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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.

2017

Sammendrag

Forbruket av økologisk mat har økt jevnt i Norge fra 2011 til 2016, mens det økologiske arealet har blitt redusert i samme periode. NIBIO som er en viktig leverandør for kunnskap om økologisk landbruk fikk i Statsbudsjettet for 2016 tildelt kunnskapsutviklingsmidler fra Landbruks- og matdepartementet som var øremerka til å "videreutvikle forskningsbasert kunnskap om økologisk landbruk". Arbeidet med å kartlegge status, flaskehalser og kunnskapsbehovet i de ulike produksjonene er basert på en gjennomgang av relevante prosjekter, rapporter og intervjuer med fagpersoner. De foreslåtte temaene for FoU-aktiviteter må anses som veiledende, og er ment som inspirasjon ved utvikling av nye prosjekter innen økologisk landbruk......

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Sammendrag

The effects of a commercial seaweed (SW) product and extracts collected from wild SWs in the Northern Norway on cultivable commensal intestinal bacterial groups isolated from Norwegian White sheep ewes were studied in vivo and in vitro. Bacterial counts from faeces from the ewes fed with supplement which contained SW meal throughout the entire indoor winter period had significantly lower lactic acid bacteria (LAB) counts (P ≈ .05). The screening of extracts from red and brown SWs showed that a number of the organic extracts had an inhibitory effect on the growth of the two Enterococcus sp. isolates. The results indicate that Ascophyllum nodosum supplementation reduces LAB counts in the ewes and the lambs, and that extracts from this SW have an inhibitory effect on the growth of Enterococcus sp. isolates.

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Sammendrag

Based on soil temperature, snow depth and the grown cultivar's maximum attainable level of frost tolerance (LT50c), the FROSTOL model simulates development of frost tolerance (LT50) and winter damage, thereby enabling risk calculations for winter wheat survival. To explore the accuracy of this model, four winter wheat cultivars were sown in a field experiment in Uppsala, Sweden in 2013 and 2014. The LT50 was determined by tests of frost tolerance in November, and the cultivars’ LT50c was estimated. Further, recorded winter survival from 20 winter wheat field variety trials in Sweden and Norway was collected from two winter seasons with substantial winter damages. FROSTOL simulations were run for selected cultivars at each location. According to percentage of winter damage, the cultivar survival was classified as “survived,” “intermediate” or “killed.” Mean correspondence between recorded and simulated class of winter survival was 75% and 37% for the locations in Sweden and Norway, respectively. Stress factors that were not accounted for in FROSTOL might explain the poorer accuracy at the Norwegian locations. The accuracy was poorest for cultivars with intermediate LT50c levels. When low temperature was the main cause of damage, as at the Swedish locations, the model accuracy was satisfying.

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Sammendrag

Proper parameterisation and quantification of model uncertainty are two essential tasks in improvement and assessment of model performance. Bayesian calibration is a method that combines both tasks by quantifying probability distributions for model parameters and outputs. However, the method is rarely applied to complex models because of its high computational demand when used with high-dimensional parameter spaces. We therefore combined Bayesian calibration with sensitivity analysis, using the screening method by Morris (1991), in order to reduce model complexity by fixing parameters to which model output was only weakly sensitive to a nominal value. Further, the robustness of the model with respect to reduction in the number of free parameters were examined according to model discrepancy and output uncertainty. The process-based grassland model BASGRA was examined in the present study on two sites in Norway and in Germany, for two grass species (Phleum pratense and Arrhenatherum elatius). According to this study, a reduction of free model parameters from 66 to 45 was possible. The sensitivity analysis showed that the parameters to be fixed were consistent across sites (which differed in climate and soil conditions), while model calibration had to be performed separately for each combination of site and species. The output uncertainty decreased slightly, but still covered the field observations of aboveground biomass. Considering the training data, the mean square error for both the 66 and the 45 parameter model was dominated by errors in timing (phase shift), whereas no general pattern was found in errors when using the validation data. Stronger model reduction should be avoided, as the error term increased and output uncertainty was underestimated.