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.
2021
Abstract
Det er ikke registrert sammendrag
Authors
T. Haikonen Jahn Davik M. Rantanen P. Parikka J. Näkkilä S. Karhu Muath K Alsheikh S. H. HjeltnesAbstract
Climate change may result in increased root system stresses in strawberry cultivation, requiring cultivars with root and crown-related resistance and resiliency traits. Approaches to widen the genetic basis and improve tools for the incorporation of novel variation are relevant to plant breeding for changing climate. The pre-breeding project NORDFRUIT is a Nordic public-private-partnership project that aims to introduce novel genetic variation from new sources, support the use of existing genetic resources adapted to Nordic and Baltic cultivation conditions, and develop efficient tools to speed up germplasm evaluation in breeding programs for climate adaptation. Pre-evaluated genotypes of Fragaria chiloensis or Fragaria virginiana were used as parents in interspecific (species hybridization) crosses, re-creating the garden strawberry hybrid species, F. ×ananassa. The created F1 hybrid seedlings were propagated by runners for replicated phenotyping trials. A greenhouse assay to test root-shoot biomass partition, growth vigour and Phytophthora cactorum resistance in these small plants was scaled up from an earlier assay based on nutrient film technology (NFT). The observed variation in disease symptom appearance, root-shoot ratio, and root proliferation indicated promising traits in the strawberry hybrid material, to be exploited further in genomic studies and to develop genome-assisted resistance breeding. The on-going work also includes field testing of the same hybrid material to evaluate winter hardiness, powdery mildew incidence, and fruit traits.
Authors
Sophie Mentzel Merete Grung Knut-Erik Tollefsen Marianne Stenrød Petersen Karina S. Jannicke MoeAbstract
The aquatic environment is constantly exposed to various chemicals caused by anthropogenic activities such as agricultural practices using plant protection products. Traditional Environmental Risk Assessment is based on calculated risk estimations usually representing a ratio of exposure to effects, in combination with assessment factors to account for uncertainty. In this study, we explore a more informative approach through probabilistic risk assessment, where probability distributions for exposure and effects are expressed and enable accounting for variability and uncertainty better. We focus on the risk assessment of various pesticides in a representative study area in the south east of Norway. Exposure data in this research was provided by the Norwegian Agricultural Environmental Monitoring Programme (JOVA)/ or predicted exposure concentration from a pesticide exposure model and effect data was derived from the NIVA Risk Assessment database (RAdb, www.niva.no/radb). A Bayesian network model is used as an alternative probabilistic approach to assess the risks of chemical. Bayesian Networks can serve as meta-models that link selected input and output variables from several separate project outputs and offer a transparent way of evaluating the required characterization of uncertainty for ERA. They can predict the probability of several risk levels, while facilitating the communication of estimates and uncertainties.
Authors
Sophie Mentzel Merete Grung Knut-Erik Tollefsen Marianne Stenrød Roger Holten S. Jannicke MoeAbstract
In Northern Europe, future changes in land-use and weather patterns are expected to result in increased precipitation and temperature this may cause an increase in plant disease and insect pests. In addition, predicted population increase will change the production demands and in turn alter agricultural practices such as crop types and with that the use pattern of pesticides. Considering these variabilities and magnitudes of pesticide exposure to the aquatic environment still needs to be accounted for better in current probabilistic risk assessment. In order to improve ecological risk assessment, this study explores an alternative approach to probabilistic risk assessment using a Bayesian Network, as these can serve as meta-models that link selected input and output variables from other models and information sources. The developed model integrates variability in both exposure and effects in the calculation of risk estimate. We focus on environmental risk of pesticides in two Norwegian case study region representatives of northern Europe. Using pesticide fate and transport models (e.g. WISPE), environmental factors such as soil and site parameters together with chemical properties and climate scenarios (current and predicted) are linked to the exposure of a pesticide in the selected study area. In the long term, the use of tools based on Bayesian Network models will allow for a more refined assessment and targeted management of ecological risks by industry and policy makers.
Authors
Sophie Mentzel Merete Grung Knut-Erik Tollefsen Marianne Stenrød Roger Holten S. Jannicke MoeAbstract
Future weather patterns are expected to result in increased precipitation and temperature, in Northern Europe. These changes can potentially cause an increase in plant disease and insect pests which will alter agricultural practice amongst other things the used crop types and application patterns of pesticides. We use a Bayesian network to explore a probabilistic risk assessment approach to better account for variabilities and magnitudes of pesticide exposure to the aquatic ecosystem. As Bayesian networks link selected input and output variables from various models and other information sources, they can serve as meta-models. In this study, we are using a pesticide fate and transport models (e.g. WISPE) with specific environmental factors such as soil and site parameters together with chemical properties and climate scenarios that are linked to a representative Norwegian study area. The derived exposure of pesticide of the study area is integrated in the Bayesian network model to estimate the risk to the aquatic ecosystem also integrating an effect distribution derived from toxicity test. This Bayesian network model will allow to incorporate climate predictions into ecological risk assessment.
Abstract
Det er ikke registrert sammendrag
Authors
Johan A. Stenberg Kjetil K. Melby Christer Magnusson Anders Nielsen Julie Rydning Micael Wendell Beatrix Alsanius Paal Krokene Mogens Nicolaisen Iben M. Thomsen Sandra A. I. Wright Trond RafossAbstract
Det er ikke registrert sammendrag
Authors
Giorgia Carnovale Filipa Rosa Volha Shapaval Simona Dzurendova Achim Kohler Trude Wicklund Svein Jarle Horn Maria Barbosa Kari SkjånesAbstract
ABSTRACT The use of microalgal starch has been studied in biorefinery frameworks to produce bioethanol or bioplastics, however, these products are currently not economically viable. Using starch−rich biomass as an ingredient in food applications is a novel way to create more value while expanding the product portfolio of the microalgal industry. Optimization of starch production in the food−approved species Chlorella vulgaris was the main objective of this study. High−throughput screening of biomass composition in response to multiple stressors was performed with FTIR spectroscopy and nitrogen starvation was identified as an important factor for starch accumulation. Further studies were subsequently performed to assess the role of light distribution, investigating photon supply rates in flat panel photobioreactors. Biomass specific photon supply rate proved to have a strong effect on the accumulation of storage compounds and starch−rich biomass with up to 30% starch was achieved in cultures with low inoculation density (0.1 g L−1) and high irradiation (1800 μmol m−2 s−1). A final large scale experiment was performed in 25 L tubular reactors, achieving a maximum of 44% starch in the biomass after 12 hours in nitrogen starved conditions. Keywords: Chlorella vulgaris, starch, FTIR, photon supply rate, microalgae
Authors
Stig A. Borgvang Dorinde Mechtilde Meike Kleinegris Viswanath Kiron Katerina Kousoulaki Maria Barbosa Anabela Raymundo Carlos Unamunzaga Anne Kjersti Uhlen Sander Hazewinkel Hans Torstein Kleivdal Trude Wicklund Kai Kristoffer Lie Nils-Arne Ekerhovd Kristian Fuglseth Dag Hjelle Arne Edvard Rosland Hortemo Hans Petter Kleppen Jørund Hagen Helen Haaland Per Fredriksen Shuichi Satoh Rene Wijffels Kari SkjånesAbstract
The knowledge- and technology platform developed within the ALGAE TO FUTURE project aims to lay a foundation for an industrial microalgae production in Norway. In the project ALGAE TO FUTURE, funded by the Norwegian Research Council 2017-2021, with a consortium of 20 national and international research and industry partners, research and product development of microalgae biomass have been approached from multiple angles merging multiple research fields. The focus of the research has been bioprocess developments linked to lipids, carbohydrates and proteins, where species selection and cultivation conditions are used to obtain microalgae biomass with specific nutrient composition targeting specific products. We have chosen to target the development of three example products, namely 1) bread using algae biomass with high protein content, 2) beer using algae biomass with high content of starch and starch-degrading enzymes, and 3) fish feed using algae biomass with high PUFA content. These case studies have been chosen in order to demonstrate the use of algal biomass from various algae species with highly different nutrient composition suitable for different products. We have in this project studied the whole process line from small scale microalgae cultivation technology, upscaling cultivation, processing of algae biomass, shelf life, food/ feed product development, food safety and consumers attitudes. Some highlights from the four-year project period will be presented. Results from these activities may contribute towards the use of microalgae as part of the future Norwegian bioeconomy.
Abstract
Mattilsynet har i samarbeid med NIBIO undersøkt nivåene av visse naturlige giftstoffer (plantetoksiner) for å få mer data og kunnskap om nivåene i utvalgte matvarer. Dette gjelder plantetoksinene tropane alkaloider i kornbasert mat og urtete, og pyrrolizidin alkaloider i te og urtete. I 2019 fant vi tropane alkaloider i form av atropin i 2 av 10 frokostblandinger og atropin og skopolamin i 1 av 5 urtete. Funnet var over den foreslåtte grenseverdien for tropane alkaloider i urtete. Det ble påvist pyrrolizidin alkaloider i 9 av 15 prøver av te og urtete. En av urteteene (merket ammete) hadde nivåer over den grenseverdien som nylig ble fastsatt for pyrrolizidin alkaloider i urtete i 2021. I 2020 ble det påvist tropane alkaloider i form av skopolamin i 2 av 5 prøver maismel, og pyrrolizidin alkaloider ble påvist i 18 av 25 prøver av urtete. Ingen av prøvene hadde nivåer over den foreslåtte grenseverdien for tropane alkaloider i maismel eller over grenseverdien som nylig ble fastsatt for pyrrolizidin alkaloider i urtete i 2021. Der det er gitt grenseverdier for disse giftstoffene i mat vil resultatene bli fulgt opp overfor selger av produktene og inngå i den offentlige kontrollen av reguleringen på matområdet. Der det ikke er gitt grenseverdier, vil resultatene bidra inn i kunnskapsgrunnlaget for vurdering av ny regulering av disse giftstoffene i mat.