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.
2023
Authors
M.L. Robinson P.G. Hahn B.D. Inouye N. Underwood S.R. Whitehead K.C. Abbott E.M. Bruna N.I. Cacho L.A. Dyer L. Abdala-Roberts W.J. Allen J.F. Andrade D.F. Angulo D. Anjos D.N. Anstett R. Bagchi S. Bagchi M. Barbosa S. Barrett C.A. Baskett E. Ben-Simchon K.J. Bloodworth J.L. Bronstein Y.M. Buckley K.T. Burghardt C. Bustos-Segura E.S. Calixto R.L. Carvalho B. Castagneyrol M.C. Chiuffo D. Cinoğlu E. Cinto Mejía M.C. Cock R. Cogni O.L. Cope T. Cornelissen D.R. Cortez D.W. Crowder C. Dallstream W. Dáttilo J.K. Davis R.D. Dimarco H.E. Dole I.N. Egbon M. Eisenring A. Ejomah B.D. Elderd Joshua Lynn Anne Muola Vigdis VandvikAbstract
Interactions between plants and herbivores are central in most ecosystems, but their strength is highly variable. The amount of variability within a system is thought to influence most aspects of plant-herbivore biology, from ecological stability to plant defense evolution. Our understanding of what influences variability, however, is limited by sparse data. We collected standardized surveys of herbivory for 503 plant species at 790 sites across 116° of latitude. With these data, we show that within-population variability in herbivory increases with latitude, decreases with plant size, and is phylogenetically structured. Differences in the magnitude of variability are thus central to how plant-herbivore biology varies across macroscale gradients. We argue that increased focus on interaction variability will advance understanding of patterns of life on Earth.
Abstract
No abstract has been registered
Authors
Hang Su Andre van Eerde Espen Rimstad Ralph Bock Norica Branza-Nichita Igor A. Yakovlev Jihong Liu ClarkeAbstract
Plants provide not only food and feed, but also herbal medicines and various raw materials for industry. Moreover, plants can be green factories producing high value bioproducts such as biopharmaceuticals and vaccines. Advantages of plant-based production platforms include easy scale-up, cost effectiveness, and high safety as plants are not hosts for human and animal pathogens. Plant cells perform many post-translational modifications that are present in humans and animals and can be essential for biological activity of produced recombinant proteins. Stimulated by progress in plant transformation technologies, substantial efforts have been made in both the public and the private sectors to develop plant-based vaccine production platforms. Recent promising examples include plant-made vaccines against COVID-19 and Ebola. The COVIFENZ® COVID-19 vaccine produced in Nicotiana benthamiana has been approved in Canada, and several plant-made influenza vaccines have undergone clinical trials. In this review, we discuss the status of vaccine production in plants and the state of the art in downstream processing according to good manufacturing practice (GMP). We discuss different production approaches, including stable transgenic plants and transient expression technologies, and review selected applications in the area of human and veterinary vaccines. We also highlight specific challenges associated with viral vaccine production for different target organisms, including lower vertebrates (e.g., farmed fish), and discuss future perspectives for the field.
Abstract
No abstract has been registered
Abstract
Inthis study, we introduce Point2Tree, a modular and versatile framework that employs a three-tiered methodology, inclusive of semantic segmentation, instance segmentation, and hyperparameter optimization analysis, designed to process laser point clouds in forestry. The semantic segmentation stage is built upon the Pointnet++ architecture and is primarily tasked with categorizing each point in the point cloud into meaningful groups or ’segments’, specifically in this context, differentiating between diverse tree parts, i.e., vegetation, stems, and coarse woody debris. The category for the ground is also provided. Semantic segmentation achieved an F1-score of 0.92, showing a high level of accuracy in classifying forest elements. In the instance segmentation stage, we further refine this process by identifying each tree as a unique entity. This process, which uses a graph-based approach, yielded an F1-score of approximately 0.6, signifying reasonable performance in delineating individual trees. The third stage involves a hyperparameter optimization analysis, conducted through a Bayesian strategy, which led to performance improvement of the overall framework by around four percentage points. Point2Tree was tested on two datasets, one from a managed boreal coniferous forest in Våler, Norway, with 16 plots chosen to cover a range of forest conditions. The modular design of the framework allows it to handle diverse pointcloud densities and types of terrestrial laser scanning data.
Authors
Linn Vassvik Anders Nielsen Erik Trond Aschehoug Bjørn Arild Hatteland Joseph Chipperfield Michael P. D. GarrattAbstract
No abstract has been registered
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No abstract has been registered
Authors
Linn VassvikAbstract
No abstract has been registered
Authors
Linn VassvikAbstract
No abstract has been registered
Authors
Pia Heltoft ThomsenAbstract
No abstract has been registered