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	Author	Yin, X.G.; Kersebaum, K.C.; Kollas, C.; Manevski, K.; Baby, S.; Beaudoin, N.; Ozturk, I.; Gaiser, T.; Wu, L.H.; Hoffmann, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Ewert, F.; de Cortazar-Atauri, I.G.; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Launay, M.; Louarn, G.; Manderscheid, R.; Mary, B.; Mirschel, W.; Nende, C.; Pacholskin, A.; Palosuo, T.; Ripoche-Wachter, D.; Rotter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Weigel, H.J.; Olesen, J.E.; Yin, X.; Kersebaum, K.C.; Kollas, C.; Manevski, K.; Baby, S.; Beaudoin, N.; Ozturk, I.; Gaiser, T.; Wu, L.; Hoffmann, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Ewert, F.; de Cortazar-Atauri, I.G.; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Launay, M.; Louarn, G.; Manderscheid, R.; Mary, B.; Mirschel, W.; Nende, C.; Pacholskin, A.; Palosuo, T.; Ripoche-Wachter, D.; Roetter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Weigel, H.-J.; Olesen, J.E.
	Title	Performance of process-based models for simulation of grain N in crop rotations across Europe			Type	Journal Article
	Year	2017	Publication	Agricultural Systems	Abbreviated Journal	Agric. Syst.
	Volume	154	Issue		Pages	63-77
	Keywords	Calibration, Crop model, Crop rotation, Grain N content, Model evaluation, Model initialization; Climate-Change; Winter-Wheat; Nitrogen-Fertilization; Agroecosystem; Models; Multimodel Ensembles; Yield Response; Use Efficiency; Soil-Moisture; Oilseed Rape; Elevated Co2
	Abstract	The accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo-climatic and agro-management conditions in Europe, under both continuous simulation and single year simulation, and for iv) two calibration levels, namely minimal and detailed calibration. Generally, the results showed that the accuracy of the simulations in predicting grain N increased under detailed calibration. The models performed better in predicting the grain N of winter wheat (Triticum aestivum L.), winter barley (Hordewn vulgare L.) and spring barley (Hordeum vulgare L.) compared to spring oat (Avena saliva L.), winter rye (Secale cereale L.), pea (Piswn sativum L.) and winter oilseed rape (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N and rainfed treatments. Moreover, the multi-model mean provided better predictions of grain N compared to any individual model. In regard to the Individual models, DAISY, FASSET, HERMES, MONICA and STICS are suitable for predicting grain N of the main crops in typical European crop rotations, which all performed well in both continuous simulation and single year simulation. Our results show that both the model initialization and the cover crop effects in crop rotations should be considered in order to achieve good performance of continuous simulation. Furthermore, the choice of either continuous simulation or single year simulation should be guided by the simulation objectives (e.g. grain yield, grain N content or N dynamics), the crop sequence (inclusion of legumes) and treatments (rate and type of N fertilizer) included in crop rotations and the model formalism.
	Address	2017-06-12
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0308-521x	ISBN		Medium
	Area		Expedition		Conference
	Notes	CropM, ft_macsur			Approved	no
	Call Number	MA @ admin @			Serial	4963
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	Author	Yin, X.; Kersebaum, K.C.; Kollas, C.; Armas-Herrera, C.M.; Baby, S.; Beaudoin, N.; Bindi, M.; Charfeddine, M.; Conradt, T.; Cortazar-Atauri, I.G.D.; Ewert, F.; Ferrise, R.; Hoffmann, H.; Lana, M.; Launay, M.; Manderscheid, R.; Manevski, K.; Mary, B.; Mirschel, W.; Moriondo, M.; Müller, C.; Nendel, C.; Öztürk, I.; Palosuo, T.; Ripoche-Wachte, D.; Rötter, R.P.; Ruget, F.; Sharif, B.; Ventrella, D.; Weigel, H.-J.; Olesen, J.E.
	Title	Uncertainty in simulating N uptakes, N leaching and N use efficiency in crop rotation systems across Europe			Type	Conference Article
	Year	2016	Publication		Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication	Berlin (Germany)	Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany
	Notes				Approved	no
	Call Number	MA @ admin @			Serial	4899
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	Author	Nendel, C.; Wieland, R.; Mirschel, W.; Specka, X.; Kersebaum, K.C.
	Title	The simulation of winter wheat yields in Thuringia, Germany, using meteorological data with different spatial resolution			Type	Conference Article
	Year	2012	Publication		Abbreviated Journal
	Volume		Issue		Pages
	Keywords	CropM
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	12th Congress of the European Society for Agronomy Helsinki, Finland, 2012-08-20 to 2012-08-24
	Notes				Approved	no
	Call Number	MA @ admin @			Serial	2678
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	Author	Nendel, C.; Wieland, R.; Mirschel, W.; Specka, X.; Kersebaum, K.-C.
	Title	Die Simulation von Winterweizenerträgen in Thüringen unter Verwendung von meteorologischen Daten unterschiedlicher räumlicher Auflösung			Type	Conference Article
	Year	2013	Publication		Abbreviated Journal
	Volume		Issue		Pages
	Keywords	CropM
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	33. GIL-Jahrestagung in Potsdam 2013 - Massendatenmanagement in der Agrar- und Ernährungswirtschaft, 2013-02-21 to 2013-02-21
	Notes				Approved	no
	Call Number	MA @ admin @			Serial	2680
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	Author	Nendel, C.; Wieland, R.; Mirschel, W.; Specka, X.; Guddat, C.; Kersebaum, K.C.
	Title	Simulating regional winter wheat yields using input data of different spatial resolution			Type	Journal Article
	Year	2013	Publication	Field Crops Research	Abbreviated Journal	Field Crops Research
	Volume	145	Issue		Pages	67-77
	Keywords	monica; agro-ecosystem model; dynamic modelling; scaling; input data; climate-change; crop yield; nitrogen dynamics; food security; mineral nitrogen; soil-moisture; scaling-up; model; maize; water
	Abstract	The success of using agro-ecosystem models for the high-resolution simulation of agricultural yields for larger areas is often hampered by a lack of input data. We investigated the effect of different spatially resolved soil and weather data used as input for the MONICA model on its ability to reproduce winter wheat yields in the Federal State of Thuringia, Germany (16,172 km(2)). The combination of one representative soil and one weather station was insufficient to reproduce the observed mean yield of 6.66 +/- 0.87 t ha(-1) for the federal state. Use of a 100 m x 100 m grid of soil and relief information combined with just one representative weather station yielded a good estimator (7.01 +/- 1.47 t ha(-1)). The soil and relief data grid used in combination with weather information from 14 weather stations in a nearest neighbour approach produced even better results (6.60 +/- 1.37 t ha(-1)); the same grid used with 39 additional rain gauges and an interpolation algorithm that included an altitude correction of temperature data slightly overpredicted the observed mean (7.36 +/- 1.17 t ha(-1)). It was concluded that the apparent success of the first two high-resolution approaches over the latter was based on two effects that cancelled each other out: the calibration of MONICA to match high-yield experimental data and the growth-defining and -limiting effect of weather data that is not representative for large parts of the region. At the county and farm level the MONICA model failed to reproduce the 1992-2010 time series of yields, which is partly explained by the fact that many growth-reducing factors were not considered in the model. (C) 2013 Elsevier B.V. All rights reserved.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language	English	Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0378-4290	ISBN		Medium	Article
	Area		Expedition		Conference
	Notes	CropM, ftnotmacsur			Approved	no
	Call Number	MA @ admin @			Serial	4498
Permanent link to this record