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.
2025
Forfattere
Eystein Skjerve Erik Georg Granquist Tone Kristin Bjordal Johansen Ingrid Olsen Truls Nesbakken Amin Sayyari Kristin Opdal Seljetun Morten Tryland Åsa Maria Olofsdotter Espmark Grete H. M. Jørgensen Janicke Nordgreen Ingrid Olesen Sonal Jayesh Patel Sokratis Ptochos Marco A. Vindas Tor Atle MoSammendrag
VKM has assessed the risk of introduction and spread of bovine tuberculosis in Norway and cannot rule out that the disease still exists in Norway. There is a low risk of the disease being reintroduced with imported cattle, but the import of llamas and alpacas poses a greater risk. If the disease were to establish in Norway, there is a high risk of spread both among domestic animals and to wildlife. These are the main conclusions The Norwegian Scientific Committee for Food and Environment (VKM) has made in a risk assessment commissioned by the Norwegian Food Safety Authority. Background Following the outbreak of bovine tuberculosis in 2022, VKM was asked to investigate the risk of introduction as well as the risk of spread and establishment of the disease in Norway. The disease primarily affects cattle, but other animals and humans can also be affected. Bovine tuberculosis is a chronic disease that is difficult to diagnose. Therefore, it may take months or years before infected animals are detected. This makes it challenging to eradicate the disease. Conclusions With today's very limited import, VKM concludes it is unlikely that bovine tuberculosis will be introduced to Norway with cattle. Since neighboring countries Sweden and Finland are free from the disease, migration of wildlife will not pose a risk of introduction. However, as the source of the 2022 outbreak has not been identified, it cannot be determined if the disease is still present in Norway. “Alpacas and llamas pose a greater risk. These species are particularly susceptible to the disease, and animals have been imported to Norway, also from countries where the bacterium is common in the cattle population. It is therefore likely that the bacterium could be introduced to Norway with these species if imports continue”, says Eystein Skjerve, Scientific leader of the project team. There is significant trade and transportation of live animals (cattle, alpacas, and llamas) within Norway. If bovine tuberculosis were to establish here, such movements would pose a significant risk of spreading the bacterium. Furthermore, manure from infected herds could pose a risk of spreading to livestock and wild animals. Additionally, contact between livestock and wild animals, such as badgers, wild boars, and various deer species, could lead to the spread of the disease to the wild population. If bovine tuberculosis is established in Norway, a control and eradication strategy would require considerable time and resources. If the disease is introduced to-, and established in wild animal populations, experience from other countries indicates that it will be very challenging to eradicate the disease. “The risk of transmission of bovine tuberculosis to humans is generally low. Veterinarians, farmers, and slaughterhouse workers have an increased risk of infection. If the disease is established in Norway, the greatest risk of transmission to humans is through the consumption of both unpasteurised milk and dairy products”, Skjerve says. Risk-Reducing Measures VKM was also asked to identify several measures that could reduce the risk of introduction and establishment of bovine tuberculosis in Norway: Avoid importing animals from countries and regions where bovine tuberculosis is present in livestock. Avoid importing roughage to Norway from countries and regions with bovine tuberculosis. Increase testing requirements for the trade and movement of alpacas and llamas inside Norway. In the event of an outbreak of bovine tuberculosis, reduce contact between livestock and wild animals and routinely test wild animals (badgers, wild boars, and deer species). (...)
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Forfattere
Håvard SteinshamnSammendrag
Svak samanheng mellom restriktiv gjæring og uRP=utnyttbart protein (unntatt ved låg TS). uRP var positivt korrelert med fordøyelegheit av organisk stoff (OMD) og RP-innhaldet. Svak samsvar mellom uRP og AAT20 (NorFor) men god samsvar mellom uRP og omsetteleg protein=MP (Luke, finske fôrevalueringssystemet)
Forfattere
Berit Marie Blomstrand Stig Milan Thamsborg Håvard Steinshamn Heidi L Enemark Inga Marie Aasen Karl-Christian Mahnert Kristin Sørheim Francesca Sheperd Jos Houdijk Spiridoula AthanasiadouSammendrag
Plant secondary metabolites (PSMs) may improve gastrointestinal health by exerting immunomodulatory, anti-inflammatory and/or antiparasitic effects. Bark extracts from coniferous tree species have previously been shown to reduce the burden of a range of parasite species in the gastrointestinal tract, with condensed tannins as the potential active compounds. In the present study, the impact of an acetone extract of pine bark (Pinus sylvestris) on the resistance, performance and tolerance of genetically diverse mice (Mus musculus) was assessed. Mice able to clear an infection quickly (fast responders, BALB/c) or slowly (slow responders, C57BL/6) were infected orally with 200 infective third-stage larvae (L3) of the parasitic nematode Heligmosomoides bakeri or remained uninfected (dosed with water only). Each infection group of mice was gavaged for 3 consecutive days from day 19 post-infection with either bark extract or dimethyl sulphoxide (5%) as vehicle control. Oral administration of pine bark extract did not have an impact on any of the measured parasitological parameter. It did, however, have a positive impact on the performance of infected, slow-responder mice, through an increase in body weight (BW) and carcase weight and reduced feed intake by BW ratio. Importantly, bark extract administration had a negative impact on the fast responders, by reducing their ability to mediate the impact of parasitism through reducing their performance and tolerance. The results indicate that the impact of PSMs on parasitized hosts is affected by host's genetic susceptibility, with susceptible hosts benefiting more from bark extract administration compared to resistant ones.
Forfattere
Håvard SteinshamnSammendrag
Tidleg’ vårgjødsling gav størst avling og minst grovfôrkostand. ‘Normal’ tidspunkt for vårgjødsling og ‘Tidleg’ førsteslått gav minst avling og størst grovfôrkostand, men best grovfôrkvalitet. ‘Normal’ tidspunkt vårgjødsling og ‘Tidleg’ førsteslått gav minst kraftfôrbehov og minst totale fôrkostnader, men forskjellen til dei andre kombinasjonane var marginal
Sammendrag
I økologisk landbruk er det et mål at gårder med husdyr skal være mest mulig selvforsynt med fôr. Minimumskravet til egenprodusert fôr har over tid blitt høyere. Rapporten presenterer ni økologiske melkeproduksjonsbruk med produksjonsdata og gårdbrukernes tanker om og prioriteringer med hensyn til selvforsyning med fôr. Vi har beregnet ulike mål på gårdenes selvforsyningsgrad og diskuterer hvordan ulike strategier på gårdene virker inn på disse resultatene. De ni økologiske melkebrukene ble valgt ut for å representere ulike klimatiske forhold og tilnærminger til selvforsyning. Data ble samlet inn i 2018 gjennom intervjuer med gårdbrukerne. Resultatene viser at selvforsyning med fôr var et viktig mål for de økologiske melkeprodusentene, først og fremst styrt av egne verdier og mål for økologisk landbruk. Studien viser at ulike strategier kan brukes for å oppnå høy selvforsyningsgrad, avhengig av gårdens beliggenhet, arealgrunnlag, melkekvote og økonomiske situasjon. Bøndenes strategier for å øke eller beholde høy selvforsyningsgrad inneholdt ulike agronomiske tiltak: øke grovfôrkvaliteten gjennom forbedret gjødselhåndtering, drenering og oftere fornyelse av enga. Noen gårder kombinerte høy ytelse med egen produksjon av korn, proteinvekster og oljevekster, mens andre økte selvforsyningsgraden ved å redusere kraftfôrnivået. Alle gårdene i denne studien hadde en høy selvforsyningsgrad med fôr. I 2017 hadde alle over 70 % fôr fra gården eller regionen, medberegnet kraftfôr, som var kravet til regelverket som trådte i kraft i 2024. Selvforsyningsgraden til gårdene varierte mellom 61 % og 100 % på tørrstoffbasis når kun fôr produsert på gården ble inkludert, og mellom 78 % og 100 % når også norskprodusert fôr ble inkludert.
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Forfattere
Kristian Hansen Håvard Steinshamn Sissel Hansen Matthias Koesling Tommy Dalgaard Bjørn Gunnar HansenSammendrag
To evaluate the environmental impact across multiple dairy farms cost-effectively, the methodological frame- work for environmental assessments may be redefined. This article aims to assess the ability of various statistical tools to predict impact assessment made from a Life Cyle Assessment (LCA). The different models predicted estimates of Greenhouse Gas (GHG) emissions, Energy (E) and Nitrogen (N) intensity. The functional unit in the study was defined as 2.78 MJMM human-edible energy from milk and meat. This amount is equivalent to the edible energy in one kg of energy-corrected milk but includes energy from milk and meat. The GHG emissions (GWP100) were calculated as kg CO2-eq per number of FU delivered, E intensity as fossil and renewable energy used divided by number of FU delivered, and N intensity as kg N imported and produced divided by kg N delivered in milk or meat (kg N/kg N). These predictions were based on 24 independent variables describing farm characteristics, management, use of external inputs, and dairy herd characteristics. All models were able to moderately estimate the results from the LCA calculations. However, their precision was low. Artificial Neural Network (ANN) was best for predicting GHG emissions on the test dataset, (RMSE = 0.50, R2 = 0.86), followed by Multiple Linear Regression (MLR) (RMSE = 0.68, R2 = 0.74). For E intensity, the Supported Vector Machine (SVM) model was performing best, (RMSE = 0.68, R2 = 0.73), followed by ANN (RMSE = 0.55, R2 = 0.71,) and Gradient Boosting Machine (GBM) (RMSE = 0.55, R2 = 0.71). For N intensity predictions the Multiple Linear Regression (MLR) (RMSE = 0.36, R2 = 0.89) and Lasso regression (RMSE = 0.36, R2 = 0.88), followed by the ANN (RMSE = 0.41, R2 = 0.86,). In this study, machine learning provided some benefits in prediction of GHG emission, over simpler models like Multiple Linear Regressions with backward selection. This benefit was limited for N and E intensity. The precision of predictions improved most when including the variables “fertiliser import nitrogen” (kg N/ha) and “proportion of milking cows” (number of dairy cows/number of all cattle) for predicting GHG emission across the different models. The inclusion of “fertiliser import nitrogen” was also important across the different models and prediction of E and N intensity.
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