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Author |
Höglind, M.; Van Oijen, M.; Cameron, D.; Persson, T. |
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Title |
Process-based simulation of growth and overwintering of grassland using the BASGRA model |
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Journal Article |
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Year |
2016 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
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Volume |
335 |
Issue |
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Pages |
1-15 |
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Keywords |
Cold hardening; Frost injury; Phleum pratense L.; Process-based; modelling; Winter survival; Yield; low-temperature tolerance; perennial forage crops; dry-matter; production; climate-change; nutritive-value; snow-cover; bayesian; calibration; timothy regrowth; phleum-pratense; lolium-perenne |
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Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers and plant breeders in addressing the challenges of climate change by simulating alternative roads of adaptation. They can also provide management decision support under current conditions. A drawback of existing grass models is that they do not take into account the effect of winter stresses, limiting their use for full-year simulations in areas where winter survival is a key factor for yield security. Here, we present a novel full-year PBM for grassland named BASGRA. It was developed by combining the LINGRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winter processes. We present the model and show how it was parameterized for timothy (Phleum pratense L.), the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRA simulates the processes taking place in the sward during the transition from summer to winter, including growth cessation and gradual cold hardening, and functions for simulating plant injury due to low temperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data from five different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudes from 59 degrees to 70 degrees N) and soil conditions. The total dataset included 11 variables, notably above-ground dry matter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used in the calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector from the single, Bayesian calibration, nearly all measured variables were simulated to an overall normalized root mean squared error (NRMSE) <0.5. For many site x experiment combinations, NRMSE was <0.3. The temporal dynamics were captured well for most variables, as evaluated by comparing simulated time courses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robust model, allowing for simulation of growth and several important underlying processes with acceptable accuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be tested further using independent data from a wide range of growing conditions. Finally we show an example of application of the model, comparing overwintering risks in two climatically different sites, and discuss future model applications. Further development work should include improved simulation of the dynamics of C reserves, and validation of winter tiller dynamics against independent data. (C) 2016 Elsevier B.V. All rights reserved. |
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2016-07-28 |
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0304-3800 |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
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4764 |
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Humblot, P.; Jayet, P.A.; Clerino, P.; Leconte-Demarsy, D.; Szopa, S.; Castell, J.F. |
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Title |
Assessment of ozone impacts on farming systems: a bio-economic modeling approach applied to the widely diverse French case |
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Journal Article |
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Year |
2013 |
Publication |
Ecological Economics |
Abbreviated Journal |
Ecol. Econ. |
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85 |
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Pages |
50-58 |
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Keywords |
ozone; bio-economic modeling; agricultural production; land use; greenhouse gas; carbon sequestration; abatement costs; climate-change; crops; agriculture; eu; emissions; benefits; level |
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Abstract |
As a result of anthropogenic activities, ozone is produced in the surface atmosphere, causing direct damage to plants and reducing crop yields. By combining a biophysical crop model with an economic supply model we were able to predict and quantify this effect at a fine spatial resolution. We applied our approach to the very varied French case and showed that ozone has significant productivity and land-use effects. A comparison of moderate and high ozone scenarios for 2030 shows that wheat production may decrease by more than 30% and barley production may increase by more than 14% as surface ozone concentration increases. These variations are due to the direct effect of ozone on yields as well as to modifications in land use caused by a shift toward more ozone-resistant crops: our study predicts a 16% increase in the barley-growing area and an equal decrease in the wheat-growing area. Moreover, mean agricultural gross margin losses can go as high as 2.5% depending on the ozone scenario, and can reach 7% in some particularly affected regions. A rise in ozone concentration was also associated with a reduction of agricultural greenhouse gas emissions of about 2%, as a result of decreased use of nitrogen fertilizers. One noteworthy result was that major impacts, including changes in land use, do not necessarily occur in ozone high concentration zones, and may strongly depend on farm systems and their adaptation capability. Our study suggests that policy makers should view ozone pollution as a major potential threat to agricultural yields. (C) 2012 Elsevier B.V. All rights reserved. |
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0921-8009 |
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TradeM |
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MA @ admin @ |
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4604 |
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Author |
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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Year |
2016 |
Publication |
Euphytica |
Abbreviated Journal |
Euphytica |
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Volume |
207 |
Issue |
3 |
Pages |
627-643 |
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Keywords |
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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Call Number |
MA @ admin @ |
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4820 |
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Ventrella, D.; Giglio, L.; Charfeddine, M.; Dalla Marta, A. |
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Title |
Consumptive use of green and blue water for winter durum wheat cultivated in Southern Italy |
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Journal Article |
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Year |
2015 |
Publication |
Italian Journal of Agrometeorology |
Abbreviated Journal |
Italian Journal of Agrometeorology |
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20 |
Issue |
1 |
Pages |
33-44 |
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Keywords |
irrigation; water productivity; model simulation; climate change; climate-change scenarios; air co2 enrichment; impact; footprint; irrigation; simulation; yield; agriculture; variability; resources |
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In this study at the regional scale, the model DSSAT CERES-Wheat was applied in order to simulate the cultivation of winter durum wheat (WW) and to estimate the green water (GW) and the blue water (BW) through a dual-step approach (with and without supplemental irrigation). The model simulation covered a period of 30 years for three scenarios including a reference period and two future scenarios based on forecasted global average temperature increase of 2 and 5 degrees C. The GW and BW contribution for evapo transpiration requirement is presented and analyzed on a distributed scale related to the Puglia region (Southern Italy) characterized by high evaporative demand of the atmosphere. The GW component was dominant compared to BW, covering almost 90% of the ETc of WW Under a Baseline scenario the weight BW was 11%, slightly increased in the future scenarios. GW appeared dependent on the spatial and temporal distribution of rainfall during the crop cycle, and to the hydraulic characteristics of soil for each calculation unit. After considering the effects of climate change on irrigation requirement of WW we carried out an example of analysis in order to verify the economic benefit of supplemental irrigation for WW cultivation. The probability that irrigation generates a negative or zero income ranged between 55 and 60% and climate change did not impact the profitability of irrigation for WW as simulated for the economic and agro-pedoclimatic conditions of Puglia region considered in this study. |
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MA @ admin @ |
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4653 |
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Foyer, C.H.; Siddique, K.H.M.; Tai, A.P.K.; Anders, S.; Fodor, N.; Wong, F.-L.; Ludidi, N.; Chapman, M.A.; Ferguson, B.J.; Considine, M.J.; Zabel, F.; Prasad, P.V.V.; Varshney, R.K.; Nguyen, H.T.; Lam, H.-M. |
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Modelling predicts that soybean is poised to dominate crop production across Africa |
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Journal Article |
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Year |
2019 |
Publication |
Plant Cell and Environment |
Abbreviated Journal |
Plant Cell Environ. |
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42 |
Issue |
1 |
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373-385 |
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Climate-Change; Food Security; Sustainable Intensification; Smallholder; Farmers; Nitrogen-Fixation; Yield; Adaptation; Diversity; Impact; CO2 |
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The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume-based farming is particularly important in Africa, where small-scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land-use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful “soybean bonanza” across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production. |
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2019-01-10 |
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0140-7791 |
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MA @ admin @ |
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5215 |
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