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Øygarden, L.; Höglind, M.; Harstad, M.; Hoveid, Ø. |
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Title |
Modelling European Agriculture with Climate change for food security |
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2013 |
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CropM |
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Bioforsk conference 2013. Proceedings in; Bioforsk Fokus Vol. 8 Nr 2. 2013. pp 372-374. Editors; Erling Fløistad & Morten Gunther. 390 pp. ISBN 978-82-17-00998-6., 2013-02-06 to 2013-02-07 |
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MA @ admin @ |
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2689 |
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Virkajärvi, P.; Korhonen, P.; Bellocchi, G.; Curnel, Y.; Wu, L.; Jégo, G.; Persson, T.; Höglind, M.; Van Oijen, M.; Gustavsson, A.-M.; Kipling, R.P. |
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Title |
Modelling responses of forages to climate change with a focus on nutritive value |
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Journal Article |
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2016 |
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Advances in Animal Biosciences |
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Advances in Animal Biosciences |
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7 |
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03 |
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227-228 |
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2040-4700 |
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LiveM, ft_macsur |
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MA @ admin @ |
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4876 |
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Van Oijen, M.; Höglind, M. |
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Title |
Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design |
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Journal Article |
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2016 |
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Euphytica |
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Euphytica |
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207 |
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3 |
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627-643 |
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BASGRA; cold tolerance; genotype-environment interaction; plant breeding; process-based modelling; yield stability; grassland productivity; timothy regrowth; climate-change; water-deficit; forest models; late blight; leaf-area; calibration; growth; tolerance |
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Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway. |
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2016-10-31 |
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0014-2336 |
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CropM, ft_macsur |
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MA @ admin @ |
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4820 |
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Persson, T.; Kværnø, S.; Höglind, M. |
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Title |
Impact of soil properties regionalization procedures on regional timothy dry matter yield and variability in southeastern Norway |
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2014 |
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CropM |
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MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12 |
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MA @ admin @ |
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2718 |
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Persson, T.; Kværnø, S.; Höglind, M. |
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Title |
Impact of soil type extrapolation on timothy grass yield under baseline and future climate conditions in southeastern Norway |
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2015 |
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Climate Research |
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Clim. Res. |
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65 |
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71-86 |
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climate change scenarios; crop modelling; forage grass; lingra; soil properties; spatial variability; phleum pretense; poaceae; simulation-model; nutritive-value; systems simulation; catimo model; crop models; growth; nitrogen; scale; productivity; regrowth |
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Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Ostfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input. |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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MA @ admin @ |
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4674 |
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