| Records |
| Author |
Angulo, C.; Gaiser, T.; Rötter, R.P.; Børgesen, C.D.; Hlavinka, P.; Trnka, M.; Ewert, F. |
| Title |
‘Fingerprints’ of four crop models as affected by soil input data aggregation |
Type |
Journal Article |
| Year |
2014 |
Publication  |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
61 |
Issue |
|
Pages |
35-48 |
| Keywords |
crop model; soil data; spatial resolution; yield distribution; aggregation; us great-plains; climate-change; integrated assessment; simulating wheat; yields; scale; productivity; uncertainty; variability; responses |
| Abstract |
• Systematic analysis of the influence of spatial soil data resolution on simulated regional yields and total growing season evapotranspiration. • The responses of four crop models of different complexity are compared. • Differences between models are larger than the effect of the chosen spatial soil data resolution. • Low influence of soil data resolution due to: high precipitation amount, methods for calculating water retention and method of data aggregation. The spatial variability of soil properties is an important driver of yield variability at both field and regional scale. Thus, when using crop growth simulation models, the choice of spatial resolution of soil input data might be key in order to accurately reproduce observed yield variability. In this study we used four crop models (SIMPLACE<LINTUL-SLIM>, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptake and drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically) contrasting regions of the federal state of North-Rhine-Westphalia (Germany) for the period from 1995 to 2008. Three spatial resolutions of soil input data were taken into consideration, corresponding to the following map scales: 1:50 000, 1:300 000 and 1:1 000 000. The four crop models were run for water-limited production conditions and model results were evaluated in the form of frequency distributions, depicted by bean-plots. In both regions, soil data aggregation had very small influence on the shape and range of frequency distributions of simulated yield and simulated total growing season evapotranspiration for all models. Further analysis revealed that the small influence of spatial resolution of soil input data might be related to: (a) the high precipitation amount in the region which partly masked differences in soil characteristics for water holding capacity, (b) the loss of variability in hydraulic soil properties due to the methods applied to calculate water retention properties of the used soil profiles, and (c) the method of soil data aggregation. No characteristic “fingerprint” between sites, years and resolutions could be found for any of the models. Our results support earlier recommendation to evaluate model results on the basis of frequency distributions since these offer quick and better insight into the distribution of simulation results as compared to summary statistics only. Finally, our results support conclusions from other studies about the usefulness of considering a multi-model approach to quantify the uncertainty in simulated yields introduced by the crop growth simulation approach when exploring the effects of scaling for regional yield impact assessments. |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1161-0301 |
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Article |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4511 |
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| Author |
Savary, S.; Jouanin, C.; Félix, I.; Gourdain, E.; Piraux, F.; Brun, F.; Willocquet, L. |
| Title |
Assessing plant health in a network of experiments on hardy winter wheat varieties in France: patterns of disease-climate associations |
Type |
Journal Article |
| Year |
2016 |
Publication |
European Journal of Plant Pathology |
Abbreviated Journal |
Eur. J. Plant Pathol. |
| Volume |
146 |
Issue |
|
Pages |
741-755 |
| Keywords |
Puccinia triticina; Puccinia striiformis; Fusarium graminearum; Fusarium culmorum; Fusarium avenaceum; Blumeria graminis; Zymoseptoria tritici; Categorical data; Risk factor; Multiple pathosystem; Correspondence analysis; Logistic regression |
| Abstract |
A data set generated by a multi-year (2003–2010) and multi-site network of experiments on winter wheat varieties grown at different levels of crop management is analysed in order to assess the importance of climate on the variability of wheat health. Wheat health is represented by the multiple pathosystem involving five components: leaf rust, yellow rust, fusarium head blight, powdery mildew, and septoria tritici blotch. An overall framework of associations between multiple diseases and climate variables is developed. This framework involves disease levels in a binary form (i.e. epidemic vs. non-epidemic) and synthesis variables accounting for climate over spring and early summer. The multiple disease-climate pattern of associations of this framework conforms to disease-specific knowledge of climate effects on the components of the pathosystem. It also concurs with a (climate-based) risk factor approach to wheat diseases. This report emphasizes the value of large scale data in crop health assessment and the usefulness of a risk factor approach for both tactical and strategic decisions for crop health management. |
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Place of Publication |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0929-1873 1573-8469 |
ISBN |
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Medium |
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| Area |
CropM |
Expedition |
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Conference |
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| Notes |
CropMwp;wos; ftnot_macsur; |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4755 |
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| Author |
Stefańczyk, E.; Sobkowiak, S.; Brylińska, M.; Śliwka, J. |
| Title |
Diversity of Fusarium spp. associated with dry rot of potato tubers in Poland |
Type |
Journal Article |
| Year |
2016 |
Publication |
European Journal of Plant Pathology |
Abbreviated Journal |
Eur. J. Plant Pathol. |
| Volume |
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Issue |
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Pages |
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| Keywords |
ITS; mycotoxin; pathogenicity; Solanum tuberosum; tef-1α; β-tubulin; sequence data; Trichothecenes; identification; fungus; pathogenicity; temperature; sensitivity; zearalenone; strains; disease |
| Abstract |
Fusarium spp. belong to the division Ascomycota and cause important plant diseases; these fungi may contaminate food products with mycotoxins, endangering human and animal health. Several Fusarium spp. have been associated with potato dry rot. The most frequent and devastating of these species are F. sambucinum, F. solani and F. oxysporum, depending on the geographic location and the season. Samples of potato tubers with dry rot symptoms were collected, and their putative fungal isolates were identified as Fusarium species using partial nucleotide sequences of the internal transcribed spacer, translation elongation factor 1-α and β-tubulin genes. Among 149 isolates, 12 species were identified. F. oxysporum was the most frequent (45 % of the isolates), followed by F. avenaceum (12.1 %), F. solani (10.7 %) and F. sambucinum (7.4 %). Phylogenetic analyses confirmed the species identifications and revealed a high diversity of F. solani and a low diversity of F. oxysporum. Potential producers of zearalenone and trichothecenes were identified within the obtained isolates using PCR markers. Isolates that were pathogenic to potatoes in laboratory tests were found in four species: F. sambucinum, F. avenaceum, F. culmorum, and F. graminearum. The effects of increased temperature and mixed inoculum on the pathogenicities of chosen species were evaluated. This study adds 434 potato-derived Fusarium sequences to the NCBI GenBank database and demonstrates that the list of Fusarium species and mycotoxins present in potato tubers may be richer than previously believed, regardless of whether these species cause dry rot or live as saprophytes. |
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English |
Summary Language |
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Original Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0929-1873 1573-8469 |
ISBN |
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Article |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4721 |
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| Author |
Rötter, R.P.; Palosuo, T.; Kersebaum, K.C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Nendel, C.; Olesen, J.E.; Patil, R.H.; Ruget, F.; Takác, J.; Trnka, M. |
| Title |
Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models |
Type |
Journal Article |
| Year |
2012 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
133 |
Issue |
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Pages |
23-36 |
| Keywords |
climate; crop growth simulation; model comparison; spring barley; yield variability; uncertainty; change impacts; nitrogen dynamics; high-temperature; soil-moisture; elevated co2; ceres-wheat; data set; growth; drought; sensitivity |
| Abstract |
In this study, the performance of nine widely used and accessible crop growth simulation models (APES-ACE, CROPSYST, DAISY, DSSAT-CERES, FASSET, HERMES, MONICA, STICS and WOFOST) was compared during 44 growing seasons of spring barley (Hordeum vulgare L) at seven sites in Northern and Central Europe. The aims of this model comparison were to examine how different process-based crop models perform at multiple sites across Europe when applied with minimal information for model calibration of spring barley at field scale, whether individual models perform better than the multi-model mean, and what the uncertainty ranges are in simulated grain yields. The reasons for differences among the models and how results for barley compare to winter wheat are discussed. Regarding yield estimation, best performing based on the root mean square error (RMSE) were models HERMES, MONICA and WOFOST with lowest values of 1124, 1282 and 1325 (kg ha(-1)), respectively. Applying the index of agreement (IA), models WOFOST, DAISY and HERMES scored best having highest values (0.632, 0.631 and 0.585, respectively). Most models systematically underestimated yields, whereby CROPSYST showed the highest deviation as indicated by the mean bias error (MBE) (-1159 kg ha(-1)). While the wide range of simulated yields across all sites and years shows the high uncertainties in model estimates with only restricted calibration, mean predictions from the nine models agreed well with observations. Results of this paper also show that models that were more accurate in predicting phenology were not necessarily the ones better estimating grain yields. Total above-ground biomass estimates often did not follow the patterns of grain yield estimates and, thus, harvest indices were also different. Estimates of soil moisture dynamics varied greatly. In comparison, even though the growing cycle for winter wheat is several months longer than for spring barley, using RMSE and IA as indicators, models performed slightly, but not significantly, better in predicting wheat yields. Errors in reproducing crop phenology were similar, which in conjunction with the shorter growth cycle of barley has higher effects on accuracy in yield prediction. (C) 2012 Elsevier B.V. All rights reserved. |
| Address |
2016-10-31 |
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Place of Publication |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0378-4290 |
ISBN |
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Article |
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Expedition |
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Conference |
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| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4803 |
| Permanent link to this record |
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| Author |
Rötter, R.P.; Palosuo, T.; Kersebaum, K.-C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Olesen, J.E.; Takáč, J.; Trnka, M. |
| Title |
Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models |
Type |
Journal Article |
| Year |
2012 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
133 |
Issue |
|
Pages |
23-36 |
| Keywords |
Climate; Crop growth simulation; Model comparison; Spring barley; Yield variability; Uncertainty; change impacts; nitrogen dynamics; high-temperature; soil-moisture; elevated co2; ceres-wheat; data set; growth; drought; sensitivity |
| Abstract |
► We compared nine crop simulation models for spring barley at seven sites in Europe. ► Applying crop models with restricted calibration leads to high uncertainties. ► Multi-crop model mean yield estimates were in good agreement with observations. ► The degree of uncertainty for simulated grain yield of barley was similar to winter wheat. ► We need more suitable data enabling us to verify different processes in the models. In this study, the performance of nine widely used and accessible crop growth simulation models (APES-ACE, CROPSYST, DAISY, DSSAT-CERES, FASSET, HERMES, MONICA, STICS and WOFOST) was compared during 44 growing seasons of spring barley (Hordeum vulgare L) at seven sites in Northern and Central Europe. The aims of this model comparison were to examine how different process-based crop models perform at multiple sites across Europe when applied with minimal information for model calibration of spring barley at field scale, whether individual models perform better than the multi-model mean, and what the uncertainty ranges are in simulated grain yields. The reasons for differences among the models and how results for barley compare to winter wheat are discussed. Regarding yield estimation, best performing based on the root mean square error (RMSE) were models HERMES, MONICA and WOFOST with lowest values of 1124, 1282 and 1325 (kg ha(-1)), respectively. Applying the index of agreement (IA), models WOFOST, DAISY and HERMES scored best having highest values (0.632, 0.631 and 0.585, respectively). Most models systematically underestimated yields, whereby CROPSYST showed the highest deviation as indicated by the mean bias error (MBE) (-1159 kg ha(-1)). While the wide range of simulated yields across all sites and years shows the high uncertainties in model estimates with only restricted calibration, mean predictions from the nine models agreed well with observations. Results of this paper also show that models that were more accurate in predicting phenology were not necessarily the ones better estimating grain yields. Total above-ground biomass estimates often did not follow the patterns of grain yield estimates and, thus, harvest indices were also different. Estimates of soil moisture dynamics varied greatly. In comparison, even though the growing cycle for winter wheat is several months longer than for spring barley, using RMSE and IA as indicators, models performed slightly, but not significantly, better in predicting wheat yields. Errors in reproducing crop phenology were similar, which in conjunction with the shorter growth cycle of barley has higher effects on accuracy in yield prediction. |
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English |
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Conference |
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| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4592 |
| Permanent link to this record |
