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.
2017
Sammendrag
Det er ikke registrert sammendrag
Forfattere
P. Schröder B. Beckers S. Daniels F. Gnädinger E. Maestri N. Marmiroli M. Mench R. Millan M.M. Obermeier N. Oustriere Tomas Persson C. Poschenrieder F. Rineau B. Rutkowska T. Schmid W. Szulc N. Witters Arne SæbøSammendrag
The rapid increase of the world population constantly demands more food production from agricultural soils. This causes conflicts, since at the same time strong interest arises on novel bio-based products from agriculture, and new perspectives for rural landscapes with their valuable ecosystem services. Agriculture is in transition to fulfill these demands. In many countries, conventional farming, influenced by post-war food requirements, has largely been transformed into integrated and sustainable farming. However, since it is estimated that agricultural production systems will have to produce food for a global population that might amount to 9.1 billion by 2050 and over 10 billion by the end of the century, we will require an even smarter use of the available land, including fallow and derelict sites. One of the biggest challenges is to reverse non-sustainable management and land degradation. Innovative technologies and principles have to be applied to characterize marginal lands, explore options for remediation and re-establish productivity. With view to the heterogeneity of agricultural lands, it is more than logical to apply specific crop management and production practices according to soil conditions. Cross-fertilizing with conservation agriculture, such a novel approach will provide (1) increased resource use efficiency by producing more with less (ensuring food security), (2) improved product quality, (3) ameliorated nutritional status in food and feed products, (4) increased sustainability, (5) product traceability and (6) minimized negative environmental impacts notably on biodiversity and ecological functions. A sustainable strategy for future agriculture should concentrate on production of food and fodder, before utilizing bulk fractions for emerging bio-based products and convert residual stage products to compost, biochar and bioenergy. The present position paper discusses recent developments to indicate how to unlock the potentials of marginal land.
Sammendrag
Currently, sugar snap peas are harvested manually. In high-cost countries like Norway, such a labour-intensive practise implies particularly large costs for the farmer. Hence, automated alternatives are highly sought after. This project explored a concept for robotic autonomous identification and tracking of sugar snap pea pods. The approach was based on a combination of visible–near infrared reflection measurements and image analysis, along with visual servoing. A proof-of-concept harvesting platform was implemented by mounting a robotic arm with hand-mounted sensors on a mobile unit. The platform was tested under plastic greenhouse conditions on potted plants of the sugar snap pea variety Cascadia using LED-lights and a partial shade. The results showed that it was feasible to differentiate the pods from the surrounding foliage using the light reflection at the spectral range around 970 nm combined with elementary image segmentation and shape modelling methods. The proof-of-concept harvesting platform was tested on 48 representative agricultural environments comprising dense canopy, varying pod sizes, partial occlusions and different working distances. A set of 104 images were analysed during the teleoperation experiment. The true positive detection rate was 93 and 87% for images acquired at long distances and at close distances, respectively. The robot arm achieved a success rate of 54% for autonomous visual servoing to a pre-grasp pose around targeted pods on 22 untouched scenarios. This study shows the potential of developing a prototype robot for semi-automated sugar snap pea harvesting.
Sammendrag
There is a scientific consensus that the future climate change will affect grass and crop dry matter (DM) yields. Such yield changes may entail alterations to farm management practices to fulfill the feed requirements and reduce the farm greenhouse gas (GHG) emissions from dairy farms. While a large number of studies have focused on the impacts of projected climate change on a single farm output (e.g. GHG emissions or economic performance), several attempts have been made to combine bio-economic systems models with GHG accounting frameworks. In this study, we aimed to determine the physical impacts of future climate scenarios on grass and wheat DM yields, and demonstrate the effects such changes in future feed supply may have on farm GHG emissions and decision-making processes. For this purpose, we combined four models: BASGRA and CSM-CERESWheat models for simulating forage grass DM and wheat DM grain yields respectively; HolosNor for estimating the farm GHG emissions; and JORDMOD for calculating the impacts of changes in the climate and management on land use and farm economics. Four locations, with varying climate and soil conditions were included in the study: south-east Norway, south-west Norway, central Norway and northern Norway. Simulations were carried out for baseline (1961–1990) and future (2046–2065) climate conditions (projections based on two global climate models and the Special Report on Emissions Scenarios (SRES) A1B GHG emission scenario), and for production conditions with and without a milk quota. The GHG emissions intensities (kilogram carbon dioxide equivalent: kgCO2e emissions per kg fat and protein corrected milk: FPCM) varied between 0.8 kg and 1.23 kg CO2e (kg FPCM)−1 , with the lowest and highest emissions found in central Norway and south-east Norway, respectively. Emission intensities were generally lower under future compared to baseline conditions due mainly to higher future milk yields and to some extent to higher crop yields. The median seasonal aboveground timothy grass yield varied between 11,000 kg and 16,000 kg DM ha−1 and was higher in all projected future climate conditions than in the baseline. The spring wheat grain DM yields simulated for the same weather conditions within each climate projection varied between 2200 kg and 6800 kg DM ha−1 . Similarly, the farm profitability as expressed by total national land rents varied between 1900 million Norwegian krone (NOK) for median yields under baseline climate conditions up to 3900 million NOK for median yield under future projected climate conditions.
Forfattere
Anne-Grete Roer Hjelkrem Mats Höglind Marcel van Oijen Jürgen Schellberg Thomas Gaiser Frank EwertSammendrag
Proper parameterisation and quantification of model uncertainty are two essential tasks in improvement and assessment of model performance. Bayesian calibration is a method that combines both tasks by quantifying probability distributions for model parameters and outputs. However, the method is rarely applied to complex models because of its high computational demand when used with high-dimensional parameter spaces. We therefore combined Bayesian calibration with sensitivity analysis, using the screening method by Morris (1991), in order to reduce model complexity by fixing parameters to which model output was only weakly sensitive to a nominal value. Further, the robustness of the model with respect to reduction in the number of free parameters were examined according to model discrepancy and output uncertainty. The process-based grassland model BASGRA was examined in the present study on two sites in Norway and in Germany, for two grass species (Phleum pratense and Arrhenatherum elatius). According to this study, a reduction of free model parameters from 66 to 45 was possible. The sensitivity analysis showed that the parameters to be fixed were consistent across sites (which differed in climate and soil conditions), while model calibration had to be performed separately for each combination of site and species. The output uncertainty decreased slightly, but still covered the field observations of aboveground biomass. Considering the training data, the mean square error for both the 66 and the 45 parameter model was dominated by errors in timing (phase shift), whereas no general pattern was found in errors when using the validation data. Stronger model reduction should be avoided, as the error term increased and output uncertainty was underestimated.
Sammendrag
Kystlyngheia på Eiternes opplever ny skjøtselsaktivitet etter en brakkleggingsperiode siste 12 år. Av den grunn ble det gjennomført kartlegging av naturtyper, og tilhørende skjøtselsplan utformet for området. Det ble registrert kystlynghei med svak verdi B, og området som helhet opplever økende trussel i form av tiltagende gjengroing. Det anbefales derfor restaurering med gjeninnførsel av beite, lyngsviing og rydding av trær/busker i kystlyngheia. Dette vil opprettholde den truede naturtypen kystlynghei, samtidig som beiteressursene i lyngheia øker. Eiternes utgjør også en landskapsverdi for regionen i form av gammelt kulturlandskap preget av kystjordbruk.
Sammendrag
På oppdrag fra Nærøy kommune ble det kartlagt viktige naturtyper på det historiske handelsstedet Risværet, og tilhørende skjøtselsplan utformet for videre skjøtsel av området. Følgende øyer ble undersøkt; Risværøy, Kalvøya, Hovøya og Sandøya. Det ble registrert både kystlynghei og naturbeitemark med verdi A. Risværøya innehar kalkrik kystlynghei, noe som er sjeldent i denne regionen. Området som helhet opplever likevel en økende trussel i form av tiltagende gjengroing. Det anbefales derfor restaurering med gjeninnførsel av lyngsviing i kystlyngheia i tillegg til dagens beite. Dette vil opprettholde den truede naturtypen kystlynghei, samtidig som beiteressursene i lyngheia øker. Risværet har også en landskapsverdi for regionen bestående av gammelt kulturlandskap preget av kystjordbruk.
Sammendrag
NIBIO, avdeling kulturlandskap og biomangfold og Norsk Landbruksrådgiving er nå i gang med et prosjekt som skal teste ut forskjellige metoder mot tett mosedekke i artsrik kulturmarkseng. Prosjektet er 3-årig, og har mottatt støtte fra Landbruksdirektoratet, gjennom Klima og miljøprogrammet.
Forfattere
Martin Riis Weisbjerg Hamzah S. Bhatti Margarita Novoa-Garrido Michael Roleda Vibeke LindSammendrag
Det er ikke registrert sammendrag
Forfattere
Steffen Werne Felix Heckendorn Michael Roleda L Baumgartner Eduarda Molina-Alcaide A Drewek Vibeke LindSammendrag
Det er ikke registrert sammendrag