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.
2010
Forfattere
Åsmund AsdalSammendrag
Poteten kommer opprinnelig fra Sør-Amerika der det finnes over 180 arter i Solanum-slekten. Etter at den kom til Europa på 1600-tallet er det blitt utviklet tusenvis av sorter og landraser av potet. I Norge blir et par hundre typer tatt vare på i genbank, hos forsknings- og foredlingsinstitusjoner og hos private samlere. Ved det internasjonale forskningsinstituttet for potet i Peru (CIP) blir 4200 sorter og 1500 varianter av viltvoksende potet tatt vare på. Potetfrø fra Peru er lagret i frøhvelvet på Svalbard. Her kan du se et lite utsnitt av mangfoldet.Plakat laget til Naturmangfoldåret 2010.
Forfattere
Per Jarle MøllerhagenSammendrag
Det er ikke registrert sammendrag
Sammendrag
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Forfattere
Siv Lene Gangenes SkarSammendrag
Abstract Quality of vegetables is influenced by many factors during growth. Changeable factors for the farmers are; variety, type of fertilizer, pest treatment methods and to some extent soil type. On the other hand pests (esp. fungi spore infection by air), precipitation, temperature and light conditions are unchangeable factors that can vary largely from year to year. In this presentation the most important pre harvest factors involved in quality changes of vegetables are discussed. Nitrogen tends to be an important factor that affects both yield and physical quality of vegetables as well as dry matter and content of minerals and secondary components. Generally, reduced levels of nitrogen increases dry matter and concentration of essential amino acids, flavour components, sugars, phenolic compounds, but not carotenes. On the other hand, content of nitrate decreases with level of nitrogen fertilisation. However, too little nitrogen restricts growth and can reduce quality of nitrogen demanding crops like Brassica vegetables. Attach by plant pathogens and insects stimulate the plants defence system by producing secondary plant compounds like phytoalexins and antioxidants that could either have positive or negative impact on health. On the other hand, certain pests could produce mycotoxins that contaminate vegetables and make them toxic to humans. Pesticide free cultivation systems can in general increase the probability for higher content of phytoalexins and mycotoxins in vegetables. Organic farming with absence of pesticides and restricted use of nitrogen adapt for an increase in content of the positive health related compounds, while at the same time decreasing the negative related compounds like pesticides and nitrate. Despite this high importance of nitrogen and pest treatment, climate factors that differ between years has shown to highly affect content of secondary compounds and sensory quality of vegetables. On the other hand, variety is a controllable factor that has an overwhelming effect of several quality factors like, sensory quality, colour and content of vitamins, minerals and secondary health related components. This could be utilised to improve quality of vegetables in both organic and conventional systems.
Sammendrag
Foreløpige resultater fra EMTOX-prosjektet
Forfattere
Tuula Kantola Mikko Vastaranta Xiaowei Yu Paivi Lyytikainen-Saarenmaa Markus Holopainen Mervi Talvitie Sanna Kaasalainen Svein Solberg Juha HyyppäSammendrag
Climate change has been observed to be related to the increase of forest insect damages in the boreal zone. The prediction of the changes in the distribution of insect-caused forest damages has become a topical issue in the field of forest research. The common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini caused severe growth losses and tree mortality of Scots pine (Pinus sylvestris L.) (Pinaceae). Logistic regression is commonly used in modelling the probability of occurrence of an event. In this study the logistic regression was investigated for predicting the needle loss of individual Scots pines (pine) using the features derived from airborne laser scanning (ALS) data. The defoliation level of 164 trees was determined subjectively in the field. Statistical ALS features were extracted for single trees and used as independent variables in logistic regression models. Classification accuracy of defoliation was 87.8% as respective kappa-value was 0.82. For comparison, only penetration features were selected and classification accuracy of 78.0% was achieved (kappa=0.56). Based on the results, it is concluded that ALS based prediction of needle losses is capable to provide accurate estimates for individual trees.
Sammendrag
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Sammendrag
We conclude that these regression models can be used as a basis for the development of prediction models for DON in spring wheat and oats, there are, however, still problems creating general models across geographic areas.
Sammendrag
While forest inventories based on airborne laser scanning data (ALS) using the area based approach (ABA) have reached operational status, methods using the individual tree crown approach (ITC) have basically remained a research issue. One of the main obstacles for operational applications of ITC is biased results often experienced due to segmentation errors. In this article, we propose a new method, called "semi-ITC" that overcomes the main problems related to ITC by imputing ground truth data within crown segments from the nearest neighboring segment. This may be none, one, or several trees. The distances between segments were derived based on a set of explanatory variables using two nonparametric methods, i.e., most similar neighbor inference (MSN) and random forest (RF). RF favored the imputation of common observations in the data set which resulted in significant biases. Main conclusions are therefore based on MSN. The explanatory variables were calculated by means of small footprint ALS and multispectral data. When testing with empirical data the new method compared favorably to the well-known ABA. Another advantage of the new method over the ABA is that it allowed for the modeling of rare tree species. The results of predicting timber volume with the semi-ITC method were unbiased and the root mean squared error (RMSE) on plot level was smaller than the standard deviation of the observed response variables. The relative RMSEs after cross validation using semi-ITC for total volume and volume of the individual species pine, spruce, birch, and aspen on plot level were 17, 38, 40, 101, and 222%, respectively. Due to the unbiasedness of the estimation, this study is a showcase for how to use crown segments resulting from ITC algorithms in a forest inventory context. (C) 2009 Elsevier Inc. All rights reserved.
Sammendrag
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