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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. |
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Title |
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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Year |
2012 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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Volume |
133 |
Issue |
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Pages |
23-36 |
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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 |
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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. |
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2016-10-31 |
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0378-4290 |
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CropM, ftnotmacsur |
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Call Number |
MA @ admin @ |
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4803 |
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Author |
Perego, A.; Sanna, M.; Giussani, A.; Chiodini, M.E.; Fumagalli, M.; Pilu, S.R.; Bindi, M.; Moriondo, M.; Acutis, M. |
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Title |
Designing a high-yielding maize ideotype for a changing climate in Lombardy plain (northern Italy) |
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Journal Article |
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Year |
2014 |
Publication |
Science of The Total Environment |
Abbreviated Journal |
Science of The Total Environment |
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Volume |
499 |
Issue |
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Pages |
497-509 |
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Keywords |
Agriculture/*methods/standards; *Climate Change; Droughts; Italy; Nitrogen/analysis; Soil; Water Supply/statistics & numerical data; Zea mays/*growth & development/standards; Climate change; Crop model; Maize; Water use adaptation |
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Abstract |
The expected climate change will affect the maize yields in view of air temperature increase and scarce water availability. The application of biophysical models offers the chance to design a drought-resistant ideotype and to assist plant breeders and agronomists in the assessment of its suitability in future scenarios. The aim of the present work was to perform a model-based estimation of the yields of two hybrids, current vs ideotype, under future climate scenarios (2030-2060 and 2070-2100) in Lombardy (northern Italy), testing two options of irrigation (small amount at fixed dates vs optimal water supply), nitrogen (N) fertilization (300 vs 400 kg N ha(-1)), and crop cycle durations (current vs extended). For the designing of the ideotype we set several parameters of the ARMOSA process-based crop model: the root elongation rate and maximum depth, stomatal resistance, four stage-specific crop coefficients for the actual transpiration estimation, and drought tolerance factor. The work findings indicated that the current hybrid ensures good production only with high irrigation amount (245-565 mm y(-1)). With respect to the current hybrid, the ideotype will require less irrigation water (-13%, p<0.01) and it resulted in significantly higher yield under water stress condition (+15%, p<0.01) and optimal water supply (+2%, p<0.05). The elongated cycle has a positive effect on yield under any combination of options. Moreover, higher yields projected for the ideotype implicate more crop residues to be incorporated into the soil, which are positively correlated with the SOC sequestration and negatively with N leaching. The crop N uptake is expected to be adequate in view of higher rate of soil mineralization; the N fertilization rate of 400 kg N ha(-1) will involve significant increasing of grain yield, and it is expected to involve a higher rate of SOC sequestration. |
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2016-10-31 |
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ISSN |
0048-9697 |
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CropM |
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MA @ admin @ |
Serial |
4798 |
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Author |
Yin, X.; Olesen, J.E.; Wang, M.; Öztürk, I.; Zhang, H.; Chen, F. |
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Title |
Impacts and adaptation of the cropping systems to climate change in the Northeast Farming Region of China |
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Journal Article |
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Year |
2016 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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Volume |
78 |
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Pages |
60-72 |
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Keywords |
Climate change; Vulnerability; Impact; Adaptation; Cropping systems; The Northeast Farming Region of China; maize production; high-temperature; growth period; yield; rice; drought; management; nitrogen; crops; pests |
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Abstract |
The Northeast Farming Region of China (NFR) is a very important crop growing area, comprising seven sub-regions: Xing’anling (XA), Sanjiang (SJ), Northwest Songliao (NSL), Central Songliao (CSL), Southwest Songliao (SSL), Changbaishan (CB) and Liaodong (LD), which has been severely affected by extreme climate events and climatic change. Therefore, a set of expert survey has been done to identify current and project future climate limitations to crop production and explore appropriate adaptation measures in NFR. Droughts have been the largest limitation for maize (Zea mays L.) in NSL and SSL, and for soybean (Glycine max L Merr.) in SSL. Chilling damage has been the largest limitation for rice (Oryza sativa L) production in XA, SJ and CB. Projected climate change is expected to be beneficial for expanding the crop growing season, and to provide more suitable conditions for sowing and harvest. Autumn frost will occur later in most parts of NFR, and chilling damage will also decrease, particularly for rice production in XA and SJ. Drought and heat stress are expected to become more severe for maize and soybean production in most parts of NFR. Also, plant diseases, pests and weeds are considered to become more severe for crop production under climate change. Adaptation measures that have already been implemented in recent decades to cope with current climatic limitations include changes in timing of cultivation, variety choice, soil tillage practices, crop protection, irrigation and use of plastic film for soil cover. With the projected climate change and increasing risk of climatic extremes, additional adaptation measures will become relevant for sustaining and improving productivity of crops in NFR to ensure food security in China. (C) 2016 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4772 |
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Author |
Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P. |
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Title |
Variability in crop yields associated with climate anomalies in China over the past three decades |
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Journal Article |
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Year |
2016 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
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Volume |
16 |
Issue |
6 |
Pages |
1715-1723 |
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Keywords |
Adaptation; Climate change; Climate extremes; Drought; Impacts and vulnerability |
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Abstract |
We used simple and explicit methods, as well as improved datasets for climate, crop phenology and yields, to address the association between variability in crop yields and climate anomalies in China from 1980 to 2008. We identified the most favourable and unfavourable climate conditions and the optimum temperatures for crop productivity in different regions of China. We found that the simultaneous occurrence of high temperatures, low precipitation and high solar radiation was unfavourable for wheat, maize and soybean productivity in large portions of northern, northwestern and northeastern China; this was because of droughts induced by warming or an increase in solar radiation. These climate anomalies could cause yield losses of up to 50 % for wheat, maize and soybeans in the arid and semi-arid regions of China. High precipitation and low solar radiation were unfavourable for crop productivity throughout southeastern China and could cause yield losses of approximately 20 % for rice and 50 % for wheat and maize. High temperatures were unfavourable for rice productivity in southwestern China because they induced heat stress, which could cause rice yield losses of approximately 20 %. In contrast, high temperatures and low precipitation were favourable for rice productivity in northeastern and eastern China. We found that the optimum temperatures for high yields were crop specific and had an explicit spatial pattern. These findings improve our understanding of the impacts of extreme climate events on agricultural production in different regions of China. |
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2016-06-20 |
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1436-3798 1436-378x |
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CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
4757 |
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Author |
Eyshi Rezaei, E.; Siebert, S.; Ewert, F. |
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Title |
Impact of data resolution on heat and drought stress simulated for winter wheat in Germany |
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Journal Article |
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Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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65 |
Issue |
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Pages |
69-82 |
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Keywords |
crop modeling; heat; drought; spatial resolution; wheat; high-temperature stress; climate-change; grain-yield; crop models; data aggregation; abiotic stress; short periods; variability; growth; duration |
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Abstract |
Heat and drought stress can reduce crop yields considerably which is increasingly assessed with crop models for larger areas. Applying these models originally developed for the field scale at large spatial extent typically implies the use of input data with coarse resolution. Little is known about the effect of data resolution on the simulated impact of extreme events like heat and drought on crops. Hence, in this study the effect of input and output data aggregation on simulated heat and drought stress and their impact on yield of winter wheat is systematically analyzed. The crop model SIMPLACE was applied for the period 1980-2011 across Germany at a resolution of 1 km x 1 km. Weather and soil input data and model output data were then aggregated to 10 km x 10 km, 25 km x 25 km, 50 km x 50 km and 100 km x 100 km resolution to analyze the aggregation effect on heat and drought stress and crop yield. We found that aggregation of model input and output data barely influenced the mean and median of heat and drought stress reduction factors and crop yields simulated across Germany. However, data aggregation resulted in less spatial variability of model results and a reduced severity of simulated stress events, particularly for regions with high heterogeneity in weather and soil conditions. Comparisons of simulations at coarse resolution with those at high resolution showed distinct patterns of positive and negative deviations which compensated each other so that aggregation effects for large regions were small for mean or median yields. Therefore, modelling at a resolution of 100 km x 100 km was sufficient to determine mean wheat yield as affected by heat and drought stress for Germany. Further research is required to clarify whether the results can be generalized across crop models differing in structure and detail. Attention should also be given to better understand the effect of data resolution on interactions between heat and drought impacts. (C) 2015 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4751 |
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