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.
2017
Sammendrag
No abstract has been registered
Sammendrag
No abstract has been registered
Forfattere
Johannes BreidenbachSammendrag
No abstract has been registered
Sammendrag
Today’s modern precision agriculture applications have a huge demand for data with high spatial and temporal resolution. This leads to the need of unmanned aerial vehicles (UAV) as sensor platforms providing both, easy use and a high area coverage. This study shows the successful development of a prototype hybrid UAV for practical applications in precision agriculture. The UAV consists of an off-the-shelf fixed-wing fuselage, which has been enhanced with multi-rotor functionality. It was programmed to perform pre-defined waypoint missions completely autonomously, including vertical take-off, horizontal flight, and vertical landing. The UAV was tested for its return-to-home (RTH) accuracy, power consumption and general flight performance at different wind speeds. The RTH accuracy was 43.7 cm in average, with a root-mean-square error of 39.9 cm. The power consumption raised with an increase in wind speed. An extrapolation of the analysed power consumption to conditions without wind resulted in an estimated 40 km travel range, when we assumed a 25 % safety margin of remaining battery capacity. This translates to a maximal area coverage of 300 ha for a scenario with 18 m/s airspeed, 50 minutes flight time, 120 m AGL altitude, and a desired 70 % of image side-lap and 85 % forward-lap. The ground sample distance with an in-built RGB camera was 3.5 cm, which we consider sufficient for farm-scale mapping missions for most precision agriculture applications.
Sammendrag
Pine wood nematode (PWN), Bursaphelenchus xylophilus, is a threat for pine species (Pinus spp.) throughout the world. The nematode is native to North America, and invaded Japan, China, Korea, and Taiwan, and more recently Portugal and Spain. PWN enters new areas through trade in wood products. Once established, eradication is not practically feasible. Therefore, preventing entry of PWN into new areas is crucial. Entry risk analysis can assist in targeting management to reduce the probability of entry. Assessing the entry of PWN is challenging due to the complexity of the wood trade and the wood processing chain. In this paper, we develop a pathway model that describes the wood trade and wood processing chain to determine the structure of the entry process. We consider entry of PWN through imported coniferous wood from China, a possible origin of Portuguese populations, to Europe. We show that exposure increased over years due to an increase in imports of sawn wood. From 2000 to 2012, Europe received an estimated 84 PWN propagules from China, 88% of which arose from imported sawn wood and 12% from round wood. The region in Portugal where the PWN was first reported is among those with the highest PWN transfer per unit of imported wood due to a high host cover and vector activity. An estimated 62% of PWN is expected to enter in countries where PWN is not expected to cause the wilt of pine trees because of low summer temperatures (e.g., Belgium, Sweden, Norway). In these countries, PWN is not easily detected, and such countries can thus serve as potential reservoirs of PWN. The model identifies ports and regions with high exposure, which helps targeting monitoring and surveillance, even in areas where wilt disease is not expected to occur. In addition, we show that exposure is most efficiently reduced by additional treatments in the country of origin, and/or import wood from PWN-free zones. Pathway modelling assists plant health managers in analyzing risks along the pathway and planning measures for enhancing biosecurity.
Sammendrag
No abstract has been registered
Sammendrag
In fungi, distribution of secondary metabolite (SM) gene clusters is often associated with host- or environment-specific benefits provided by SMs. In the plant pathogen Alternaria brassicicola (Dothideomycetes), the DEP cluster confers an ability to synthesize the SM depudecin, a histone deacetylase inhibitor that contributes weakly to virulence. The DEP cluster includes genes encoding enzymes, a transporter, and a transcription regulator. We investigated the distribution and evolution of the DEP cluster in 585 fungal genomes and found a wide but sporadic distribution among Dothideomycetes, Sordariomycetes, and Eurotiomycetes. We confirmed DEP gene expression and depudecin production in one fungus, Fusarium langsethiae. Phylogenetic analyses suggested 6–10 horizontal gene transfers (HGTs) of the cluster, including a transfer that led to the presence of closely related cluster homologs in Alternaria and Fusarium. The analyses also indicated that HGTs were frequently followed by loss/pseudogenization of one or more DEP genes. Independent cluster inactivation was inferred in at least four fungal classes. Analyses of transitions among functional, pseudogenized, and absent states of DEP genes among Fusarium species suggest enzyme-encoding genes are lost at higher rates than the transporter (DEP3) and regulatory (DEP6) genes. The phenotype of an experimentally-induced DEP3 mutant of Fusarium did not support the hypothesis that selective retention of DEP3 and DEP6 protects fungi from exogenous depudecin. Together, the results suggest that HGT and gene loss have contributed significantly to DEP cluster distribution, and that some DEP genes provide a greater fitness benefit possibly due to a differential tendency to form network connections.
Sammendrag
No abstract has been registered
Forfattere
Marcos Viejo Elena Carneros Hugh Cross Igor A. Yakovlev Carl Gunnar Fossdal Jorunn Elisabeth OlsenSammendrag
No abstract has been registered
Sammendrag
The use of digital aerial photogrammetry (DAP) for forest inventory purposes has been widely studied and can produce comparable accuracy compared with airborne laser scanning (ALS) in small, homogeneous areas. However, the accuracy of DAP for large scale applications with heterogeneous terrain and forest vegetation has not yet been reported. In this study we examined the accuracy of timber volume, biomass and basal area prediction models based on DAP and national forest inventory (NFI) data on a large area in central Norway. Two separate point clouds were derived from aerial image acquisitions of 2010 and 2013. Vegetation heights were extracted by subtracting terrain elevation derived from ALS. A large number of NFI sample plots (483) measured between 2010 and 2014 were used as reference data to fit linear models for timber volume, biomass and basal area with height metrics derived from the DAP data as explanatory variables. Variables describing the heterogeneous environmental and image acquisition conditions were calculated and their influence on the model accuracy was tested. The results showed that forest parameter prediction using DAP works well when applied to a large area. The model fits of the timber volume, biomass and basal area models were good with R2 of 0.80, 0.81, 0.81 and RMSEs of 41.43 m3 ha−1 (55% of the mean observed value), 32.49 t ha−1 (47%), 5.19 m2 ha−1 (41%), respectively. Only a small proportion of the variation could be attributed to the heterogeneous conditions. The inclusion of the relative sun inclination led to an improvement of the model RMSEs by 2% of the mean observed values. The relatively low cost and stability across large areas make DAP an attractive source of auxiliary information for large scale forest inventories.