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
Margit Oami Kollstrøm Ulrike Böcker Anne Kjersti Uhlen Annbjørg Kristoffersen Jon Arne Dieseth Erik Tengstrand Shiori KogaAbstract
The gluten-viscoelastic properties are essential for breadmaking quality and are affected by both genotypes and environments, such as weather conditions. However, it is still not clear how weather conditions cause variation in gluten quality and at which stage of the grain filling they are critical. The aim of the study was to explore the relationship between weather parameters during grain filling and the viscoelastic properties of gluten. The gluten of spring wheat varieties grown over 17 seasons, resulting in a total of 70 different environments, was analyzed with the Kieffer extensibility rig. The variation in viscoelastic properties of gluten was mainly explained by environment, followed by genotype, while the genotype*environment interaction was small. The results also indicated that the periods around heading and physical maturity were the most critical when weather conditions affected the gluten quality. Our results also revealed that factors other than weather conditions are responsible for the variation in gluten quality.
Authors
Alexander N. Hristov André Bannink M Battelli Alejandro Belanche M.C. Cajarville Sanz G Fernandez-Turren F Garcia Arjan Jonker D.A. Kenny Vibeke Lind S.J. Meale D Meo Zilio Camila Muñoz David Pacheco Nico Peiren Mohammad Ramin L Rapetti Angela Schwarm Sokratis Stergiadis Katerina Theodoridou E.M. Ungerfeld S van Gastelen D.R. Yanez-Ruiz S.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
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Authors
Jian Liu Faruk Djodjic Barbro Ulén Helena Aronsson Marianne Bechmann Lars Bergström Tore Krogstad Katarina KyllmarAbstract
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2024
Authors
Mojtaba Shafiei Csilla Farkas Eva Skarbøvik Nikolai Friberg Moritz Shore Dominika Krzeminska Anne-Grete Buseth Blankenberg Katrin BiegerAbstract
Nature-based solutions (NBS) are an increasingly popular strategy to water resources management, with a growing number of research projects and policy interventions. Development, implementation, and decision on NBS for retention of water, sediments, and nutrients in the landscape often require substantial investment in data acquisition and modeling efforts. SWAT+ provides several new approaches compared to SWAT in terms of i) enhanced catchment configuration with more spatial objects, ii) improved representation of the connectivity between man-made hydrologic systems and the catchment stream network, and iii) new algorithms to implement complex rule-based management actions. These advantages make SWAT+ very suitable for simulating catchment processes in relation to NBS and for developing catchment-based tools for optimizing the type, location, and design of NBS. To further propel the simulation and optimization of NBS at the catchment scale with SWAT+, we propose establishing a community to harmonize and synergize the efforts of SWAT+ users worldwide in the field of NBS implementation and management. The envisioned SWAT+ NBS community would comprise researchers and scientists sharing a common vision, engaged in co-developing frameworks, addressing policy imperatives, co-creating knowledge, and advocating for best practices in applying the SWAT+ model for advanced NBS optimization and management. The objectives of this presentation are 1) to discuss the phases of NBS development and management at catchment scale, 2) to identify the research gaps in using SWAT+ in NBS studies, and 3) to propose a structure and a coordination framework to shape the SWAT+ NBS community.
Abstract
The use of SWAT+ model is increasingly prevalent in the simulation and evaluation of Nature-Based Solutions (NBS) at the catchment scale. Compared to the SWAT model, the SWAT+ model offers several advancements, including enhanced catchment configuration, improved representation of connectivity between man-made hydrologic systems and the catchment stream network, and new algorithms for implementing rule sets for management actions. In this presentation, we outline our methodology and present some preliminary findings from implementing SWAT+ in a South-Eastern Norwegian catchment. The catchment has a relatively large proportion of agricultural land based on Norwegian standards, with several natural lakes. Our modelling results underscore the importance of the spatial configuration phase, particularly in detailed spatial settings and HRU characterization, for simulating catchment-NBS interactions. We found that integrating reanalysis of spatial meteorological data in 1x1 km resolution could significantly improve streamflow simulation. In our case study, by using Met Nordic Reanalysis Dataset from Norwegian Meteorological Institute, the NS efficiency increased from -0.05 to 0.4 prior to any calibrations. Furthermore, we discuss challenges in simulating catchment-NBS interactions with SWAT+, particularly concerning “prospective impact evaluation” in the planning phase of constructed wetlands (design, placement, and optimization).
Abstract
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