Audun Korsaeth - Academia.edu (original) (raw)

Papers by Audun Korsaeth

The aim of this study was to compare production and policy risk of organic, integrated and conven... more The aim of this study was to compare production and policy risk of organic, integrated and conventional cropping systems in Norway. Experimental cropping system data (1991-1999) from eastern Norway were combined with budgeted data. Empirical distributions of total farm income for different cropping systems were estimated with a simulation model that uses a multivariate kernel density function to smooth the limited experimental data. Stochastic efficiency with respect to a function (SERF) was used to rank the cropping systems for farmers with various risk aversion levels. The results show that the organic system had the greatest net farm income variability, but the existing payment system and organic price premiums makes it the most economically viable alternative.

Organic Crop Production – Ambitions and Limitations, 2008

In this overview, a synthesis of the first 10 years of the Apelsvoll cropping system experiment, ... more In this overview, a synthesis of the first 10 years of the Apelsvoll cropping system experiment, located in southeast Norway, is given. All major flows of N, P and K in six different cropping systems, each covering 0.18 ha of separately tile-drained plots, were either measured or estimated. The effects of the cropping system on the soil nutrient pools (total-N,

Soil Biology & Biochemistry, 2007

Mechanistic, multi-compartment decomposition models require that carbon (C) and nitrogen (N) in p... more Mechanistic, multi-compartment decomposition models require that carbon (C) and nitrogen (N) in plant material be distributed among pools of different degradability. For this purpose, measured concentrations of C and N in fractions obtained through stepwise chemical digestion ...

Soil Biology and Biochemistry, 2002

Soil Biology and Biochemistry, 2001

Precision Agriculture, 2006

Zeitschrift für Pflanzenernährung und Bodenkunde, 1997

Journal of Near Infrared Spectroscopy, 2013

ABSTRACT Validation of reflectance-based prediction models for plant properties is often performe... more ABSTRACT Validation of reflectance-based prediction models for plant properties is often performed on just one or two years of data. Hence, we aimed to perform a more comprehensive study regarding the validation of prediction models for grain yield and protein concentration. A FieldSpec3 portable field spectroradiometer was used to measure canopy reflectance in spring wheat. Spectral reflectance data were collected from three different experimental locations in up to four different years during the period 2007-2010, so that seven unique site years were included, comprising, altogether, 976 individual plots. Several datasets had moderate to severe lodging, which had a markedly negative influence on the prediction results. To correct for this problem, a classification model for the classes "lodging" and "standing crop" was calibrated from the spectral data. The model gave a total classification accuracy of 98.3%. Prediction models for grain yield and grain protein concentration were computed by means of the recent statistical method powered partial least squares (PPLS). Models were calibrated and validated on several combinations of the spectral datasets in order to reveal spatial and temporal effects on the prediction performance. The model performance generally increased with increasing variation in the calibration data, both in time (i.e. more years included) and space (i.e. more sites included). The best model for grain yield explained 94% [root mean square error of prediction (RMSEP)=156 g m(-2)] of the variance and the predictions of grain protein concentration explained 67% [RMSEP=1.51 g dry matter (DM) 100 g(-1)] of the variance. The performance of the grain yield PPLS models was compared with that of models based on some widely used vegetation indices [normalised difference vegetation index (NDVI), modified soil adjusted vegetation index (MSAVI), red edge inflection point (REIP) and d-chl-ab]. The explained variance of the models based on vegetation indices did not exceed 55%, indicating that these models were inferior to full spectrum models. This study shows that one or two years of spectral measurement are insufficient for building fully operational models for cereal property predictions.

$Research paper thumbnail of Near infrared reflectance spectroscopy for quantification of crop residue, green manure and catch crop C and N fractions governing decomposition dynamics in soil$

Journal of Near Infrared Spectroscopy, 2004

ABSTRACT For environmental, as well as agronomic reasons, the turnover of carbon (C) and nitrogen... more ABSTRACT For environmental, as well as agronomic reasons, the turnover of carbon (C) and nitrogen (N) from crop residues, catch crops and green manures incorporated into agricultural soils has attracted much attention. It has previously been found that the C and N content in fractions from stepwise chemical digestion of plant materials constitutes an adequate basis for describing a priori the degradability of both C and N in soil. However, the analyses involved are costly and, therefore, unlikely to be used routinely. The aim of the present work was to develop near infrared (NIR) calibrations for C and N fractions governing decomposition dynamics. Within the five Nordic countries, we sampled a uniquely broad-ranged collection representing most of the fresh and mature plant materials that may be incorporated into agricultural soils from temperate regions. The specific objectives of the current study were (1) to produce NIR calibrations with data on C and N in fractions obtained by stepwise chemical digestion (SCD); (2) to validate these calibrations on independent plant samples and (3) to compare the precision and robustness of these broad-based calibrations with calibrations derived from materials within a narrower quality range. According to an internal validation set, plant N, soluble N, cellulose C, holocellulose (hemicellulose + cellulose) C, soluble C and neutral detergent fibre (NDF) dry matter were the parameters best predicted (r2=0.97, 0.95, 0.94, 0.91, 0.90 and 0.94, respectively). However, the calibrations for soluble C and NDF were regarded as unstable, as their validation statistics were substantially poorer than the calibration statistics. The calibrations for all structural N fractions and lignin C were considered poor (r2=0.47-0. 70). By comparing our broad-based calibrations for plant N and NDF with similar calibrations for a sample set representing a commercial forage database, it was evident that the broad-based calibrations predicted a narrow-based sample set better than vice versa. For plant N, the residual mean squared error of prediction (RMSEP), when testing the broad-based calibration with the narrow-based validation set, was substantially smaller than the RMSEP obtained when validating the broad-based calibration internally (1.8 vs 2.7 mg N g -1 dry matter). Overall, the calibrations that performed best were those concerning the parameters most strongly influencing C and N mineralisation from plant materials.

Journal of Arachnology, 2013

Nutrient Cycling in Agroecosystems, 2003

Nitrate leaching is often low from grasslands, primarily due to their long period of N uptake com... more Nitrate leaching is often low from grasslands, primarily due to their long period of N uptake compared to arable crops. In the present paper we explore the combined effects of N input regime, soil type and climatic conditions through a combination of field lysimeter studies and simulation modeling of temporary grassland. A lysimeter consisting of eight 10 × 4 ×

Agriculture, Ecosystems & Environment, 2008

Agriculture, Ecosystems & Environment, 2000

Agriculture, Ecosystems & Environment, 2002

Agricultural Systems, 2012

ABSTRACT This study assesses the environmental impacts from production of 1 kg barley, oat and sp... more ABSTRACT This study assesses the environmental impacts from production of 1 kg barley, oat and spring wheat, in central southeast Norway by means of life cycle assessment. The results were given for twelve impact categories, selected based on relevance to the system. These categories are climate change, fossil depletion, freshwater ecotoxicity, freshwater eutrophication, human toxicity, marine ecotoxicity, marine eutrophication, ozone depletion, particulate matter formation, photochemical oxidant formation, terrestrial acidification and terrestrial ecotoxicity. The assessment covers processes from cradle to farm gate, including all farm activities related to grain cultivation, as well as the production and acquisition of machinery, equipments and buildings, diesel and oil, fertilizer, lime, seeds and pesticides.In order to reveal the importance of system boundaries, factors that are included in this study and often excluded in other studies, such as machinery manufacturing, buildings, pesticide production and use, humus mineralization and NOX loss from use of mineral fertilizer were systematically individually omitted. The sensitivity of the LCA results to several selected parameters governing greenhouse gas emissions and climate change (CC) was evaluated by varying the parameters ±50% of the default value.The assessment gave a CC impact of 0.79, 0.77 and 0.74 kg CO2-eq for production of 1 kg barley, oat and spring wheat, respectively. The choice of system boundaries were found to have great impact on the results, and CC impact was reduced by more than 40% when factors that are not commonly reported in literature were excluded. This clearly demonstrates the need of comprehensive documentation of system boundaries in order to perform meaningful comparisons of environmental impact caused by grain production under different conditions.The sensitivity analysis revealed that most of the impact categories were not particularly sensitive to the parameters selected. A 50% change in the emission factor for N2O emissions from N inputs had highest effect on CC with 11–13%. The highest overall impacts were found for the fraction of mineral fertilizer volatilized as NH3 and NOX, with 32–53% change in photochemical oxidant and particular matter formation, and terrestrial acidification impact categories.

Agricultural Systems, 2014

Acta Agriculturae Scandinavica, Section B - Plant Soil Science, 2006