001050250 001__ 1050250
001050250 005__ 20260108204825.0
001050250 037__ $$aFZJ-2026-00062
001050250 1001_ $$0P:(DE-Juel1)204405$$aGrygosch, Lars$$b0$$eCorresponding author$$ufzj
001050250 1112_ $$aEuropean Plant Phenotyping Symposium$$cBonn$$d2025-09-16 - 2025-09-19$$gEPPS$$wGermany
001050250 245__ $$a[meta]data for non-invasive field phenotyping
001050250 260__ $$c2025
001050250 3367_ $$033$$2EndNote$$aConference Paper
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001050250 520__ $$aRecent advancements in non-invasive sensor systems have revolutionized plant phenotyping field studies. Proximal sensing technologies along with remote sensingfrom satellites, aircrafts, and UAVs, now enable non-destructive measurements at different scales under realistic environmental conditions. These technologies,however, produce vast and complex datasets, making sophisticated data management strategies critical for enhancing the findability, accessibility, interoperability,and reusability (FAIR) of data. To address this, we are developing a benchmark dataset that exemplifies typical field phenotypic and remote sensing data, supportedby templates and guidelines for effective data management.
001050250 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0
001050250 536__ $$0G:(GEPRIS)501899475$$aDFG project G:(GEPRIS)501899475 - FAIRe Dateninfrastruktur für die Agrosystemforschung (501899475)$$c501899475$$x1
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001050250 980__ $$aI:(DE-Juel1)IBG-2-20101118
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