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.
2022
Sammendrag
Book of Abstracts p. 225: Perennial sow-thistle (Sonchus arvensis L.) is a problematic weed in arable crops in northern Europe. To control S. arvensis, strategies which reduce both seeds and creeping root production are essential. Inducing repeated sprouting should result in depleting root reserves and reduction in the subsequent shoot emergence. Earlier studies of S. arvensis in the northern European countries have shown a restricted sprouting ability from July/August/ September to October/November. To better understand the sprouting patterns, we conducted joint outdoor pot experiments from March 2020 until July 2021 in three northern European regions: Northern Germany, Norway, and Finland. In each pot, root pieces of 5 cm from local plant material were planted at 5cm depth. Above-ground plants were cut at the soil surface in the growing season of 2020 at 1) flower-bud stage, 2) first visible open flowers, 3) start of seed production, and 4) withering stage. Shoots were counted monthly in 2020 and 2021. In the year 2020, in Germany, sprouting, flowering, seed-set, and withering started earlier than at the other two sites. Significantly more shoots showed up at the flower-bud stage in Germany and Finland compared to Norway. In Finland, significantly more shoots were observed at the later cutting stages compared to the first counts at the flower bud stage. As a subsequent effect, fewest shoots showed up in 2021 at the German and Finnish sites after cutting at flower bud and early flowering stage. The lowest emerged shoot number in 2021 for Norway tended to occur after cutting at the flower bud stage and the start of seed production. Accordingly, cutting at the flower-bud stage decreases the ability to produce shoots in the next year. Keywords: Perennial sow-thistle, sprouting, cutting, shoots Acknowledgements: This research was part of the project “AC/DC-weeds” which is funded by ERA-Net Cofund SusCrop/EU Horizon 2020, Grant no. 771134
Forfattere
Jorunn BørveSammendrag
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Forfattere
Trygve S. Aamlid Jon Sæland Arne Svalastog Simen Settendal Victoria Stornes Moen Ove HetlandSammendrag
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Sammendrag
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Forfattere
Zahra BitarafanSammendrag
https://nibio.no/nyheter/sproyting-med-klopyralid-kan-gi-rester-av-ugrasmidler-i-honning?locationfilter=true
Sammendrag
Stand-level growth and yield models are important tools that support forest managers and policymakers. We used recent data from the Norwegian National Forest Inventory to develop stand-level models, with components for dominant height, survival (number of survived trees), ingrowth (number of recruited trees), basal area, and total volume, that can predict long-term stand dynamics (i.e. 150 years) for the main species in Norway, namely Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and birch (Betula pubescens Ehrh. and Betula pendula Roth). The data used represent the structurally heterogeneous forests found throughout Norway with a wide range of ages, tree size mixtures, and management intensities. This represents an important alternative to the use of dedicated and closely monitored long-term experiments established in single species even-aged forests for the purpose of building these stand-level models. Model examination by means of various fit statistics indicated that the models were unbiased, performed well within the data range and extrapolated to biologically plausible patterns. The proposed models have great potential to form the foundation for more sophisticated models, in which the influence of other factors such as natural disturbances, stand structure including species mixtures, and management practices can be included.
Forfattere
Giorgia Carnovale Shaun Allan Leivers Filipa Rosa Hans Ragnar Norli Edvard Hortemo Trude Wicklund Svein Jarle Horn Kari SkjånesSammendrag
Microalgal biomass is widely studied for its possible application in food and human nutrition due to its multiple potential health benefits, and to address raising sustainability concerns. An interesting field whereby to further explore the application of microalgae is that of beer brewing, due to the capacity of some species to accumulate large amounts of starch under specific growth conditions. The marine species Tetraselmis chui is a well-known starch producer, and was selected in this study for the production of biomass to be explored as an active ingredient in beer brewing. Cultivation was performed under nitrogen deprivation in 250 L tubular photobioreactors, producing a biomass containing 50% starch. The properties of high-starch microalgal biomass in a traditional mashing process were then assessed to identify critical steps and challenges, test the efficiency of fermentable sugar release, and develop a protocol for small-scale brewing trials. Finally, T. chui was successfully integrated at a small scale into the brewing process as an active ingredient, producing microalgae-enriched beer containing up to 20% algal biomass. The addition of microalgae had a noticeable effect on the beer properties, resulting in a product with distinct sensory properties. Regulation of pH proved to be a key parameter in the process.
Sammendrag
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Forfattere
Helani Perera Miyuru Gunathilake Ravindu Panditharathne Najib Al-mahbashi Upaka RathnayakeSammendrag
Satellite-based precipitation products, (SbPPs) have piqued the interest of a number of researchers as a reliable replacement for observed rainfall data which often have limited time spans and missing days. The SbPPs possess certain uncertainties, thus, they cannot be directly used without comparing against observed rainfall data prior to use. The Kelani river basin is Sri Lanka’s fourth longest river and the main source of water for almost 5 million people. Therefore, this research study aims to identify the potential of using SbPPs as a different method to measure rain besides using a rain gauge. Furthermore, the aim of the work is to examine the trends in precipitation products in the Kelani river basin. Three SbPPs, precipitation estimation using remotely sensed information using artificial neural networks (PERSIANN), PERSIANN-cloud classification system (CCS), and PERSIANN-climate data record (CDR) and ground observed rain gauge daily rainfall data at nine locations were used for the analysis. Four continuous evaluation indices, namely, root mean square error (RMSE), (percent bias) PBias, correlation coefficient (CC), and Nash‒Sutcliffe efficiency (NSE) were used to determine the accuracy by comparing against observed rainfall data. Four categorical indices including probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and proportional constant (PC) were used to evaluate the rainfall detection capability of SbPPs. Mann‒Kendall test and Sen’s slope estimator were used to identifying whether a trend was present while the magnitudes of these were calculated by Sen’s slope. PERSIANN-CDR performed well by showing better performance in both POD and CSI. When compared to observed rainfall data, the PERSIANN product had the lowest RMSE value, while all products indicated underestimations. The CC and NSE of all three products with observed rainfall data were also low. Mixed results were obtained for the trend analysis as well. The overall results showed that all three products are not a better choice for the chosen study area.
Forfattere
Bjørn Egil FløSammendrag
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