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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.

2023

Sammendrag

Normal log lengths in Norway are 3–6 m (NL), but occasionally there is a demand for short timber with a 2.5 m log length (ST). There are concerns that ST could reduce the forwarders' productivity. Six type stands were created based on harvester data. Different assortment distributions, conditions, and forwarders were simulated in each type stand. It was found that an additional ST assortment almost always decreased productivity (from –15.5 to +4%). Increased forwarding distance (m), more difficult driving conditions, and increased log concentration [m3·(100 m strip road)–1] decreased the productivity difference between sites with ST and NL and sites with only NL. Increased forwarder size increased the productivity difference between sites with ST and NL and sites with only NL. It is possible to load two stacks of ST on some forwarders. Such loading was more productive than loading one stack on longer forwarding distances, while the opposite was the case on short distances. However, loading two stacks of ST can lead to overloading.

Sammendrag

After fungal decay experiments chemical characterisation of the wood is often a routine and several methodological approaches are available. In this study, we tested if simultaneous thermal analysis (STA) is a valid alternative to traditional wet chemical methods since STA allows significantly smaller sample size and faster analysis. Three model fungi including the brown rot fungi Rhodonia placenta and Gloeophyllum trabeum and the white rot fungus Trametes versicolor were employed in the study using Norway spruce as substrate. The experiment was harvested after 10, 20 and 52 weeks. At each harvest interval, aliquots of the material were characterized by STA and wet chemical methods. The results validated that STA can be effectively used to estimate cell wall composition of brown rot depolymerised wood. However, STA slightly overestimated cellulose at brown rot decay above 50%. The method was not verified for simultaneous white rot because STA only estimated hemicellulose correctly compared to the wet chemical method. Hence, STA is considered suitable for brown rot fungi below 50% mass loss but not for simultaneous white rot because STA did not estimate cellulose and lignin correctly.

Til dokument

Sammendrag

Yield maps give farmers information about growth conditions and can be a tool for sitespecific crop management. Combine harvesters may provide farmers with detailed yield maps if there is a constant flow of a certain amount of biomass through the yield sensor. This is unachievable for grass seeds because the weight of the intake is generally too small to record the variation. Therefore, there is a need to find another way to make grass seed yield maps. We studied seed yield variation in two red fescue (Festuca rubra) fields with variation in management and soil fertility, respectively. We estimated five vegetation indices (VI) based on RGB images taken from a drone to describe yield variation, and trained prediction models based on relatively few harvested plots. Only results from the VI showing the strongest correlation between the index and the yield are presented (Normalized Excess Green Index (ExG) and Normalized Green/Red Difference Index (NGRDI)). The study indicates that it is possible to predict the yield variation in a grass field based on relatively few harvested plots, provided the plots represent contrasting yield levels. The prediction errors in yield (RMSE) ranged from 171 kg ha-1 to 231 kg ha-1, with no clear influence of the size of the training data set. Using random selection of plots instead of selecting plots representing contrasting yield levels resulted in slightly better predictions when evaluated on an average of ten random selections. However, using random selection of plots came with a risk of poor predictions due to the occasional lack of correlation between yield and VI. The exact timing of unmanned aerial vehicles (UAVs) image capture showed to be unimportant in the weeks before harvest.