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
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.
Forfattere
Xiande Li Zhilu Sun Giovanna Ottaviani Aalmo Fangfang Cao Divina Gracia P. Rodriguez Chen Qian Yongxun Zhang Knut ØistadSammendrag
Agricultural extension services are integral to technology adoption where they play a key role in delivering relevant agricultural information and technologies to farmers. In China, agricultural extension services are provided through experimentation, demonstration, training, and consulting. In Norway, agricultural extension is focused on collecting, developing, and coordinating agricultural knowledge to farmers. This chapter focuses on why agricultural extension is needed, how it is developed, and what services agricultural extension provides to its clients. It discusses experiences from China and Norway where agricultural extension has led to or is necessary for boosting agricultural productivity, increasing food security and safety, and improving the well-being of farmers.
Sammendrag
Up-to-date and reliable information on land cover and land use status is important in many aspects of human activities. Knowledge about the reference dataset, its coverage, nomenclature, thematic and geometric accuracy, spatial resolution is crucial for appropriate selection of reference samples used in the classification process. In this study, we examined the impact of the selection and pre-processing of reference samples for the classification accuracy. The classification based on Random Forest algorithm was performed using firstly the automatically selected reference samples derived directly from the national databases, and secondly using the pre-processed and verified reference samples. The verification procedures involved the iterative analysis of histogram of spectral features derived from the Sentinel-2 data for individual land cover classes. The verification of the reference samples improved the accuracy of delineation of all land cover classes. The highest improvement was achieved for the woodland broadleaved and non- and sparce vegetation classes, with the overall accuracy increasing from 51% to 73%, and from 33% to 74%, respectively. The second objective of this study was to derive the best possible land cover classification over the mountain area in Norway, therefore we examined whether the use of the Digital Elevation Model (DEM) can improve the classification results. Classifications were carried out based on Sentinel-2 data and a combination of Sentinel-2 and DEM. Using the DEM the accuracy for nine out of ten land cover classes was improved. The highest improvement was achieved for classes located at higher altitudes: low vegetation and non- and sparse vegetation.
Forfattere
Geir Orderud Petr Porcal Bjørnar Eikebrokk Jiří Sláma Rolf David Vogt Josef Hejzlar Ståle HaalandSammendrag
Several actors have an impact on the quality of drinking water, but ultimately drinking water treatment plants (DWTPs) play a decisive role in ensuring that water quality complies with public regulations. Several developing technologies are combined in water treatment processes. In this paper, we are analysing the technological development of DWTPs in the South Bohemian region of the Czech Republic. The empirical basis is five DWTPs of varying size, and data are gathered through semi-structured interviews with relevant staff inside and outside of the five DWTPs. This study identifies the interplay of factors driving technological development: public regulations, the economic capacity of local DWTP owners together with subsidies from the European Union and national authorities, political priorities by local authorities, and the knowledge network. The paper addressess learning–knowledge–change processes of DWTPs, thereby contributing to our understanding of developing competence in producing drinking water. Generally, large DWTPs are front-runners in introducing new technologies while the smaller ones are lagging. Still, private companies operating small plants on behalf of municipal owners ensure that those DWTPs are part of a wider knowledge network, aiding to introduce a necessary and cost-effective upgrade to treatment steps.
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Forfattere
Susanne ZazzeraSammendrag
MAMN-BIO MAMN-HAVSJ
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Forfattere
Liang Wang Alba Dieguez-Alonso Maria Nicte Polanco Olsen Julie Cathrine Guldahl Øyvind Skreiberg Alice Budai Daniel RasseSammendrag
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