Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2023
Forfattere
Karin Juul HesselsøeSammendrag
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Forfattere
Trygve S. AamlidSammendrag
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Sammendrag
Soil management is important for sustainable agriculture, playing a vital role in food production and maintaining ecological functions in the agroecosystem. Effective soil management depends on highly accurate soil property estimation. Machine learning (ML) is an effective tool for data mining, selection of key soil properties, modeling the non-linear relationship between different soil properties. Through coupling with spectral imaging, ML algorithms have been extensively used to estimate physical, chemical, and biological properties quickly and accurately for more effective soil management. Most of the soil properties are estimated by either near infrared (NIR), Vis-NIR, or mid-infrared (MIR) in combination with different ML algorithms. Spectroscopy is widely used in estimation of chemical properties of soil samples. Spectral imaging from both UAV and satellite platforms should be taken to improve the spatial resolution of different soil properties. Spectral image super-resolution should be taken to generate spectral images in high spatial, spectral, and temporal resolutions; more advanced algorithms, especially deep learning (DL) should be taken for soil properties’ estimation based on the generated ‘super’ images. Using hyperspectral modeling, soil water content, soil organic matter, total N, total K, total P, clay and sand were found to be successfully predicted. Generally, MIR produced better predictions than Vis-NIR, but Vis-NIR outperformed MIR for a number of properties. An advantage of Vis-NIR is instrument portability although a new range of MIR portable devices is becoming available. In-field predictions for water, total organic C, extractable phosphorus, and total N appear similar to laboratory methods, but there are issues regarding, for example, sample heterogeneity, moisture content, and surface roughness. More precise and detailed soil property estimation will facilitate future soil management.
Sammendrag
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Foredrag – Artsrike kulturavhengige økosystemer og matproduksjon for framtida
Ellen Johanne Svalheim
Forfattere
Ellen Johanne SvalheimSammendrag
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Sammendrag
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Sammendrag
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Forfattere
Jorunn BørveSammendrag
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Forfattere
Fride Høistad ScheiSammendrag
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Forfattere
Cecilie Marie Mejdell Knut Egil Bøe Grete H. Meisfjord Jørgensen Turid BuvikSammendrag
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