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Sharif, B.; Mankowski, D.; Kersebaum, K.C.; Trnka, M.; Schelde, K.; Olsesen, J.E. |
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Title |
Empirical analysis on crop-weather relationships |
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Report |
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Year |
2015 |
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FACCE MACSUR Reports |
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6 |
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D-C2.5 |
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There have been several studies, where process-based crop models are developed, used and compared in order to project crop production and corresponding model uncertainties under climate change. Despite many advances in this field, there are some correlations between climate variables and crop growth, such as pest and diseases, that is often absent in process-based models. Such relationships can be simulated using empirical models. In this study, several statistical techniques were applied on winter oilseed rape data collected in some European countries. The empirical models were then used to predict yield of winter oilseed rape in the field experiments during more than 20 years, up to 2013. Results suggest that newly developed regression techniques such as shrinkage methods work well both in yield projections and finding the influential climatic variables. Many of regression techniques agree in terms of yield prediction; however, choice of significant climate variables is rather sensitive to the choice of regression technique. No Label |
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MA @ admin @ |
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2092 |
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Schils, R.; Kersebaum, K.C.; Nieróbca, A.; Zylowska, K.; Boogaard, H.; De Groot, H.; Van Bussel, L.; Wolf, J.; Van Ittersum, M. |
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Title |
Yield gap analysis of cereals in Europe supported by local knowledge |
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Conference Article |
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2014 |
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CropM |
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MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12 |
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MA @ admin @ |
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2799 |
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Schils, R.; Kersebaum, K.C.; Nieróbca, A.; Zylowska, K.; Boogaard, H.; De Groot, H.; Rijk, B.; van Bussel, L.; Wolf, J.; van Ittersum, M. |
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Title |
Global Yield Gap Atlas; cereals in Europe |
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Conference Article |
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2014 |
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CropM |
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XIII ESA congress, Debrecen, Hungary, 2014-08-25 to 2014-08-29 |
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MA @ admin @ |
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2798 |
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Salo, T.J.; Palosuo, T.; Kersebaum, K.C.; Nendel, C.; Angulo, C.; Ewert, F.; Bindi, M.; Calanca, P.; Klein, T.; Moriondo, M.; Ferrise, R.; Olesen, J.E.; Patil, R.H.; Ruget, F.; Takáč, J.; Hlavinka, P.; Trnka, M.; Rötter, R.P. |
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Comparing the performance of 11 crop simulation models in predicting yield response to nitrogen fertilization |
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Journal Article |
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2016 |
Publication |
Journal of Agricultural Science |
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J. Agric. Sci. |
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154 |
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7 |
Pages |
1218-1240 |
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northern growing conditions; climate-change impacts; spring barley; systems simulation; farming systems; soil properties; winter-wheat; dynamics; growth; management |
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Abstract |
Eleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area index (LAI) and yield observations. The models were then tested against new data for 2009 and their performance was assessed and compared with both the two calibration years and the test year. For the calibration period, root mean square error between measurements and simulated grain dry matter yields ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi-model mean could not correct systematic errors in model simulations. Variation in soil N mineralization and LAI development due to differences in weather not captured by the models most likely was the main reason for their unsatisfactory performance. This suggests the need for model improvement in soil N mineralization as a function of soil temperature and moisture. Furthermore, specific weather event impacts such as low temperatures after emergence in 2009, tending to enhance tillering, and a high precipitation event just before harvest in 2008, causing possible yield penalties, were not captured by any of the models compared in the current study. |
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0021-8596 1469-5146 |
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CropM, ft_macsur |
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MA @ admin @ |
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4713 |
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Ruiz-Ramos, M.; Ferrise, R.; Rodríguez, A.; Lorite, I.J.; Tao, F.; Pirttioja, N.; Fronzek, S.; Palosuo, T.; Carter, T.R.; Bindi, M.; Höhn, J.G.; Kersebaum, K.C.; Trnka, M.; Hoffmann, H.; Baranowski, P.; Buis, S.; Cammarano, D.; Deligios, P.A.U.-, P.H.; Minet, J.; Montesino, M.; Porter, J.; Recio, J.; Ruget, F.; Sanz, A.; Steinmetz, Z.; Stratonovitch, P.; Supit, I.; Ventrella, D.; Wit, A.D.; Rötter, R.P. |
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Title |
Wheat yield potential in Europe under climate change explored by adaptation response surfaces |
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Conference Article |
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Year |
2016 |
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Montpellier (France) |
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6th AgMIP Global Workshop, 2016-06-28 to 2016-06-30, Montpellier, France |
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MA @ admin @ |
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4886 |
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