Logo des Repositoriums
 

Evaluation of a decision support system for the recommendation of pasture harvest date and form

Kurzanzeige
dc.contributor.authorReuter, Tobias
dc.contributor.authorSaborío Morales, Juan Carlos
dc.contributor.authorTieben, Christoph
dc.contributor.authorNahrstedt, Konstantin
dc.contributor.authorKraatz, Franz
dc.contributor.authorMeemken, Hendrik
dc.contributor.authorHünker, Gerrit
dc.contributor.authorLingemann, Kai
dc.contributor.authorBroll, Gabriele
dc.contributor.authorJarmer, Thomas
dc.contributor.authorHertzberg, Joachim
dc.contributor.authorTrautz, Dieter
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.accessioned2023-02-21T15:14:18Z
dc.date.available2023-02-21T15:14:18Z
dc.date.issued2023
dc.description.abstractThe task of generating automatic recommendations of pasture harvest date and form was previously addressed through a knowledge-based decision support system (DSS). The system follows expert rules and exploits data such as the weather history and forecast, the growth stage of grass and legumes, plant height and crude fibre content. In this paper, we present the results of our evaluation of this DSS on 26 fields in West and Northwest Germany. We compared the suggestions made by the DSS with the decisions of expert farmers and obtained an accuracy of R²=0.746 and RMSE=7.83 days. The best results occurred for intensively managed fields for dairy cows, with an R² of 0.891 and RMSE of 3.20 days. We conclude our DSS and its underlying methodology have the potential to support farmers and secure high-quality fodder.en
dc.identifier.isbn978-3-88579-724-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/40297
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.subjectexpert system
dc.subjectgrassland harvesting
dc.subjectforage
dc.subjectknowledge representation
dc.subjectdecision-support
dc.titleEvaluation of a decision support system for the recommendation of pasture harvest date and formen
dc.typeText/Conference Paper
gi.citation.endPage494
gi.citation.publisherPlaceBonn
gi.citation.startPage489
gi.conference.date13.-14. Februar 2023
gi.conference.locationOsnabrück

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
GIL_2023_Reuter_489-494.pdf
Größe:
633.33 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P330 - 43. GIL-Jahrestagung 2023 - Fokus: Resiliente Agri-Food-Systeme