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.
2024
Forfattere
Melissa MagerøySammendrag
Det er ikke registrert sammendrag
Forfattere
Randika K. Makumbura Prasad Dissanayake Miyuru Gunathilake Namal Rathnayake Komali Kantamaneni Upaka RathnayakeSammendrag
This study presents the first attempt in Sri Lanka to generate a forest fire risk map covering the entire country using a GIS-based forest fire index (FFI) model. The model utilized seven parameters: land use, temperature, slope, proximity to roads and settlements, elevation, and aspect. All these parameters were derived using GIS techniques with ArcGIS10.4 and QGIS3.16. Data from Remote Sensing sources, particularly the MODIS hotspot real-world dataset, were employed to gather fire count information for the year 2020. Validation was conducted through the merging hotspot technique and kernel density estimation (KDE). The research findings highlight the districts in the Central and Uva provinces, such as NuwaraEliya (10.3 km2), Kandy (2.74 km2), and Badulla (10.41 km2), as having a “very low risk" of forest fire potential. Conversely, districts like Hambanthota (0.1 km2), Kaluthara (0.04 km2), and Kurunegala (0.2 km2) exhibit a “very high risk" of forest fire potential, although it is negligible compared country's total area. Overall, the study suggests that Sri Lanka is not currently facing a significant threat of forest fires and is a “medium risk" of forest fires as 49.49% of land falls under this category. These results are of immense value to relevant authorities, including the Ministry of Wildlife and Forest Resources Conservation, in formulating effective strategies to manage and mitigate forest fire risks in the country.
Sammendrag
Soybean pod count is a crucial aspect of soybean plant phenotyping, offering valuable reference information for breeding and planting management. Traditional manual counting methods are not only costly but also prone to errors. Existing detection-based soybean pod counting methods face challenges due to the crowded and uneven distribution of soybean pods on the plants. To tackle this issue, we propose a Soybean Pod Counting Network (SPCN) for accurate soybean pod counting. SPCN is a density map-based architecture based on Hybrid Dilated Convolution (HDC) strategy and attention mechanism for feature extraction, using the Unbalanced Optimal Transport (UOT) loss function for supervising density map generation. Additionally, we introduce a new diverse dataset, BeanCount-1500, comprising of 24,684 images of 316 soybean varieties with various backgrounds and lighting conditions. Extensive experiments on BeanCount-1500 demonstrate the advantages of SPCN in soybean pod counting with an Mean Absolute Error(MAE) and an Mean Squared Error(MSE) of 4.37 and 6.45, respectively, significantly outperforming the current competing method by a substantial margin. Its excellent performance on the Renshou2021 dataset further confirms its outstanding generalization potential. Overall, the proposed method can provide technical support for intelligent breeding and planting management of soybean, promoting the digital and precise management of agriculture in general.
Sammendrag
Six seed mixtures differing in number of species and their proportion of timothy (Phleum pratense L.) were tested during three/four production (ley) years in replicated field experiments at three climatically different sites in Norway; one a mountainous inland site at 61° N (Løken) and two in coastal environments, at 61° N (Fureneset) and 65° N (Tjøtta). There were significant differences in forage accumulation (FA) and digestible forage accumulation (DFA) between the three sites. There was a significant FA decline from the third to the fourth ley year for mixtures containing timothy, but not for mixtures without timothy. Estimated interannual FA- stability was higher for timothy-based seed mixtures than for mixtures without timothy at the inland site, but FA-stability was lower at the coastal sites. In the third-year herbage of timothy-based mixtures at the inland site consisted almost solely of timothy, whereas at the coastal sites meadow fescue (Festuca pratensis Huds.) and especially tall fescue (F. arundinacea Schreb.) dominated. In seed mixtures without timothy, cocksfoot (Dactylis glomerata L.) suppressed other species at the inland site, whereas at the coastal sites, tall fescue and ryegrasses (Lolium spp.) were the dominant species in the third-year herbage. Length of growing season and site-specific growing conditions were important drivers for the observed species changes. Timothy can thus be recommended for ley establishment at sites where the growing season is short (<4 months) and plant growth is intensive, but under conditions with a longer growing season it needs to be sown in mixtures with grass species that surpass the regrowth capacity of timothy.
Forfattere
Eva Narten HøbergSammendrag
Det er ikke registrert sammendrag
Forfattere
Eva Narten HøbergSammendrag
Det er ikke registrert sammendrag
Sammendrag
Det er ikke registrert sammendrag
Intervju – Spill på lag med nytteinsektene i jordbruket
Marie Vestergaard Henriksen, Liv Jorunn Hind
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Pia Heltoft ThomsenSammendrag
Det er ikke registrert sammendrag
Sammendrag
Climate change with fluctuations in weather patterns, environmental concerns, and increased costs of mineral fertilizers all demand adjustment of nitrogen (N) used for forage production. The aim of the study was to investigate the effects of splitting N application in spring on dry-matter (DM) yield, crude protein (CP) content and protein quality of timothy-meadow fescue leys. The trial was conducted during two years at three locations (Kvithamar and Særheim, Norway and Länghem, Sweden). Split N application with 60 kg N ha–1 at onset of grass growth in April and 50 kg N ha–1 in May resulted in the same DM yields and CP concentrations as a single application of 110 kg N ha–1 in April in Kvithamar the first year and Særheim both years. In Länghem both years and for Kvithamar in the second year, a late application two weeks before first cut gave less DM yield than the single full application in April. Split application did not affect the contents of nonprotein N or nitrate.