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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.

2019

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Sammendrag

Knowledge of soil microtopography and its changes in space and over time is important to the understanding of how tillage influences infiltration, runoff generation and erosion. In this study, the use of a terrestrial laser scanner (TLS) is assessed for its ability to quantify small changes in the soil surface at high spatial resolutions for a relatively large surface area (100 m2). Changes in soil surface morphology during snow cover and melt are driven by frost heave, slaking, pressure exertion by the snowpack and overland flow (erosion and deposition). An attempt is undertaken to link these processes to observed changes at the soil surface. A new algorithm for soil surface roughness is introduced to make optimal use of the raw point cloud. This algorithm is less scale dependent than several commonly used roughness calculations. The results of this study show that TLSs can be used for multitemporal scanning of large surfaces and that small changes in surface elevation and roughness can be detected. Statistical analysis of the observed changes against terrain indices did not yield significant evidence for process differentiation.

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High-throughput sequencing is increasingly favoured to assay the presence and abundance of microRNAs (miRNAs) in biological samples, even from low RNA amounts, and a number of commercial vendors now offer kits that allow miRNA sequencing from sub-nanogram (ng) inputs. Although biases introduced during library preparation have been documented, the relative performance of current reagent kits has not been investigated in detail. Here, six commercial kits capable of handling <100ng total RNA input were used for library preparation, performed by kit manufactures, on synthetic miRNAs of known quantities and human total RNA samples. We compared the performance of miRNA detection sensitivity, reliability, titration response and the ability to detect differentially expressed miRNAs. In addition, we assessed the use of unique molecular identifiers (UMI) sequence tags in one kit. We observed differences in detection sensitivity and ability to identify differentially expressed miRNAs between the kits, but none were able to detect the full repertoire of synthetic miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the relative levels of the majority of miRNAs. UMI tags, at least within the input ranges tested, offered little advantage to improve data utility. In conclusion, biases in miRNA abundance are heavily influenced by the kit used for library preparation, suggesting that comparisons of datasets prepared by different procedures should be made with caution. This article is intended to assist researchers select the most appropriate kit for their experimental conditions.