Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2016
Abstract
Individual tree mortality models based on logistic regression exist for different tree species and countries around the world. We examine two mortality models developed in Norway and two models from Austria for Norway spruce (Picea abies), Scots pine (Pinus sylvestris) and birch (Betula pubescens and Betula pendula) trees. We apply all models with their original coefficients on the Norwegian National Forest Inventory (NNFI) data. The dataset comprises 36,217 spruce, 17,483 pine and 24,418 birch trees. We show the differences in predictions that arise from newly paramete-rized predictor variables and the effect of the original calibration data from different geographic regions. Next we recalibrate the mortality functions with the NNFI data to show the improvements in the predictions and illustrate the impact of the different predictor variables. We apply statistical methods to assess which of the original and recalibrated models best mimic the observed mortality rates of the three species. Finally we provide the new coefficient set for the model functions for spruce, pine and birch in Norway.
Abstract
Here, we present the 3,795,952 bp complete genome sequence of the biofilm-forming Curtobacterium sp. strain BH-2-1-1, isolated from conventionally grown lettuce (Lactuca sativa) from a field in Vestfold, Norway. The nucleotide sequence of this genome was deposited into NCBI GenBank under the accession CP017580.
Authors
Daniel Muluwork Atsbeha Kyrre Rickertsen Dadi KristoferssonAbstract
No abstract has been registered
Authors
Dominika Średnicka-Tober Marcin Barański Chris Seal Roy Sanderson Charles Benbrook Håvard Steinshamn Joanna Gromadzka-Ostrowska Ewa Rembiałkowska Krystyna Skwarło-Sońta Mick Eyre Giulio Cozzi Mette Krogh Larsen Teresa Jordon Urs Niggli Tomasz Sakowski Philip C. Calder Graham C. Burdge Smaragda Sotiraki Alexandros Stefanakis Halil Yolcu Sokratis Stergiadis Eleni Chatzidimitriou Gillian Butler Gavin Stewart Carlo LeifertAbstract
Demand for organic meat is partially driven by consumer perceptions that organic foods are more nutritious than non-organic foods. However, there have been no systematic reviews comparing specifically the nutrient content of organic and conventionally produced meat. In this study, we report results of a meta-analysis based on sixty-seven published studies comparing the composition of organic and non-organic meat products. For many nutritionally relevant compounds (e.g. minerals, antioxidants and most individual fatty acids (FA)), the evidence base was too weak for meaningful meta-analyses. However, significant differences in FA profiles were detected when data from all livestock species were pooled. Concentrations of SFA and MUFA were similar or slightly lower, respectively, in organic compared with conventional meat. Larger differences were detected for total PUFA and n-3 PUFA, which were an estimated 23 (95 % CI 11, 35) % and 47 (95 % CI 10, 84) % higher in organic meat, respectively. However, for these and many other composition parameters, for which meta-analyses found significant differences, heterogeneity was high, and this could be explained by differences between animal species/meat types. Evidence from controlled experimental studies indicates that the high grazing/forage-based diets prescribed under organic farming standards may be the main reason for differences in FA profiles. Further studies are required to enable meta-analyses for a wider range of parameters (e.g. antioxidant, vitamin and mineral concentrations) and to improve both precision and consistency of results for FA profiles for all species. Potential impacts of composition differences on human health are discussed.
Abstract
This contribution demonstrates an example of experimental automatic image analysis to detect spores prepared on microscope slides derived from trapping. The application is to monitor aerial spore counts of the entomopathogenic fungus Pandora neoaphidis which may serve as a biological control agent for aphids. Automatic detection of such spores can therefore play a role in plant protection. The present approach for such detection is a modification of traditional manual microscopy of prepared slides, where autonomous image recording precedes computerised image analysis. The purpose of the present image analysis is to support human visual inspection of imagery data – not to replace it. The workflow has three components: • Preparation of slides for microscopy. • Image recording. • Computerised image processing where the initial part is, as usual, segmentation depending on the actual data product. Then comes identification of blobs, calculation of principal axes of blobs, symmetry operations and projection on a three parameter egg shape space.
Abstract
No abstract has been registered
Authors
Paal KrokeneAbstract
No abstract has been registered
Authors
K. Syrengelas K. Lewis Carola Grebitus Rudolfo M. Jr. NaygaAbstract
No abstract has been registered
Authors
Atle Mysterud William Ryan Easterday Vetle Malmer Stigum Anders Aas Erling Meisingset Hildegunn ViljugreinAbstract
Global environmental changes are causing Lyme disease to emerge in Europe. The life cycle of Ixodes ricinus, the tick vector of Lyme disease, involves an ontogenetic niche shift, from the larval and nymphal stages utilizing a wide range of hosts, picking up the pathogens causing Lyme disease from small vertebrates, to the adult stage depending on larger (non-transmission) hosts, typically deer. Because of this complexity the role of different host species for emergence of Lyme disease remains controversial. Here, by analysing long-term data on incidence in humans over a broad geographical scale in Norway, we show that both high spatial and temporal deer population density increase Lyme disease incidence. However, the trajectories of deer population sizes play an overall limited role for the recent emergence of the disease. Our study suggests that managing deer populations will have some effect on disease incidence, but that Lyme disease may nevertheless increase as multiple drivers are involved.
Abstract
No abstract has been registered