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.
2023
Forfattere
Trygve S. AamlidSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Håvard SteinshamnSammendrag
Det er ikke registrert sammendrag
Forfattere
Håvard SteinshamnSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Tomáš Peterka Petra Hájková Martin Jiroušek Dirk Hinterlang Milan Chytrý Liene Aunina Judit Deme Melinda Lyons Hallie Seiler Harald Zechmeister Iva Apostolova Carl Beierkuhnlein Melanie Bischof Claudia Biţă-Nicolae Lisa Brancaleoni Renata Ćušterevska Jürgen Dengler Yakiv Didukh Daniel Dítě Lyubov Felbaba-Klushyna Emmanuel Garbolino Renato Gerdol Svitlana Iemelianova Florian Jansen Riikka Juutinen Jasmina Kamberović Jutta Kapfer Barbora Klímová Ilona Knollová Tiina H.M. Kolari Predrag Lazarević Ringa Luostarinen Eva Mikulášková Đorđije Milanović Luca Miserere Jesper Erenskjold Moeslund José A. Molina Aaron Pérez-Haase Alessandro Petraglia Marta Puglisi Eszter Ruprecht Eva Šmerdová Daniel Spitale Marcello Tomaselli Kiril Vassilev Michal HájekSammendrag
Det er ikke registrert sammendrag
Forfattere
Laura Elina JaakolaSammendrag
Phenolic compounds constitute one of the most important groups of the bioactive molecules in food plants. These compounds have received attention for their beneficial properties for human health and they also are involved in diverse important roles in plants, including signaling and defense against biotic and abiotic stress factors. Vaccinium berries are one of the richest sources of phenolic compounds of which flavonoid classes of anthocyanins, proanthocyanidins, flavonols in addition to hydroxycinnamic acids are the main phenolics in these species. Besides in berries, phenolic compounds are also present in other parts of the plant. Biosynthesis of flavonoids via the phenylpropanoid pathway is well understood and the key enzymes leading to different intermediates or different flavonoid classes have been characterized in many species including wild and cultivated Vaccinium species. At the molecular level, the biosynthesis is regulated via co-ordinated transcriptional control of the enzymes in the pathway by the interaction with transcription factors of the MYB-bHLH-WD40 (MBW) complex. Upstream regulators of the pathway have also been identified. The biosynthesis is controlled both at the level as well as by the surrounding environmental factors. Plant hormones are the key players in the development and the ripening process of the fruits. Especially abscisic acid (ABA) and methyl jasmonate (MeJA) have been shown to have a key role in the flavonoid metabolism of Vaccinium species. Accumulation of transcriptome, genome and metabolome data are currently increasing our understanding on the complicated regulation networks controlling the metabolism of the phenolic compounds in the Vaccinium species. This offers new tools for selection of the species and cultivars with preferred characteristics, for instance berries with higher health benefit potential or plants with better stress resistance.
Forfattere
Franziska Mohr Vasco Diogo Julian Helfenstein Niels Debonne Thymios Dimopoulos Wenche Dramstad Maria García-Martín Józef Hernik Felix Herzog Thanasis Kizos Angela Lausch Livia Lehmann Christian Levers Robert Pazur Virginia Ruiz-Aragón Rebecca Swart Claudine Thenail Hege Ulfeng Peter H. Verburg Tim Williams Anita Zarina Matthias BürgiSammendrag
Farming in Europe has been the scene of several important socio-economic and environmental developments and crises throughout the last century. Therefore, an understanding of the historical driving forces of farm change helps identifying potentials for navigating future pathways of agricultural development. However, long-term driving forces have so far been studied, e.g. in anecdotal local case studies or in systematic literature reviews, which often lack context dependency. In this study, we bridged local and continental scales by conducting 123 oral history interviews (OHIs) with elderly farmers across 13 study sites in 10 European countries. We applied a driving forces framework to systematically analyse the OHIs. We find that the most prevalent driving forces were the introduction of new technologies, developments in agricultural markets that pushed farmers for farm size enlargement and technological optimisation, agricultural policies, but also cultural aspects such as cooperation and intergenerational arrangements. However, we find considerable heterogeneity in the specific influence of individual driving forces across the study sites, implying that generic assumptions about the dynamics and impacts of European agricultural change drivers hold limited explanatory power on the local scale. Our results suggest that site-specific factors and their historical development will need to be considered when addressing the future of agriculture in Europe in a scientific or policy context.
Forfattere
Adrian Straker Stefano Puliti Johannes Breidenbach Christopher Kleinn Grant Pearse Rasmus Astrup Paul MagdonSammendrag
Fine-grained information on the level of individual trees constitute key components for forest observation enabling forest management practices tackling the effects of climate change and the loss of biodiversity in forest ecosystems. Such information on individual tree crowns (ITC's) can be derived from the application of ITC segmentation approaches, which utilize remotely sensed data. However, many ITC segmentation approaches require prior knowledge about forest characteristics, which is difficult to obtain for parameterization. This can be avoided by the adoption of data-driven, automated workflows based on convolutional neural networks (CNN). To contribute to the advancements of efficient ITC segmentation approaches, we present a novel ITC segmentation approach based on the YOLOv5 CNN. We analyzed the performance of this approach on a comprehensive international unmanned aerial laser scanning (UAV-LS) dataset (ForInstance), which covers a wide range of forest types. The ForInstance dataset consists of 4192 individually annotated trees in high-density point clouds with point densities ranging from 498 to 9529 points m-2 collected across 80 sites. The original dataset was split into 70% for training and validation and 30% for model performance assessment (test data). For the best performing model, we observed a F1-score of 0.74 for ITC segmentation and a tree detection rate (DET %) of 64% in the test data. This model outperformed an ITC segmentation approach, which requires prior knowledge about forest characteristics, by 41% and 33% for F1-score and DET %, respectively. Furthermore, we tested the effects of reduced point densities (498, 50 and 10 points per m-2) on ITC segmentation performance. The YOLO model exhibited promising F1-scores of 0.69 and 0.62 even at point densities of 50 and 10 points m-2, respectively, which were between 27% and 34% better than the ITC approach that requires prior knowledge. Furthermore, the areas of ITC segments resulting from the application of the best performing YOLO model were close to the reference areas (RMSE = 3.19 m-2), suggesting that the YOLO-derived ITC segments can be used to derive information on ITC level.
Forfattere
Binbin Xiang Torben Peters Theodora Kontogianni Frawa Vetterli Stefano Puliti Rasmus Astrup Konrad SchindlerSammendrag
Panoptic segmentation is the combination of semantic and instance segmentation: assign the points in a 3D point cloud to semantic categories and partition them into distinct object instances. It has many obvious applications for outdoor scene understanding, from city mapping to forest management. Existing methods struggle to segment nearby instances of the same semantic category, like adjacent pieces of street furniture or neighbouring trees, which limits their usability for inventory- or management-type applications that rely on object instances. This study explores the steps of the panoptic segmentation pipeline concerned with clustering points into object instances, with the goal to alleviate that bottleneck. We find that a carefully designed clustering strategy, which leverages multiple types of learned point embeddings, significantly improves instance segmentation. Experiments on the NPM3D urban mobile mapping dataset and the FOR-instance forest dataset demonstrate the effectiveness and versatility of the proposed strategy.