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.
2011
Authors
Louise R. Cooke Huub T.A.M. Schepers Arne Hermansen Ruairidh A. Bain Nick J. Bradshaw Faye Ritchie David S. Shaw Albartus Evenhuis Geert J.T. Kessel Johan G.N. Wander Björn Andersson Jens Grønbech Hansen Asko Hannukkala Ragnhild Nærstad Bent J. NielsenAbstract
No abstract has been registered
Abstract
Experimental evidence shows that Norway spruce can adjust adaptive traits by a kind of long-term memory of temperature and day length present at the time of its early seed development. This mechanism is termed epigenetics; changes in gene activity not based on differences in the genetic code and yet transferable from one generation to the next. This is a rapidly growing research field in human, animal and plant genetics.
Authors
Tore SkrøppaAbstract
No abstract has been registered
Authors
Tore SkrøppaAbstract
No abstract has been registered
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No abstract has been registered
Authors
Alastair James Ward Anne-Kristin LøesAbstract
No abstract has been registered
Authors
Signe Kynding Borgen Arne Grønlund Olof Andrén Thomas Kätterer Lars Bakken Keith PaustianAbstract
Monitoring changes in soil organic carbon (SOC) is not only linked to atmospheric CO2 dynamics, but also to the sustainability of agricultural systems, maintaining food security, reducing water pollution and soil erosion. In accordance with the methodology of the Intergovernmental Panel for Climate Change (IPCC), we developed a Tier 2 method for estimating CO2 emissions from cropland on mineral soils in Norway and compared the results with those of a Tier 1 method. As in most countries, long-term C stock or emission data sets useful for generating factors are scarce in Norway. We used a soil C balance model (ICBM) to calculate country-specific C stock change factors for relevant management systems. Agricultural activity data for 31 agrozones, from 58 ºN to 71ºN, was applied to estimate annual net CO2 emissions from 1999 to 2009. Calculated annual net emissions were larger when estimated by the Tier 2 method than Tier 1 because i) Tier 2-generated stock change factors for crop rotations with animal manure application were larger than the Tier 1 default values and ii) major changes in agricultural management during the inventory period led to a reduction in manure availability. We conclude that model-based Tier 2 methods are promising when empirical data are limited, but activity data, especially regarding animal manure practices (application rates and crop rotation preferences) are crucial for emission estimates by the IPCC methods.
Authors
Fredrik Bøhler Bernt-Håvard ØyenAbstract
No abstract has been registered
Abstract
There is a great demand for involving rapid, non destructive and less time consuming methods for quick control and prediction of soil quality, environmental monitoring, and other precision measurements in agriculture. Near infrared reflectance spectroscopy (NIRS) is considered as an appropriate alternative method to conventional analytical methods for large scale measurements. The objective of this study was to investigate the possibilities of NIRS for prediction of some chemical properties of soil samples. A total of 97 samples from Stara Zagora, Kazanlak and Gurkovo region taken from the 0-40 cm layer were collected. Soil types were Luvisols, Vertisols, Fluvisols and Rankers. The samples were analyzed for total phosphorus by spectrometric determination of phosphorus soluble in sodium hydrogen carbonate solution, total nitrogen by Kjeldahl method, pH (H O)-potentiometrically and electrical conductivity (EC). 2 The spectral data of all air dried samples were measured using an Perkin Elmer Spectrum One NTS, FT-NIR Spectrometer, within the range from 700 to 2500 nm. Partial Least Squares (PLS) regression was used to built models to determine soil chemical parameters from the NIR spectra. Two-third of the samples were used as a calibration set and the remaining samples as independent validation test set. The best model was obtained for total nitrogen with a coefficient of determination r=0,91, standard error of calibration SEP=336 mg/kg, and the ratio of the standard variation of the reference data to the SEP, indicating the performance of the calibration, of RPD=2,3. The accuracy of prediction was poor for electrical conductivity. The results obtained clearly indicated that NIRS had the potential to predict some soil components rapidly and without sample preparation.