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

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Sammendrag

Rubus idaeus L. (red raspberry), is a perennial woody plant species of the Rosaceae family that is widely cultivated in the temperate regions of world and is thus an economically important soft fruit species. It is prized for its flavour and aroma, as well as a high content of healthful compounds such as vitamins and antioxidants. Breeding programs exist globally for red raspberry, but variety development is a long and challenging process. Genomic and molecular tools for red raspberry are valuable resources for breeding. Here, a chromosome-length genome sequence assembly and related gene predictions for the red raspberry cultivar ‘Anitra’ are presented, comprising PacBio long read sequencing scaffolded using Hi-C sequence data. The assembled genome sequence totalled 291.7 Mbp, with 247.5 Mbp (84.8%) incorporated into seven sequencing scaffolds with an average length of 35.4 Mbp. A total of 39,448 protein-coding genes were predicted, 75% of which were functionally annotated. The seven chromosome scaffolds were anchored to a previously published genetic linkage map with a high degree of synteny and comparisons to genomes of closely related species within the Rosoideae revealed chromosome-scale rearrangements that have occurred over relatively short evolutionary periods. A chromosome-level genomic sequence of R. idaeus will be a valuable resource for the knowledge of its genome structure and function in red raspberry and will be a useful and important resource for researchers and plant breeders.

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Sammendrag

Sorption of nutrients such as NH4+ is often quoted as a critical property of biochar, explaining its value as a soil amendment and a filter material. However, published values for NH4+ sorption to biochar vary by more than 3 orders of magnitude, without consensus as to the source of this variability. This lack of understanding greatly limits our ability to use quantitative sorption measurements towards product design. Here, our objective was to conduct a quantitative analysis of the sources of variability, and infer which biochar traits are more favourable to high sorption capacity. To do so, we conducted a standardized remodelling exercise of published batch sorption studies using Langmuir sorption isotherm. We excluded studies presenting datasets that either could not be reconciled with the standard Langmuir sorption isotherm or generated clear outliers. Our analysis indicates that the magnitude of sorption capacity of unmodified biochar for NH4+ is lower than previously reported, with a median of 4.2 mg NH4+ g−1 and a maximum reported sorption capacity of 22.8 mg NH4+ g−1. Activation resulted in a significant relative improvement in sorption capacity, but absolute improvements remain modest, with a maximum reported sorption of 27.56 mg NH4+ g−1 for an activated biochar. Methodology appeared to substantially impact sorption estimates, especially practices such as pH control of batch sorption solution and ash removal. Our results highlight some significant challenges in the quantification of NH4+ sorption by biochar and our curated data set provides a potentially valuable scale against which future estimates can be assessed.

Sammendrag

Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment.