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.
2025
Authors
Alexander N. Hristov André Bannink Marco Battelli Alejandro Belanche M. Cecilia Cajarville Sanz Gonzalo Fernandez-Turren Florencia Garcia Arjan Jonker David A. Kenny Vibeke Lind Sarah J. Meale David Meo Zilio Camila Muñoz David Pacheco Nico Peiren Mohammad Ramin Luca Rapetti Angela Schwarm Sokratis Stergiadis Katerina Theodoridou Emilio M. Ungerfeld Sanne van Gastelen David R. Yáñez-Ruiz Sinead M. Waters Peter LundAbstract
There is a need for rigorous and scientifically-based testing standards for existing and new enteric methane mitigation technologies, including antimethanogenic feed additives (AMFA). The current review provides guidelines for conducting and analyzing data from experiments with ruminants intended to test the antimethanogenic and production effects of feed additives. Recommendations include study design and statistical analysis of the data, dietary effects, associative effect of AMFA with other mitigation strategies, appropriate methods for measuring methane emissions, production and physiological responses to AMFA, and their effects on animal health and product quality. Animal experiments should be planned based on clear hypotheses, and experimental designs must be chosen to best answer the scientific questions asked, with pre-experimental power analysis and robust post-experimental statistical analyses being important requisites. Long-term studies for evaluating AMFA are currently lacking and are highly needed. Experimental conditions should be representative of the production system of interest, so results and conclusions are applicable and practical. Methane-mitigating effects of AMFA may be combined with other mitigation strategies to explore additivity and synergism, as well as trade-offs, including relevant manure emissions, and these need to be studied in appropriately designed experiments. Methane emissions can be successfully measured, and efficacy of AMFA determined, using respiration chambers, the sulfur hexafluoride method, and the GreenFeed system. Other techniques, such as hood and face masks, can also be used in short-term studies, ensuring they do not significantly affect feed intake, feeding behavior, and animal production. For the success of an AMFA, it is critically important that representative animal production data are collected, analyzed, and reported. In addition, evaluating the effects of AMFA on nutrient digestibility, animal physiology, animal health and reproduction, product quality, and how AMFA interact with nutrient composition of the diet is necessary and should be conducted at various stages of the evaluation process. The authors emphasize that enteric methane mitigation claims should not be made until the efficacy of AMFA is confirmed in animal studies designed and conducted considering the guidelines provided herein.
Abstract
Urban green structures (UGS) play important roles in enhancing urban ecosystems by providing benefits such as mitigating the urban heat island effect, improving air quality, supporting biodiversity, and aiding in stormwater management. Accurately mapping UGS is important for sustainable urban planning and management. Traditional methods of mapping such as manual mapping, aerial photography interpretation and pixel-based classification have limitations in terms of coverage, accuracy, and efficiency. Object-based image analysis (OBIA) has gained prominence due to its ability to incorporate both spectral and spatial information making it particularly effective for classification of high-resolution satellite data. This paper reviews the application of OBIA on satellite images for UGS mapping, focusing on various data sources, popular segmentation methods, and classification techniques, highlighting their respective advantages and limitations. Key segmentation methodologies discussed include multi-resolution segmentation and watershed segmentation. For classification, the review covers machine learning techniques such as random forests, support vector machines, and convolutional neural networks, among others. Several case studies highlight the successful implementation of OBIA in diverse urban environments by demonstrating improvements in classification accuracy and detail. The review also addresses the challenges associated with OBIA, such as dealing with heterogenous urban landscapes, data sources and with OBIA methods itself. Future directions for UGS mapping include the integration of deep learning algorithms, advancements in satellite data technologies, and the development of standardized classification frameworks. By providing a detailed analysis of the current state-of-the-art in object-based UGS mapping, this review aims to guide future research and practical applications in UGS management.
Authors
Mostafa Hoseini Helle Ross Gobakken Stephan Hoffmann Csongor Horvath Johannes Rahlf Jan Bjerketvedt Stefano Puliti Rasmus AstrupAbstract
RoadSens is a platform designed to expedite the digitalization process of forest roads, a cornerstone of efficient forest operations and management. We incorporate stereo-vision spatial mapping and deep-learning image segmentation to extract, measure, and analyze various geometric features of the roads. The features are precisely georeferenced by fusing post-processing results of an integrated global navigation satellite system (GNSS) module and odometric localization data obtained from the stereo camera. The first version of RoadSens, RSv1, provides measurements of longitudinal slope, horizontal/vertical radius of curvature and various cross-sectional parameters, e.g., visible road width, centerline/midpoint positions, left and right sidefall slopes, and the depth and distance of visible ditches from the road’s edges. The potential of RSv1 is demonstrated and validated through its application to two road segments in southern Norway. The results highlight a promising performance. The trained image segmentation model detects the road surface with the precision and recall values of 96.8 and 81.9 , respectively. The measurements of visible road width indicate sub-decimeter level inter-consistency and 0.38 m median accuracy. The cross-section profiles over the road surface show 0.87 correlation and 9.8 cm root mean squared error (RMSE) against ground truth. The RSv1’s georeferenced road midpoints exhibit an overall accuracy of 21.6 cm in horizontal direction. The GNSS height measurements, which are used to derive longitudinal slope and vertical curvature exhibit an average error of 5.7 cm compared to ground truth. The study also identifies and discusses the limitations and issues of RSv1, which provide useful insights into the challenges in future versions.
Abstract
Optimised contributions of green infrastructure (GI) to urban ecosystem services are strongly related to its multifunctionality. The challenge, however, is that the concept of multifunctionality still needs to be transformed into an operationalised assessment to evaluate current performance, which is instrumental in supporting spatial planning and policy strategies. Using the case of Stavanger City (Norway), the study conducted a spatial assessment of the multifunctionality of the urban green infrastructure. The study used a comprehensive set of 27 function indicators estimated for each of the 156 spatial units classified by their type, age, size, and biophysical characteristics. Correlation patterns among indicators and how the average and effective multifunctionality related to unit characteristics were analysed using correlation and multivariate approaches. The study demonstrated weak correlations between function indicators but revealed some potential trade-offs and function bundles. Notably, bundles related to tree cover (e.g. C sequestration, stormwater retention) had negative relationships with facilitation measures. There was a large overlap in functions between GI types associated with public green spaces and parks. Moreover, the characteristics of green infrastructure units, like size and age, primarily affected multifunctionality through effects on function indicators. Regarding the city-wide multifunctionality, we found some turnover and subsetting of functions among units, supporting multifunctionality at larger spatial scales. However, the average contributions from different GI types were similar. The study highlights the need to understand correlation patterns among function indicators and function bundles as critical to benefit from synergies and avoid unintentional trade-offs when designing and managing urban green areas.
Abstract
No abstract has been registered
Authors
Jian Liu Faruk Djodjic Barbro Ulén Helena Aronsson Marianne Bechmann Lars Bergström Tore Krogstad Katarina KyllmarAbstract
No abstract has been registered
2024
Authors
Maria Åsnes MoanAbstract
Bonitet er definert som overhøyden ved en gitt referansealder og brukes for å beskrive skogens potensial for å produsere tømmer. Bonitering, altså å bestemme boniteten, har utviklet seg fra feltbaserte metoder til metoder som benytter seg av punktskydata. Punktskydata fra flybåren laserskanning og bildematching har blitt brukt til å bonitere med den direkte og høydedifferensielle metoden. Disse metodene bruker overhøydeutviklingen over en kjent periode til å bonitere ved bruk av punktskydata fra minst to tidspunkt, dvs. multitemporale punktskydata. Den direkte metoden boniterer ved bruk av en prediksjonsmodell for bonitet med forklaringsvariabler beregnet fra punktskydata. Den høydedifferensielle metoden finner boniteten der forventet overhøydeutvikling passer best med den predikerte overhøydeutviklingen. Denne avhandlingen tok sikte på å forbedre metodene for bonitering med punktskydata og består av fire studier. Forstyrrelser kan gjøre et område uegnet for bonitering med punktskydata. Tidligere har man definert egnethet som områder uten negativ utvikling i overhøyde eller biomasse, men dette betyr ikke nødvendigvis at overhøydeutviklingen er uforstyrret. Den første studien i denne avhandlingen klassifiserte egnethet med variabler fra multitemporale laserdata. Egnethet var definert basert på feltregistrerte forstyrrelser hos dominerende trær. Resultatene viste at egnethet kunne klassifiseres med multitemporale laserdata, selv om definisjonene av egnethet i den studien var konservative ettersom ett dødt dominerende tre var nok til at prøveflaten ble klassifisert som uegnet. En tidsserie med laserdata kan forbedre nøyaktigheten til boniteringen sammenlignet med å bruke laserdata fra to påfølgende laserskanninger. Dette er fordi overhøydeutviklingen for en lengre periode vil bli representert. Den andre studien i denne avhandlingen brukte laserdata fra tre tidspunkt for å bonitere med den direkte og høydedifferensielle metoden. Prediksjonsfeilene var ikke statistisk signifikant forskjellig når man brukte laserdata fra hele tidsserien sammenlignet med å bruke laserdata fra to påfølgende tidspunkt, dvs. enten første og andre eller andre og tredje tidspunkt. Imidlertid økte andelen av området som var egnet for bonitering når hvilket som helst delsett av påfølgende tidspunkter i tidsserien kunne brukes, noe som ga en økt fleksibilitet til å unngå å perioder der det hadde vært en forstyrrelse. «Value of improved information» kan brukes til å vurdere nytteverdien av forskjellige boniteringsmetoder når beslutningstakeren har ulike mål for skogforvaltningen. Den tredje studien brukte stokastisk programmering for å beregne «value of improved information» ved bruk av den direkte og høydedifferensielle metoden med enten multitemporale laserdata eller laserdata og påfølgende bildematchingsdata. Resultatene viste at «value of improved information» var nærmest null og dermed best for den høydedifferensielle metoden i vårt studieområde. Den høydedifferensielle metoden kan potensielt brukes til å bonitere i ungskog. Den fjerde studien detekterte posisjonen til kvistkranser fra veldig tette punktskydata med en dyplæringsmodell og brukte detekterte kvistkranser til å bonitere med den høydedifferensielle metoden. Dette ga en «root mean square error» mellom 19,85 og 20,87%. En utfordring med bonitering i ungskog er at bonitetskurvene er brattere for lave aldre sammenlignet med høyere aldre, noe som resulterer i at feil i deteksjonen av kvistkranser har større konsekvenser for bestemmelsen av bonitet i ungskog. Denne avhandlingen har tatt for seg noen utfordringer og muligheter for bonitering med punktskydata. Likevel viste den første og fjerde studien at det er behov for mer forskning på hvordan man best kan definere egnethet og bonitere i ungskog.
Abstract
Livestock production systems with ruminants are generally associated with high enteric methane emissions and thus a high carbon footprint, causing these systems to be challenged when it comes to what products to eat and wear in a sustainable future.
Authors
Cornelya Klutsch Juho Vuolteenaho Birk Schulze Runar Kjær David Kniha Ane-Sofie Bednarczyk Hansen Ida Marie Luna Fløystad Tone Roksvåg Aandahl Simo Maduna Tommi Nyman Paul Eric Aspholm Snorre HagenAbstract
An overview of projects working on/with soil at NIBIO Svanhovd
Authors
Veronica Quynh Thi PhanAbstract
Norway spruce (Picea abies (L.) H. Karst.) is a beneficial conifer species in Europe, especially in forestry. The increasing demand of Norway spruce has led to high production of seedlings in growth facilities. Growth conditions in these facilities contribute to fungal outbreaks, and the continuous use of fungicides to combat fungal infections will eventually develop resistance in the fungi. Applying chemical compounds directly to the seeds to prime inducible defences may be a simpler and safer method to protect the seedlings. In this study, seeds were treated with the chemicals methyl jasmonate (MeJA) and chitosan (Chi) to determine if seed priming is possible in Norway spruce. Furthermore, seeds were also treated with JAR, and a combination of JAR and MeJA or Chi, to investigate the hormone signalling pathways involved in MeJA and Chi induced defence responses. To establish the effects of these chemicals, the germination percentage and phenotypes of 4-week-old seedlings were evaluated. Additionally, 4-week-old seedlings were challenged with mechanical wounding and MeJA to determine if the seed treatments had an influence on defence responses. Gene expression levels of seven defence-related genes (CHI4, CHI2, NRPE1, ROS1, JAR1, LAR3, LOX) were quantified at two time points after challenge. In addition, chitinase enzyme activity was measured. The findings of this study indicates that the chemicals MeJA and Chi can possibly penetrate the seed coats of Norway spruce, making seed priming possible. However, this study did not include all defence responses and most genes did not reveal any priming effect, thus it was difficult to determine the signalling pathways involved in defence responses. Overall, the ontogeny of Norway spruce may play a major role in the activation of various defence mechanisms.