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.
2026
Sammendrag
Et nytt rammeverk for forståelse av H2S-risiko i RAS ble presentert. Modellberegninger viser hvordan endringer i CO2, alkalinitet og pH kan påvirke risikoen for H2S-toksisitet i RAS. Økt CO2 og påfølgende pH-fall kan øke andelen fritt H2S, mens stressrelaterte CO2-topper kan forsterke risikoen ytterligere. Høy alkalinitet reduserer konsentrasjonen av fritt H2S, men kan samtidig skjule opphopning av totalt sulfid. CO2-målinger kun ved karinnløp er ikke nok til å vurdere H2S-risikoen i RAS. Risikovurdering bør derfor omfatte totalsulfidbalanse og forventede pH-variasjoner. Det anbefales å overvåke CO2-topper, vurdere H2S-risiko i ulike deler av anlegget basert på totalt sulfid, og fastsette anleggsspesifikke grenseverdier for totalt sulfid basert på forventet vannkvalitet under maksimal belastning. Særlig bør risikoen vurderes ved høy biomasse og under stress, trenging eller håndtering.
Sammendrag
IMPRESS-prosjektet undersøkte respons på stigende mengder mineralgjødsel-N i eng på to lokaliteter. Tørrstoffavlingen økte tydelig fra lave til moderate N-nivåer, men meravlingen ble liten mot toppen av gjødslingsstigen. Samtidig økte mengden høstet N og differansen mellom tilført mineralgjødsel-N og høstet N. Nitrogendifferansen er en partiell beregning og skal ikke tolkes som målt N-tap. Kløverinnholdet avtok med stigende N-tilførsel. Endringene i fôrkvalitet var ikke like entydige. Innholdet av råprotein og NDF kunne øke, mens FEm-innholdet og fordøyelighet kunne avta. Resultatene samsvarer med andre nyere norske forsøksresultater. De gir ikke grunnlag for å betrakte de høyeste tilførselsmengdene av N som optimale eller for å anbefale en generell økning i gjødslingsnormene. N-gjødslingen bør tilpasses forventet avling, kløverandel, antall slåtter, engalder og lokale vekstforhold.
Forfattere
L. Llonch M. Ruiz-Colmenero Matthias Koesling M. Terré J. Cucurull M. Verdú C. Medinyà J. Riera S. Martí M DevantSammendrag
Palm oil is a commonly used dietary fat source in European dairy beef production, but concerns about deforestation associated with its cultivation have stimulated interest in alternative fat sources with the potential to mitigate enteric methane emissions and reduce the carbon footprint of beef production. Oils richer in polyunsaturated fatty acids have been suggested as promising alternatives due to their potential to modify rumen fermentation. The present study aimed to evaluate the dietary substitution of palm oil with sunflower oil, which is rich in polyunsaturated fatty acids, on animal performance, enteric methane emissions, and environmental footprint. Ninety-four crossbred bulls (399 ± 9.3 kg BW and 271 ± 4.0 days of age) were allocated into six pens and fed concentrate and straw separately, both ad libitum. Treatments were based on the fat source of the concentrates: (1) CTR (n = 46), with 3.50% palm oil on a weight basis as control; and (2) SUN (n = 48), with 3.50% sunflower oil. The study lasted 42 days. Individual feed intake was recorded daily. Bulls were weighed every two weeks. Enteric emissions (CH4, CO2, and O2) were recorded daily with a “sniffer” measurement system installed in each concentrate feeder per pen. Daily CH4 production (L/day) was estimated based on Madsen et al. (2010). Data were analysed using a mixed-effects model. The environmental impact of the two diets was evaluated with the life cycle assessment methodology. No differences in average daily weight gain were observed between dietary oil sources (1.83 vs 1.85 ± 0.141 kg/day, P = 0.87; CTR vs SUN, respectively) and concentrate intake (7.48 vs 7.48 ± 0.420 kg DM/day, P = 1.00; CTR vs SUN). A treatment × period interaction (P < 0.05) with no clear pattern was observed in most of the enteric CH4 emissions data. Nevertheless, in the first 14 days of the study, enteric CH4 emission expressed relative to concentrate intake was lower (P < 0.01) in SUN bulls than in CTR bulls. Carbon footprint was lower in SUN concentrate (0.75 kg CO2 eq/kg concentrate feed) compared with the CTR concentrate (0.89 kg CO2 eq/kg concentrate feed). Thus, the substitution of palm oil with sunflower oil reduces enteric methane emissions expressed relative to concentrate intake during the first days after dietary substitution without detrimental effects on animal performance and reduces the carbon footprint of the dietary concentrate, which is the main contributor to meat’s carbon footprint.
Forfattere
Giovanna Ottaviani AalmoSammendrag
Det er ikke registrert sammendrag
Forfattere
María Bustamante Liria Concetta Maria Messina Simona Manuguerra Andrea Santulli Giovanna Ottaviani AalmoSammendrag
Despite significant progress in understanding the complexity of food systems’ challenges, there remains a lack of clarity around how these systems can undergo transformative change and what is required to enable such shifts. This paper focuses on social innovation as a promising mechanism for addressing structural challenges and reconfiguring food systems toward sustainability, equity, justice, and resilience. Our main contribution is the design of an actionable guidance that helps practitioners and researchers explore and leverage the transformative potential of social innovations. This guidance emerges from a dialogue between a key framework for analyzing social-ecological transformations and recent advancements in Transformative Social Innovation (TSI) theory. By incorporating insights on adaptive, bottom-linked governance and relational dynamics into the SES processual framework, we strengthen its applicability to TSI analysis and make it more adaptable for real-world contexts. We apply this guidance to a case study in Western Sicily’s aquatic food systems, where a long-standing social innovation – rooted in Living Lab methodologies and collaborative governance – demonstrates the potential to challenge dominant values by reconfiguring dominant social relations, empower local actors, and engage with both deep and shallow leverage points, contributing to systemic transformations. By combining cross-field dialogue with empirical application, this paper offers both practical tools for analyzing and designing transformative social innovation processes and practical insights into how social innovations can contribute to more sustainable, resilient, and equitable futures. It directly speaks to practitioners, scholars, and policy makers interested in enabling systemic transformation through socially embedded innovation processes.
Forfattere
A. Terskaia R. Oucheikh Junxiang Peng J. Oliveira D. Parsons J. Morel A.M. Abdi Z. Cai S. Thapa N. Boke-Olen P. Olsson H.G. Smith J. Ekroos L. EklundhSammendrag
Grassland management practices are critical both for maintaining resilient food production and for preserving biodiversity, yet spatially explicit information on them is often limited. Recent advances in freely available, remotely sensed land surface phenology and productivity datasets raise the question of whether phenological metrics provide additional, biologically interpretable information for characterising and mapping grassland management beyond conventional spectral features. In this study, we evaluated the information content and added value of freely available, ready-to-use Sentinel-2–derived High-Resolution Vegetation Phenology and Productivity (HR-VPP) data for distinguishing broad grassland management types (conventional leys, organic leys, and semi-natural grasslands) across multiple spatial scales. We analyzed 1455 grasslands across the intensively farmed Skåne province (southern Sweden) over 2018–2022 at provincial and local scales. We further tested whether phenological variables improve grassland management classification when combined with multi-temporal Sentinel-2 spectral data using state-of-the-art machine learning (ML) methods, and applied a conformal prediction framework to manage classification uncertainty. Relationships between HR-VPP metrics and field-measured biomass were additionally assessed using independent field data from northern Sweden. Field-level analyses showed weak (R2 = 0.28) to moderate (R2 = 0.47) relationships between HR-VPP productivity metrics and measured biomass. HR-VPP metrics captured statistically significant but subtle differences among management types, with strong overlap between categories, particularly at the provincial scale. Differences were more pronounced at local scales. Consequently, HR-VPP variables alone had limited predictive power and ML model accuracy was low (0.53). However, combining HR-VPP with Sentinel-2 spectral time-series data substantially improved classification performance, achieving an accuracy of 0.70. Feature importance analysis indicated that spectral indices dominated classification, with limited direct contribution from phenological parameters. These findings highlight both the potential and current limitations of continental-scale phenology and productivity products for grassland management monitoring and point to the need for improved models and complementary data sources to better capture management practices.
Forfattere
Stefano Zanotto Jon Arne Dieseth Wendy Marie Waalen Paolo Annicchiarico Anne Kjersti UhlenSammendrag
Background Faba bean cultivation in northern Europe is challenged by high variability in yield performance due to strong genotype × environment interaction (GEI). Appropriate GEI modeling and interpretation is essential for both cultivar recommendation and breeding for Nordic conditions. Methods Grain yield data from fifteen spring faba bean cultivars evaluated in eleven Norwegian environments during four growing seasons (2022–2025) were analyzed using the Additive Main Effects and Multiplicative Interaction (AMMI) model. Climatic drivers of GEI were investigated using factorial regression, while genome-wide SNP markers were used to assess the relationship between molecular diversity and adaptive differentiation. Results Environment, genotype, and GEI significantly influenced grain yield. The AMMI model with three GEI principal components (AMMI3) represented the biologically meaningful GEI signal and explained 83.4% of the GEI variation. The predictive accuracy of this model closely approached that of BLUP and GBLUP. Factorial regression showed that maximum and mean September temperatures explained 38.5% of the GEI variation, indicating that late-season thermal conditions are the principal environmental drivers of cultivar adaptation. We identified three top-yielding genotypes (Ketu, Birgit, and Vire) that can be object of site-specific recommendation. Two sub-regions emerged as possibly distinct breeding targets, namely, a major one, and a smaller one featuring cooler late-cycle temperatures and specific adaptation of very early material. A significant Mantel correlation between genomic and adaptive dissimilarity (r = 0.40, P = 0.029) suggested that differences in environmental adaptation have a measurable genetic basis. Conclusions This study identified elite cultivars for recommendation and generated crucial information for future crop breeding and variety testing in Norway. Breeding for wide adaptation across climatically diversified environments is justified by the modest size of the smaller sub-region and its expected decreasing importance due to climate change. The relationship between genomic and adaptive dissimilarity, if confirmed for a larger genotype set, could be exploited for a preliminary screening of regional breeding material and novel plant introductions.
Sammendrag
In this paper, we propose a fishery control scheme that happens to be first best in the context of a Gordon‐Schaefer model with asymmetric information about effort/harvesting costs. It is widely acknowledged that in the absence of regulations, competition between vessels leads to a competitive game wherein the outcome is inefficient. We introduce a management scheme that regulates the fishing industry through an individual convex tax on effort or on catches. The shares of this tax can be traded in a market, thus solving problems related to asymmetric information. This can be achieved since heterogeneous fishing firms are individually stimulated to solve the same optimality problem as a social planner would. We apply this model to the Northwest Mediterranean demersal fishery as a case study.
Forfattere
Frode VeggelandSammendrag
Det er ikke registrert sammendrag
Forfattere
Frode VeggelandSammendrag
Det er ikke registrert sammendrag