Integration for Sustainable Management Zone Delineation in Precision Agriculture (öffnet in neuem Fenster)

Autoren: Dušan Jovanović, Miro Govedarica, Milan Gavrilović, Ranko Čabilovski, Tamme van der Wal
Veröffentlicht in: Sustainability, Ausgabe 17, 2025, ISSN 2071-1050
Herausgeber: MDPI AG
DOI: 10.3390/SU17156931

Development and In-Field Validation of an Autonomous Soil Mechanical Resistance Sensor (öffnet in neuem Fenster)

Autoren: Valentijn De Cauwer, Simon Cool, Axel Willekens, Sébastien Temmerman, David Nuyttens, Tommy D’ Hose, Jan Pieters, Sam Leroux
Veröffentlicht in: Sensors, Ausgabe 25, 2025, ISSN 1424-8220
Herausgeber: MDPI AG
DOI: 10.3390/S25061919

Which and how many soil sensors are ideal to predict key soil properties: A case study with seven sensors (öffnet in neuem Fenster)

Autoren: J. Schmidinger, V. Barkov, H. Tavakoli, J. Correa, M. Ostermann, M. Atzmueller, R. Gebbers, S. Vogel
Veröffentlicht in: Geoderma, Ausgabe 450, 2024, ISSN 0016-7061
Herausgeber: Elsevier BV
DOI: 10.1016/J.GEODERMA.2024.117017

Effect of training sample size, sampling design and prediction model on soil mapping with proximal sensing data for precision liming (öffnet in neuem Fenster)

Autoren: Jonas Schmidinger, Ingmar Schröter, Eric Bönecke, Robin Gebbers, Joerg Ruehlmann, Eckart Kramer, Vera L. Mulder, Gerard B. M. Heuvelink, Sebastian Vogel
Veröffentlicht in: Precision Agriculture, Ausgabe 25, 2024, ISSN 1385-2256
Herausgeber: Springer Science and Business Media LLC
DOI: 10.1007/S11119-024-10122-3

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