Using machine learning to predict the impact of agricultural factors on communities of soil microarthropods

D. Dem?ar, S. D?eroski, P. H. Krogh, T. Larsen

    Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

    Abstract

    With the newly arisen ecological awareness in the agriculture the sustainable use and development of the land is getting more important. With the sustainable use of soil in mind, we are developing a decision support system that helps making decisions on managing agricultural systems and is able to handle both conventional and genetically modified crops as a part of the ECOGEN project. The decision support system considers economical and agricultural factors and actions including crop selection, crop sequence, pest and weed control actions etc. For such decision support system to work, it needs modules that predict results of different agricultural actions. One of the most important factors for sustainable use and fertility of soil is soil flora and fauna. Any change of that community can influence the short or long term soil fertility and soil usability.
    OriginalsprogEngelsk
    TidsskriftMetodoloski zvezki - Advances in Methodology and Statistics
    Vol/bind2
    Nummer1
    Sider (fra-til)147-159
    StatusUdgivet - 2005

    Fingeraftryk

    Dyk ned i forskningsemnerne om 'Using machine learning to predict the impact of agricultural factors on communities of soil microarthropods'. Sammen danner de et unikt fingeraftryk.

    Citationsformater