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Modelling Outcrossing of Transgenes in Maize Between Neighboring Maize Fields

dc.contributor.authorDebeljak, Marko
dc.contributor.authorDemšar, Damjan
dc.contributor.authorDžeroski, Sašo
dc.contributor.authorSchiemann, Joachim
dc.contributor.authorWilhelm, Ralf
dc.contributor.authorMeier-Bethke, Sara
dc.contributor.editorHřebíček, J.
dc.contributor.editorRáček, J.
dc.date.accessioned2019-09-16T09:34:32Z
dc.date.available2019-09-16T09:34:32Z
dc.date.issued2005
dc.description.abstractWe analyze data about the flow of pollen and more specifically the outcrossing from genetically modified maze to conventional maze to determine the most important factors influencing the flow. The machine learning technique of regression tree induction is used to build models that predict the degree of outcrossing from data on the relative position of the donor and recipient fields and the winds, as well as several variables derived from these (especially considering flowering times). The resulting models show that the distance between the fields plays a dominant role, followed by the angle and the percentage of appropriate wind (blowing from the donor to the recipient field).de
dc.description.urihttp://enviroinfo.eu/sites/default/files/pdfs/vol112/0610.pdfde
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/27287
dc.publisherMasaryk University Brno
dc.relation.ispartofInformatics for Environmental Protection - Networking Environmental Information
dc.relation.ispartofseriesEnviroInfo
dc.titleModelling Outcrossing of Transgenes in Maize Between Neighboring Maize Fieldsde
dc.typeText/Conference Paper
gi.citation.publisherPlaceBrno
gi.conference.date2005
gi.conference.locationBrno
gi.conference.sessiontitleModelling, simulation and computing

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