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dc.contributor.authorUtstumo, Trygve
dc.contributor.authorUrdal, Frode
dc.contributor.authorBrevik, Anders
dc.contributor.authorDørum, Jarle
dc.contributor.authorNetland, Jan
dc.contributor.authorOverskeid, Øyvind
dc.contributor.authorBerge, Therese W.
dc.contributor.authorGravdahl, Jan Tommy
dc.date.accessioned2019-03-28T13:10:22Z
dc.date.available2019-03-28T13:10:22Z
dc.date.created2018-09-14T20:43:54Z
dc.date.issued2018
dc.identifier.citationComputers and Electronics in Agriculture. 2018, 154 36-45.nb_NO
dc.identifier.issn0168-1699
dc.identifier.urihttp://hdl.handle.net/11250/2592250
dc.description.abstractVegetables and other row-crops represent a large share of the agricultural production. There is a large variation in crop species, and a limited availability in specialized herbicides. The robot presented here utilizes systematic growing techniques to navigate and operate in the field. By the use of machine vision it separates seeded vegetable crops from weed. Each weed within the row is treated with individual herbicide droplets, without affecting the crop. This results in a significant reduction in herbicide use, and allows for the use of herbicides that would otherwise harm the crop. The robot is tailored to this purpose with cost, maintainability, efficient operation and robustness in mind. The three-wheeled design is unconventional, and the design maintains maneuverability and stability with the benefit of reduced weight, complexity and cost. Indoor pot trials with four weed species demonstrated that the Drop-on-Demand system (DoD) could control the weeds with as little as 7.6 μg glyphosate or 0.15 μg iodosulfuron per plant. The results also highlight the importance of liquid characteristics for droplet stability and leaf retention properties. The common herbicide glyphosate had no effect unless mixed with suitable additives. A field trial with the robot was performed in a carrot field, and all the weeds were effectively controlled with the DoD system applying 5.3 μg of glyphosate per droplet. The robot and DoD system represent a paradigm shift to the environmental impact and health risks of weed control, while providing a valuable tool to the producers.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleRobotic in-row weed control in vegetablesnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber36-45nb_NO
dc.source.volume154nb_NO
dc.source.journalComputers and Electronics in Agriculturenb_NO
dc.identifier.doi10.1016/j.compag.2018.08.043
dc.identifier.cristin1609730
dc.relation.projectNorges forskningsråd: 234226nb_NO
dc.description.localcode© 2018. This is the authors’ accepted and refereed manuscript to the article. Locked until 7.9.2020 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/nb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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