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.
2017
Abstract
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.
Abstract
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.
Authors
Anne-Grete Roer Hjelkrem Mats Höglind Marcel van Oijen Jürgen Schellberg Thomas Gaiser Frank EwertAbstract
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.
Abstract
No abstract has been registered
Authors
Steffen Werne Felix Heckendorn Michael Roleda L Baumgartner Eduarda Molina-Alcaide A Drewek Vibeke LindAbstract
No abstract has been registered
Authors
Eduarda Molina-Alcaide Maria Dolores Carro Michael Roleda Martin Riis Weisbjerg Vibeke Lind Margarita Novoa-GarridoAbstract
Seaweeds have potentials as alternative feed for ruminants, but there is a limited knowledge on their nutritive value. Seven seaweed species collected along the coast above the Arctic circle of Norway, both in spring and autumn, were assessed for nutrients and total polyphenols (TEP) content, gas production kinetics and in vitro rumen fermentation in batch cultures of ruminal microorganisms. The seaweeds were three red species (Mastocarpus stellatus, Palmaria palmata and Porphyra sp.), three brown species (Alaria esculenta, Laminaria digitata and Pelvetia canaliculata) and one green species (Acrosiphonia sp.). Additionally, the abundance and diversity of total bacteria, protozoa and archaea in the cultures with the three red seaweeds collected in spring were analyzed by quantitative PCR and PCR-DGGE, respectively. The crude protein (CP) content varied widely. Pelvetia had the greatest (P < 0.001) ether extract (EE) content. Non-structural carbohydrates (NSC) content varied from 135 to 541 g/kg DM with brown seaweeds having the greatest values. Ash and CP contents were higher in spring than in autumn (P = 0.020 and 0.003, respectively), whereas concentrations of EE and NSC were not affected by collecting season (P = 0.208–0.341). The TEP values ranged from 1.46 to 50.3 mg/g dry matter (DM), and differed (P < 0.001) among seaweed species and collecting season, being greater in autumn than in spring. The DM effective degradability (DMED), estimated from gas production parameters for a rumen passage rate of 3.0% per h, ranged from 424 to 652 g/kg, the highest values were recorded for Mastocarpus stellatus and Porphyra sp. The lowest DMED values were registered for Pelvetia canaliculata and Acrosiphonia sp. In 24-h incubations (500 mg DM), Palmaria palmata had the highest (P < 0.05) volatile fatty acids (VFA) and methane production (4.34 and 0.761 mmol, respectively) and the lowest (P < 0.05) final pH values and acetate to propionate ratios (6.57 and 2.34, respectively). There were no differences (P > 0.05) among the other seaweeds in VFA production, but Porphyra sp. had the second highest methane production (P < 0.05; 0.491 mmol) compared with the other seaweeds (0.361 mmol; averaged value). The methane/total VFA ratio was not affected (P > 0.05) by either seaweed species or the collection season. Higher final pH (P < 0.05) and lower (P < 0.05) methane and VFA production, ammonia-N concentrations and DMED values were promoted by the fermentation of seaweed collected in autumn compared with those from spring. Among the red seaweeds, there were no species-specific differences (P > 0.05) in the abundance or the diversity of total bacteria, protozoa and archaea. In the PCR-DGGE analysis, samples were separated by the incubation run for all microbial populations analyzed, but not by seaweed species. The results indicate that seaweed species differ markedly in their in vitro rumen degradation, and that samples collected in autumn had lower rumen degradability than those collected in spring.
Authors
Laura Jaakola Laura Zoratti Nga Nguyenquynh Lara Giongo Katja Karppinen Anne Linn Hykkerud Eivind Uleberg Inger Martinussen Hely HäggmanAbstract
No abstract has been registered
Authors
Sigridur Dalmannsdottir Marit Jørgensen Marcin Rapacz Liv Østrem Arild Larsen Rolf Rødven Odd Arne RognliAbstract
The effect of variable autumn temperatures in combination with decreasing irradiance and daylength on photosynthesis, growth cessation and freezing tolerance was investigated in northern- and southern-adapted populations of perennial ryegrass (Lolium perenne) and timothy (Phleum pratense) intended for use in regions at northern high latitudes. Plants were subjected to three different acclimation temperatures; 12, 6 and 9/3°C (day/night) for 4 weeks, followed by 1 week of cold acclimation at 2°C under natural light conditions. This experimental setup was repeated at three different periods during autumn with decreasing sums of irradiance and daylengths. Photoacclimation, leaf elongation and freezing tolerance were studied. The results showed that plants cold acclimated during the period with lowest irradiance and shortest day had lowest freezing tolerance, lowest photosynthetic activity, longest leaves and least biomass production. Higher acclimation temperature (12°C) resulted in lower freezing tolerance, lower photosynthetic activity, faster leaf elongation rate and higher biomass compared with the other temperatures. Photochemical mechanisms were predominant in photoacclimation. The northern-adapted populations had a better freezing tolerance than the southern-adapted except when grown during the late autumn period and at the highest temperature; then there were no differences between the populations. Our results indicate that the projected climate change in the north may reduce freezing tolerance in grasses as acclimation will take place at higher temperatures and shorter daylengths with lower irradiance.
Authors
Stef Bokhorst Laura Jaakola Katja Karppinen Guro Kristine Edvinsen Hanne Mæhre Jarle W. BjerkeAbstract
Main conclusion Evergreen plants are more vulnerable than grasses and birch to snow and temperature variability in the sub-Arctic. Most Arctic climate impact studies focus on single factors, such as summer warming, while ecosystems are exposed to changes in all seasons. Through a combination of field and laboratory manipulations, we compared physiological and growth responses of dominant sub-Arctic plant types to midwinter warming events (6 °C for 7 days) in combination with freezing, simulated snow thaw and nitrogen additions. We aimed to identify if different plant types showed consistent physiological, cellular, growth and mortality responses to these abiotic stressors. Evergreen dwarf shrubs and tree seedlings showed higher mortality (40–100%) following extreme winter warming events than Betula pubescens tree seedlings and grasses (0–27%). All species had growth reductions following exposure to − 20 °C, but not all species suffered from − 10 °C irrespective of other treatments. Winter warming followed by − 20 °C resulted in the greatest mortality and was strongest among evergreen plants. Snow removal reduced the biomass for most species and this was exacerbated by subsequent freezing. Nitrogen increased the growth of B. pubescens and grasses, but not the evergreens, and interaction effects with the warming, freezing and snow treatments were minor and few. Physiological activity during the winter warming and freezing treatments was inconsistent with growth and mortality rates across the plants types. However, changes in the membrane fatty acids were associated with reduced mortality of grasses. Sub-Arctic plant communities may become dominated by grasses and deciduous plants if winter snowpack diminishes and plants are exposed to greater temperature variability in the near future. C-repeat binding factor · Fatty acids · Frost · Grass · Multiple stresses · Shrub · Snow
Authors
Mohammad Ramin Marcia De Oliveira Franco Michael Roleda Inga Marie Aasen Mårten Hetta Håvard SteinshamnAbstract
No abstract has been registered