| Records |
| Author |
van Bussel, L.G.J.; Ewert, F.; Zhao, G.; Hoffmann, H.; Enders, A.; Wallach, D.; Asseng, S.; Baigorria, G.A.; Basso, B.; Biernath, C.; Cammarano, D.; Chryssanthacopoulos, J.; Constantin, J.; Elliott, J.; Glotter, M.; Heinlein, F.; Kersebaum, K.-C.; Klein, C.; Nendel, C.; Priesack, E.; Raynal, H.; Romero, C.C.; Rötter, R.P.; Specka, X.; Tao, F. |
| Title |
Spatial sampling of weather data for regional crop yield simulations |
Type |
Journal Article |
| Year |
2016 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
Volume  |
220 |
Issue |
|
Pages |
101-115 |
| Keywords |
Regional crop simulations; Winter wheat; Upscaling; Stratified sampling; Yield estimates; climate-change scenarios; water availability; growth simulation; potential impact; food-production; winter-wheat; model; resolution; systems; soil |
| Abstract |
Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50,100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0168-1923 |
ISBN |
|
Medium |
Article |
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4673 |
| Permanent link to this record |
| |
|
| |
| Author |
Rötter, R.P.; Appiah, M.; Fichtler, E.; Kersebaum, K.C.; Trnka, M.; Hoffmann, M.P. |
| Title |
Linking modelling and experimentation to better capture crop impacts of agroclimatic extremes-A review |
Type |
Journal Article |
| Year |
2018 |
Publication |
Field Crops Research |
Abbreviated Journal |
|
| Volume |
221 |
Issue |
|
Pages |
142-156 |
| Keywords |
ft_macsur; Agroclimatic extremes; Crop model; Heat; Drought; Heavy rain; Anthropogenic Climate-Change; Head-Emergence Frost; Weather Extremes; Wheat Yields; Temperature Variability; Induced Sterility; Food Security; Soil-Moisture; Plant-Growth; Winter-Wheat |
| Abstract |
Climate change implies higher frequency and magnitude of agroclimatic extremes threatening plant production and the provision of other ecosystem services. This review is motivated by a mismatch between advances made regarding deeper understanding of abiotic stress physiology and its incorporation into ecophysiological models in order to more accurately quantifying the impacts of extreme events at crop system or higher aggregation levels. Adverse agroclimatic extremes considered most detrimental to crop production include drought, heat, heavy rains/hail and storm, flooding and frost, and, in particular, combinations of them. Our core question is: How have and could empirical data be exploited to improve the capability of widely used crop simulation models in assessing crop impacts of key agroclimatic extremes for the globally most important grain crops? To date there is no comprehensive review synthesizing available knowledge for a broad range of extremes, grain crops and crop models as a basis for identifying research gaps and prospects. To address these issues, we selected eight major grain crops and performed three systematic reviews using SCOPUS for period 1995-2016. Furthermore, we amended/complemented the reviews manually and performed an in-depth analysis using a sub-sample of papers. Results show that by far the majority of empirical studies (1631 out of 1772) concentrate on the three agroclimatic extremes drought, heat and heavy rain and on the three major staples wheat, maize and rice (1259 out of 1772); the concentration on just a few has increased over time. With respect to modelling studies two model families, i.e. CERES-DSSAT and APSIM, are dearly dominating for wheat and maize; for rice, ORYZA2000 and CERES-Rice predominate and are equally strong. For crops other than maize and wheat the number of studies is small. Empirical and modelling papers don’t differ much in the proportions the various extreme events are dealt with drought and heat stress together account for approx. 80% of the studies. There has been a dramatic increase in the number of papers, especially after 2010. As a way forward, we suggest to have very targeted and well-designed experiments on the specific crop impacts of a given extreme as well as of combinations of them. This in particular refers to extremes addressed with insufficient specificity (e.g. drought) or being under-researched in relation to their economic importance (heavy rains/storm and flooding). Furthermore, we strongly recommend extending research to crops other than wheat, maize and rice. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
|
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5199 |
| Permanent link to this record |
| |
|
| |
| Author |
Mäkinen, H.; Kaseva, J.; Trnka, M.; Balek, J.; Kersebaum, K.C.; Nendel, C.; Gobin, A.; Olesen, J.E.; Bindi, M.; Ferrise, R.; Moriondo, M.; Rodriguez, A.; Ruiz-Ramos, M.; Takáč, J.; Bezák, P.; Ventrella, D.; Ruget, F.; Capellades, G.; Kahiluoto, H. |
| Title |
Sensitivity of European wheat to extreme weather |
Type |
Journal Article |
| Year |
2018 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
222 |
Issue |
|
Pages |
209-217 |
| Keywords |
European wheat; Cultivar; Weather; Extreme; Climate change; Yield response; High-Temperature; Heat-Stress; Use Efficiency; Growth-Stages; Winter-Wheat; Yield; Crop; Barley; Tolerance |
| Abstract |
The frequency and intensity of extreme weather is increasing concomitant with changes in the global climate change. Although wheat is the most important food crop in Europe, there is currently no comprehensive empirical information available regarding the sensitivity of European wheat to extreme weather. In this study, we assessed the sensitivity of European wheat yields to extreme weather related to phenology (sowing, heading) in cultivar trials across Europe (latitudes 37.21 degrees to 61.34 degrees and longitudes- 6.02 degrees to 26.24 degrees) during the period 1991-2014. All the observed agro-climatic extremes (>= 31 degrees C, >= 35 degrees C, or drought around heading; >= 35 degrees C from heading to maturity; excessive rainfall; heavy rainfall and low global radiation) led to marked yield penalties in a selected set of European cultivars, whereas few cultivars were found to with no yield penalty in such conditions. There were no European wheat cultivars that responded positively (+ 10%) to drought after sowing, or frost during winter (- 15 degrees C and – 20 degrees C). Positive responses to extremes were often shown by cultivars associated with specific regions, such as good performance under high temperatures by southern-origin cultivars. Consequently, a major future breeding challenge will be to evaluate the potential of combining such cultivar properties with other properties required under different growing conditions with, for example, long day conditions at higher latitudes, when the intensity and frequency of extremes rapidly increase. |
| Address |
2018-06-05 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0378-4290 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5200 |
| Permanent link to this record |
| |
|
| |
| Author |
Korhonen, P.; Palosuo, T.; Persson, T.; Höglind, M.; Jego, G.; Van Oijen, M.; Gustavsson, A.-M.; Belanger, G.; Virkajärvi, P. |
| Title |
Modelling grass yields in northern climates – a comparison of three growth models for timothy |
Type |
Journal Article |
| Year |
2018 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
224 |
Issue |
|
Pages |
37-47 |
| Keywords |
Forage grass; Model comparison; Timothy; Uncertainty; Yield; Nutritive-Value; Catimo Model; Nitrogen Balances; Simulation; Regrowth; Wheat; Stics; Dynamics; Harvest; Water |
| Abstract |
During the past few years, several studies have compared the performance of crop simulation models to assess the uncertainties in model-based climate change impact assessments and other modelling studies. Many of these studies have concentrated on cereal crops, while fewer model comparisons have been conducted for grasses. We compared the predictions for timothy grass (Phleum pratertse L.) yields for first and second cuts along with the dynamics of above-ground biomass for the grass simulation models BASGRA and CATIMO, and the soil -crop model STICS. The models were calibrated and evaluated using field data from seven sites across Northern Europe and Canada with different climates, soil conditions and management practices. Altogether the models were compared using data on timothy grass from 33 combinations of sites, cultivars and management regimes. Model performances with two calibration approaches, cultivar-specific and generic calibrations, were compared. All the models studied estimated the dynamics of above-ground biomass and the leaf area index satisfactorily, but tended to underestimate the first cut yield. Cultivar-specific calibration resulted in more accurate first cut yield predictions than the generic calibration achieving root mean square errors approximately one third lower for the cultivar-specific calibration. For the second cut, the difference between the calibration methods was small. The results indicate that detailed soil process descriptions improved the overall model performance and the model responses to management, such as nitrogen applications. The results also suggest that taking the genetic variability into account between cultivars of timothy grass also improves the yield estimates. Calibrations using both spring and summer growth data simultaneously revealed that processes determining the growth in these two periods require further attention in model development. |
| Address |
2018-07-12 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0378-4290 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5206 |
| Permanent link to this record |
| |
|
| |
| Author |
Jing, Q.; Bélanger, G.; Baron, V.; Bonesmo, H.; Virkajärvi, P.; Young, D. |
| Title |
Regrowth simulation of the perennial grass timothy |
Type |
Journal Article |
| Year |
2012 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
| Volume |
232 |
Issue |
|
Pages |
64-77 |
| Keywords |
biomass; carbohydrate; leaf area index; n uptake; reserve-dependent growth; temperature; nutritive-value; carbohydrate reserves; phleum-pratense; catimo model; leaf-area; nitrogen-fertilization; spring harvest; meadow fescue; tall fescue; growth |
| Abstract |
Several process-based models for simulating the growth of perennial grasses have been developed but few include the simulation of regrowth. The model CATIMO simulates the primary growth of timothy (Phleum pratense L), an important perennial forage grass species in northern regions of Europe and North America. Our objective was to further develop the model CATIMO to simulate timothy regrowth using the concept of reserve-dependent growth. The performance of this modified CATIMO model in simulating leaf area index (LAI), biomass dry matter (DM) yield, and N uptake of regrowth was assessed with data from four independent field experiments in Norway, Finland, and western and eastern Canada using an approach that combines graphical comparison and statistical analysis. Biomass DM yield and N uptake of regrowth were predicted at the same accuracy as primary growth with linear regression coefficients of determination between measured and simulated values greater than 0.79, model simulation efficiencies greater than 0.78, and normalized root mean square errors (14-30% for biomass and 24-34% for N uptake) comparable with the coefficients of variation of measured data (1-21% for biomass and 1-25% for N uptake). The model satisfactorily simulated the regrowth LAI but only up to a value of about 4.0. The modified CATIMO model with its capacity to simulate regrowth provides a framework to simulate perennial grasses with multiple harvests, and to explore management options for sustainable grass production under different environmental conditions. Crown Copyright (C) 2012 Published by Elsevier B.V. All rights reserved. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0304-3800 |
ISBN |
|
Medium |
Article |
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CropM, LiveM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4473 |
| Permanent link to this record |
