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.
2018
Redaktører
Geir-Harald StrandSammendrag
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Forfattere
Anna Maria Vettraino Alberto Santini Christo Nikolov Jean-Claude Grégoire Rumen Tomov Andrei Orlinski Tiit Maaten Halldors Sverrisson Bjørn Økland René EschenSammendrag
The sentinel plants concept responds to the need for new strategies to identify and study potential plant pests (including pathogens) and assess associated risks before their introduction to other continents. However, even if very promising, this tool is not yet implemented on a large scale, partially because it requires adequate planning, long-term funding, strong local links and reliable collaborators. In addition, a wider implementation of sentinel plantations and sentinel nurseries requires knowledge of regulations and procedures regarding the possibilities for their establishment in different countries. In order to achieve this objective, a questionnaire survey was conducted in 2016, to which more than 40 countries around the world responded. The results reveal that many countries have few regulations specifically concerning the import of propagation material, making import of this relatively low-risk material easier than the import of larger living plants that may have been more exposed to pests in the exporting country. The planting of alien woody plants in the environment is possible for scientific purposes in most countries as exemption from general phytosanitary import requirements, but the import and planting of alien plant species may be regulated by different government departments. We will present the outcomes of this study, which will be useful to facilitate the selection of locations for future sentinel plants and may provide guidance on the rules for import of plant propagation material for the establishment of sentinel plants and sentinel nurseries in different countries.
Sammendrag
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Forfattere
Bjørn ØklandSammendrag
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Forfattere
Bjørn ØklandSammendrag
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Forfattere
Bjørn ØklandSammendrag
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Sammendrag
The fungus Neonectria fuckeliana has become an increasing problem on Norway spruce (Picea abies) in the Nordic countries during recent years. Canker wounds caused by the pathogen reduce timber quality and top-dieback is a problem for the Christmas tree industry. In this study, four inoculation trials were conducted to examine the ability of N. fuckeliana to cause disease on young Norway spruce plants and determine how different wound types would affect the occurrence and severity of the disease. Symptom development after 8–11 months was mainly mild and lesion lengths under bark were generally minor. However, N. fuckeliana could still be reisolated and/or molecularly detected. Slow disease development is in line with older studies describing N. fuckeliana as a weak pathogen. However, the results do not explain the serious increased damage by N. fuckeliana registered in Nordic forests and Christmas tree plantations. Potential management implications, such as shearing Christmas trees during periods of low inoculum pressure, cleaning secateurs between trees, and removal and burning of diseased branches and trees to avoid inoculum transfer and to keep disease pressure low, are based on experiments presented here and experiences with related pathogens.
Forfattere
Francisco Javier Ancin Murguzur Aitor Barbero-Lopez Sari Kontunen-Soppela Antti HaapalaSammendrag
Microbial growth on culture media is a commonplace technique to estimate the growth rate and virulence ofmicrobes, assess inhibitory effects of compounds and estimate potential damages of plant pathogens in agri-culture. Growth area measurement of solid cultures is still commonly performed as a manual process that re-quires skilled technicians and substantial time, thus warranting an automated system to reduce the workload andincrease measurement efficiency. A machine learning approach (Support Vector Machines) was developed tofully automate the area measurement process. We developed a functional model that processes images andreturns the microbial area coverage considerably faster than a manual measurement method, with minimal userinput and highly comparable results (R2= 0.88, kappa = 0.88) applicable over large datasets.
Sammendrag
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Forfattere
Mekjell MelandSammendrag
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