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Towards model-based automation of plant-specific weed regulation

dc.contributor.authorRenz, Marian
dc.contributor.authorNiemeyer, Mark
dc.contributor.authorHertzberg, Joachim
dc.contributor.editorHoffmann, Christa
dc.contributor.editorStein, Anthony
dc.contributor.editorRuckelshausen, Arno
dc.contributor.editorMüller, Henning
dc.contributor.editorSteckel, Thilo
dc.contributor.editorFloto, Helga
dc.date.accessioned2023-02-21T15:13:54Z
dc.date.available2023-02-21T15:13:54Z
dc.date.issued2023
dc.description.abstractWeeds are commonly known as a major factor for yield losses in agriculture, competing with crops for resources like nutrients, water, and light. However, keeping specific weeds could benefit agricultural sites for example by nitrogen fixation, erosion protection, or increasing biodiversity. This comes with technological challenges like plant detection and classification, damage estimation, and selective removal. This paper presents a model-based approach to the problem of damage estimation of perceived plants. The system uses contextual and background knowledge in the form of rules about the plant count per square meter and the distance to the nearest crop together with thresholds for each weed species. The functionality is demonstrated using an artificial dataset and exemplary thresholds, showing the potential of using knowledge about plant-crop interactions for more sophisticated weed control systems.en
dc.identifier.isbn978-3-88579-724-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/40252
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-330
dc.subject: selective weeding
dc.subjectbiodiversity
dc.subjectrule-based reasoning
dc.titleTowards model-based automation of plant-specific weed regulationen
dc.typeText/Conference Paper
gi.citation.endPage218
gi.citation.publisherPlaceBonn
gi.citation.startPage207
gi.conference.date13.-14. Februar 2023
gi.conference.locationOsnabrück

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