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.
2024
Abstract
Aims To develop a methodology to study uptake and redistribution by plants of NH4+ from deep soil, applying it to investigate deep root N uptake by cultivated grassland species. Methods A slow-release 15NH4+ label adsorbed to clinoptilolite was placed into soil (depth 42 cm) well below the densest root zone in well-established monospecific stands of five grass and two clover species. Species showing a variety of deep rooting patterns, N acquisition strategy, forage qualities, and persistence in hemiboreal conditions were chosen. The label was placed in early spring and tracked throughout one or two growing seasons in two repeated experiments. Results After two growing seasons ~ 90% of the label was tracked in the soil and harvested herbage of grasses, less in clovers. Deep N uptake was limited in spring, increased during mid-season, and was strongest in autumn in all species, despite lower herbage yield in autumn. Species differed in ability to recover and maintain 15N in the soil–plant system. In one growing season, Lolium perenne L., Phleum pratense L., Schedonorus pratensis (Huds.) P.Beauv. and Schedonorus arundinaceus (Schreb.) Dumort herbage recovered ~ 65% of the label, Poa pratensis L. 54%, and Trifolium pratense L. and Trifolium repens L. 36–48%. Label transport to topsoil was observed, mainly attributable to plant nutrient redistribution rather than physical diffusion. Conclusions The innovative slow-release 15N label enabled tracing species differences and seasonal changes in uptake of NH4+ from deep soil. Among the tall-growing grasses, growth vigor appeared as important for deep N uptake as expected root depth.
Authors
Kristian Hansen Matthias Koesling Håvard Steinshamn Bjørn Gunnar Hansen Tommy Dalgaard Sissel HansenAbstract
In this study, 200 Norwegian dairy farms were analyzed over three years to compare greenhouse gas emissions, nitrogen (N) intensity, gross margin, and land use occupation between organically and conventionally managed farms. Conventionally managed farm groups were constructed based on propensity matching, selecting the closest counterparts to organically managed farms (n=15). These groups, each containing 15 farms, were differentiated by an increasing number of matching variables. The first group was matched based on geographical location, milk quota, and milking cow units. In the second match, the proportion of milking cows in the total cattle herd was added, and in the third, the ratio of milk delivered to milk produced and concentrate usage per dairy cow were included. The analysis showed that the conventionally managed farms (n=185) had higher greenhouse gas emissions (1.42 vs 0.98 kg CO2 per 2.78 MJ of edible energy from milk and meat, calculated as GWP100-AR4) and higher N intensity (6.9 vs 5.0 kg N input per kg N output) compared to the organic farms (N=15). When comparing emissions per kg of energy-corrected milk (ECM) delivered, conventional farms also emitted more CO2 (1.07 vs 0.8 kg CO2 per kg ECM). Furthermore, conventionally managed farms showed lower gross margins both in terms of NOK per 2.78 MJ edible energy delivered (5.8 vs 6.5 NOK) and per milking cow unit (30 100 vs 34 400 NOK), and they used less land (2.9 vs 3.6 m² per 2.78 MJ edible energy delivered) compared to organic farms. No differences were observed among the three conventionally managed groups in terms of emissions, N intensity, land use occupation, and gross margin.
Abstract
Ruminants, including sheep, contribute significantly to methane emissions, thus resulting in high emissions per kg of product. However, they can utilise plant material unsuitable for human consumption, thereby transforming it into valuable, protein-rich food. Grazing also preserves cultural landscapes and can contribute to carbon sequestration. Under¬standing the balance between these factors within the climate change context is crucial. This study inves-tigates the environmental impact of meat, milk, and wool production from sheep farming in Norway and Slovenia.
Abstract
Ruminants, including sheep, significantly contribute to methane emissions, which results in high emissions per kg of product. Conversely, ruminants can utilise plant material unsuitable for human consumption, effectively converting it into valuable, protein-rich food. Grazing also maintains cultural landscapes and contributes to carbon sequestration. Therefore, under- standing the balance between these factors in the context of climate change is essential. This study analyses the environmental impact of meat, milk, and wool production from sheep farming in Norway and Slovenia.
Abstract
No abstract has been registered
Authors
Ritter Atoundem Guimapi Berit Nordskog Anne-Grete Roer Hjelkrem Ingeborg Klingen Ghislain Tchoromi Tepa-Yotto Manuele Tamò Karl ThunesAbstract
The fall armyworm, Spodoptera frugiperda, situation in Africa remains a priority threat despite significant efforts made since the first outbreaks in 2016 to control the pest and thereby reduce yield losses. Field surveys in Benin and Mali reported that approximately one-week post-emergence of maize plants, the presence of fall armyworm (egg/neonates) could be observed in the field. Scouting for fall armyworm eggs and neonates is, however, difficult and time consuming. In this study, we therefore hypothesized that the optimum timeframe for the fall armyworm female arriving to lay eggs in sown maize fields could be predicted. We did this by back-calculating from interval censored data of egg and neonates collected in emerging maize seedlings at young leaf developmental stage. Early time of ovipositing fall armyworm after sowing was recorded in field experiments. By using temperature-based models to predict phenological development for maize and fall armyworm, combined with analytical approaches for time-to-event data with censored status, we estimated that about 210 accumulated Degree Days (DD) is needed for early detection of neonate larvae in the field. This work is meant to provide new insights on timely pest detection and to guide for precise timing of control measures.
Abstract
No abstract has been registered
2023
Authors
Richard Helliwell Tommy Ruud Davide Bochicchio Anne Grete Kongsted Matthias Koesling Stig Milan Thamsborg Marina Spinu Marina Stukelj Atle WibeAbstract
No abstract has been registered
Authors
Matthias KoeslingAbstract
Enabling the FARMnor LCA-model (Flow Analysis and Resource Management for Norway) to handle large number of farms to calculate farm-specific LCA's. For each farm, data are automatically imported, the LCA calculated and results stored before proceeding with the next farm. This update allows in addition to conduct sensitivity and uncertainty analyses.
Authors
Matthias KoeslingAbstract
Extending the FARMnor model (Flow Analysis and Resource Management for Norway) for sheep based on the guidelines from IPCC (2019) and Carbon Limits (2021). In the calultaions it is differentiated between lambs, sheep, ewes and rams and period in barn as well as grazing farm- and rangeland. In addition the possibility to include carbon sequestration due to grazing rangeland was added.