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van Bussel, L.G.J.; Stehfest, E.; Siebert, S.; Müller, C.; Ewert, F. |
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Title |
Simulation of the phenological development of wheat and maize at the global scale |
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Journal Article |
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Year |
2015 |
Publication |
Global Ecology and Biogeography |
Abbreviated Journal |
Glob. Ecol. Biogeogr. |
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Volume |
24 |
Issue |
9 |
Pages |
1018-1029 |
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Keywords |
Agricultural management; crop calendars; cultivar; variety characteristics; global crop modelling; global harvest dates; phenology; climate-change; winter-wheat; annual crops; photoperiod sensitivity; geographical variation; temperature; responses; adaptation; cultivars; model |
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AimTo derive location-specific parameters that reflect the geographic differences among cultivars in vernalization requirements, sensitivity to day length (photoperiod) and temperature, which can be used to simulate the phenological development of wheat and maize at the global scale. LocationGlobal. Methods Based on crop calendar observations and literature describing the large-scale patterns of phenological characteristics of cultivars, we developed algorithms to compute location-specific parameters to represent this large-scale pattern. Vernalization requirements were related to the duration and coldness of winter, sensitivity to day length was assumed to be represented by the minimum and maximum day lengths occurring at a location, and sensitivity to temperature was related to temperature conditions during the vegetative development phase of the crop. Results Application of the derived location-specific parameters resulted in high agreement between simulated and observed lengths of the cropping period. Agreement was especially high for wheat, with mean absolute errors of less than 3 weeks. In the main maize cropping regions, cropping periods were over- and underestimated by 0.5-1.5 months. We also found that interannual variability in simulated wheat harvest dates was more realistic when accounting for photoperiod effects. Main conclusions The methodology presented here provides a good basis for modelling the phenological characteristics of cultivars at the global scale. We show that current global patterns of growing season length as described in cropping calendars can be largely reproduced by phenology models if location-specific parameters are derived from temperature and day length indicators. Growing seasons can be modelled more accurately for wheat than for maize, especially in warm regions. Our method for computing parameters for phenology models from temperature and day length offers opportunities to improve the simulation of crop productivity by crop simulation models developed for large spatial areas and for long-term climate impact projections that account for adaptation in the selection of varieties |
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1466-822x |
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CropM, ft_macsur |
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MA @ admin @ |
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4729 |
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Stefańczyk, E.; Sobkowiak, S.; Brylińska, M.; Śliwka, J. |
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Title |
Diversity of Fusarium spp. associated with dry rot of potato tubers in Poland |
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Journal Article |
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Year |
2016 |
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European Journal of Plant Pathology |
Abbreviated Journal |
Eur. J. Plant Pathol. |
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ITS; mycotoxin; pathogenicity; Solanum tuberosum; tef-1α; β-tubulin; sequence data; Trichothecenes; identification; fungus; pathogenicity; temperature; sensitivity; zearalenone; strains; disease |
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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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0929-1873 1573-8469 |
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CropM, ft_macsur |
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MA @ admin @ |
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4721 |
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Sándor, R.; Ma, S.; Acutis, M.; Barcza, Z.; Ben Touhami, H.; Doro, L.; Hidy, D.; Köchy, M.; Lellei-Kovács, E.; Minet, J.; Perego, A.; Rolinski, S.; Ruget, F.; Seddaiu, G.; Wu, L.; Bellocchi, G. |
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Uncertainty in simulating biomass yield and carbon–water fluxes from grasslands under climate change |
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2015 |
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Advances in Animal Biosciences |
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Advances in Animal Biosciences |
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6 |
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01 |
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49-51 |
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Keywords |
grassland productivity; carbon balance; model simulation; uncertainty; sensitivity |
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2040-4700 |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
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4651 |
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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. |
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Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models |
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Journal Article |
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2012 |
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Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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133 |
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23-36 |
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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 |
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► 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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CropM, ftnotmacsur |
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MA @ admin @ |
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4592 |
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Martre, P.; He, J.; Le Gouis, J.; Semenov, M.A. |
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In silico system analysis of physiological traits determining grain yield and protein concentration for wheat as influenced by climate and crop management |
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2015 |
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Journal of Experimental Botany |
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J. Experim. Bot. |
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66 |
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12 |
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3581-3598 |
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Climate; *Computer Simulation; Crops, Agricultural/*growth & development/physiology; Edible Grain/*growth & development; Models, Biological; Nitrogen/metabolism; Plant Proteins/*metabolism; Plant Transpiration; Probability; *Quantitative Trait, Heritable; Soil/chemistry; Triticum/growth & development/metabolism/*physiology; Water/chemistry; Crop growth model; genetic adaptation; grain protein concentration; grain yield; interannual variability; sensitivity analysis; wheat (Triticum aestivum L.); yield stability |
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Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work. |
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1460-2431 (Electronic) 0022-0957 (Linking) |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4567 |
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