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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.

NIBIO's Scientific Publications →

2025

Authors

Frode Veggeland

Abstract

No abstract has been registered

Authors

Mette Thomsen

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No abstract has been registered

Authors

Darius Kviklys

Abstract

No abstract has been registered

Authors

Darius Kviklys

Abstract

No abstract has been registered

Authors

Lillian Øygarden Marianne Vileid Uleberg Jostein Frydenlund Frøydis Gillund Arne Bardalen

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Foredrag på NJF Nordic Baltic Symposium

Authors

Anniken Fure Stensrud Åshild Ergon Randi Berland Frøseth

Abstract

Genetically diverse spring wheat and farmers’ mass selection can improve yield stability in organic systems.

Authors

Adomaitytė A. Mindaugas Liaudanskas Darius Kviklys Jonas Viskelis Juozas Lanauskas Valdimaras Janulis

Abstract

No abstract has been registered

Authors

Adomaitytė Mindaugas Liaudanskas Sedbare Juozas Lanauskas Darius Kviklys Jonas Viskelis

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No abstract has been registered

Authors

Adomaitytė Mindaugas Liaudanskas Sedbare Juozas Lanauskas Jonas Viskelis Darius Kviklys

Abstract

No abstract has been registered

To document

Authors

Inger Martinussen Marius Hauglin Aksel Granhus Anne Linn Hykkerud Jari Miina

Abstract

The year-to-year variation in the availability of lingonberries (Vaccinium vitis-idaea L.) is a challenge for commercial exploitation. There is also a need to identify the best locations for lingonberry harvesting. Here, we present research that utilized field observations from the Norwegian National Forest Inventory to model and map the association between lingonberry cover and stand characteristics. Additionally, a set of permanent sampling plots were established for annual recording of berry yields in different Norwegian regions, representing variations in slope and forest characteristics. Ultimately, the recorded information on yield from the temporary sample plots were combined with predictions from the cover model, as well as data from remote sensing and climatic data from nearby weather stations (for locations see Figure 1a) to derive: 1) a model for lingonberry yield, and 2) and a yield map covering all forest land in Norway. Variables included in the final berry yield model are main tree species, soil parent material, mean temperature June-August, stand basal area, latitude, slope and distance to coastline (Miina et al., 2024).