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.
2011
Forfattere
Arne Hermansen Leslie A Wanner Ragnhild Nærstad Sonja KlemsdalSammendrag
Det er ikke registrert sammendrag
Sammendrag
The aim of this study was to use energy-dispersive X-ray spectroscopy (EDX) to localize chitosan in the cell wall of chitosan-impregnated Scots pine. It was of interest to investigate the concentration of chitosan in wood to gain further knowledge and understanding of the distribution of chitosan in the wooden matrix. After deacetylation, chitosan was re-acetylated with chloroacetic anhydride to achieve a covalent bonding of chloride to the chitosan polymer. Chloride-labelled chitosan was measured by EDX using a scanning electron microscope and described as chloride intensity. Analysis of free chloride anions was performed by dialysis and inductively coupled plasma atomic emission spectroscopy. There was a significant correlation between the molecular weight of chitosan and the intensity of covalentbonded chloride to the chitosan polymer. High molecular weight chitosan showed a better interaction with the cell wall structure than low molecular chitosan.
Forfattere
Berit Nordskog Trond Rafoss Ragnhild Nærstad Ingerd Skow Hofgaard Halvard Hole Oleif Elen Guro BrodalSammendrag
Forecasting models for prediction of diseases and pests in crop plants are helpful tools in decision support systems for crop management. Correct use of pesticides may result in optimal effect, increased yield and better quality of the crop, while minimizing the environmental strain and costs. In Norway, a range of decision support systems for diseases, pests and weeds are available through the internet service VIPS (www.vips-landbruk.no). The reliability of disease and pest forecasts depends on robust forecasting models and relevant weather data. Although weather data are collected from a network of 80 weather stations located in agricultural production areas in Norway, many farms are remotely located from a weather station. The accuracy of forecasts relies on distance and geographical variation from the farm site to the nearest weather station. Forecasts for pest or diseases can be tailored to fit the local conditions at a farm site by use of weather forecasts and radar measured rainfall. The use of this system will be of particular interest to farms located far from the nearest weather station. Also, locally adapted forecasts for pest or diseases promote a sense of ownership and personal interest in the forecasting systems provided. The Norwegian Meteorological Institute provide weather forecasts on a 4x4 km spatial resolution in rural areas on a 1 hour timescale, while radar measured rainfall has a 1x1 km spatial resolution on a 15 min time scale. These data are currently connected to the existing weather stations to predict warnings ahead of time. The new approach is to adapt these data to individual farm sites. Previous tests have shown that weather prognosis for rainfall is less accurate than weather prognosis for temperature, wind, air humidity and radiation. Estimated rainfall will therefore be based on radar measurements. As part of a pilot project, the use of farm scale forecasts to predict development of plant diseases were tested at 35 farms in the Solør-Odal district in Norway in 2010 and 2011. Preliminary results show that late-blight forecasts produced on a farm scale often differ from forecasts based on data from the nearest weather station, proving the significance of the local approach in farm scale forecasting. Predictions of DON (deoxynivalenol) concentration in oats at harvest based on farm scale weather data, compared to predictions based on weather data from the nearest weather station will also be studied. Future aspects will be to work towards an improved system where farmers throughout Norway can register their farm and automatically have access to a range of pest and disease forecasts based on site specific weather data.
Forfattere
Berit NordskogSammendrag
Det er ikke registrert sammendrag
Forfattere
Morten Nitteberg Bruce TalbotSammendrag
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Forfattere
Tom Johnson Sara Alva-Lizarraga Karen Refsgaard Thanassos Kampas Demetris Psaltopoulos Gemma FrancesSammendrag
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Forfattere
Therese With Berge Steve Goldberg Daniel Løvås Jan Netland Øyvind OverskeidSammendrag
I samarbeid med Adigo AS har Bioforsk Plantehelse påbegynt utvikling av en ugrasrobot som skal kontrollere ugras i radene av kålrot.
Sammendrag
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Forfattere
Arnold ArnoldussenSammendrag
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Forfattere
Jihong Liu ClarkeSammendrag
Det er ikke registrert sammendrag