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Author |
Jancic, M. |
Title |
Climate change adaptation in maize production in Serbia |
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Report |
Year |
2016 |
Publication |
FACCE MACSUR Reports |
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9 C6 - |
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Sp9-3 |
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Climate change is noticed and well established phenomenon, described as change in the statistical properties of the climate system, considered over long period of time, regardless of cause (Houghton, 1996). This change has been monitored on global (Rosenzweig et al., 1994; Harrison et al., 1995; Wolf et al., 1995; Watson et al., 1996; Downing et al., 2000; Sathaye et al., 1997; Sirotenko et al., 1997) and regional scale (Alexandrov et al., 2002; Lalic et al., 2012; Vučetić, 2011) by researchers, organizations and part of various programmes (IPCC, UNESCO Climate Change Initiative). In a same time, it was analysed change in agroclimatic indices, soil and water balance, crop development and yield, that quantify climate change impact on agricultural production. In recent regional studies and research projects (COST 734, 2008; ADAGIO, 2009), it was estimated and quantified climate change impact on yield and development in crop production of Central and Eastern European countries and Mediterranean region. The research showed a decrease in yield in several major crops, important in national food production and part of economy. A high variability in yield from year to year and decrease in yield was showed for most cereals. |
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MA @ admin @ |
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4856 |
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Slawinski, C.; Brzezinska, M.; Lipiec, J. |
Title |
MACSUR -Modelling European Agriculture with Climate Change for Food Security |
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2012 |
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CropM |
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A seminar on presenting the objectives of FACCE-JPI MACSUR project and discussing the participation of the Institute of Agrophysics PAS in this project (cooperation between partners: 139, 158, 162), Institute of Agrophysics Polish Academy of Sciences, Lub |
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MA @ admin @ |
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2842 |
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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. |
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 |
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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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English |
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0378-4290 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4803 |
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Author |
Nikolic, U.; Mitter, H.; Schmid, E.; F., S. |
Title |
Stand und Perspektiven des Sojaanbaues in Serbien (situation and outlook of soy bean production in Serbia) |
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Conference Article |
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2014 |
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TradeM |
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42. Jahrestagung der Österreichischen Gesellschaft für Agrarökonomie, Wien, 2014-09-25 to 2014-09-26 |
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MA @ admin @ |
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2685 |
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Author |
Kondracka, K.; Nosalewicz, A.; Lipiec, J. |
Title |
Effect of heat stress and water deficit on photosynthesis |
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2014 |
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III. Conference of Young Scientists, Lublin, Poland, 2014-05-25 to 2014-05-26 |
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MA @ admin @ |
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2563 |
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