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Hoffmann, H.; Zhao, G.; Asseng, S.A.U.-,; Bindi, M.; Cammarano, D.; Constantin, J.; Coucheney, E.; Dechow, R.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kassie, B.; Kersebaum, K.C.; Kiese, R.; Klatt, S.; Kuhnert, M.; Lewan, E.; Moriondo, M.; Nendel, C.; Raynal, H.; Roggero, P.P.; Rötter, R.; Siebert, S.; Sosa, C.; Specka, X.; Tao, F.; Teixeira, E.; Trombi, G.; Yeluripati, J.; Vanuytrecht, E.; Wallach, D.; Wang, E.; Weihermüller, L.; Zhao, Z.; Ewert, F. |
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Analysing data aggregation effects on large-scale yield simulations |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4923 |
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Seifried, A.; Sinabell, F.; Mitter, H.; E., S. |
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Title |
Analysing stochastic dominance of soybean and maize production in Austria |
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2014 |
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TradeM |
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Lebensmittelversorgung, Lebensmittelsicherheit und Ernährungssouveränität Food security, safety and sovereignty, 24. Jahrestagung der Österreichischen Gesellschaft für Agrarökonomie, Wien, 2014-09-25 to 2014-09-26 |
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MA @ admin @ |
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2816 |
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Kersebaum, K.C.; Boote, K.J.; Jorgenson, J.S.; Nendel, C.; Bindi, M.; Frühauf, C.; Gaiser, T.; Hoogenboom, G.; Kollas, C.; Olesen, J.E.; Rötter, R.P.; Ruget, F.; Thorburn, P.J.; Trnka, M.; Wegehenkel, M. |
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Title |
Analysis and classification of data sets for calibration and validation of agro-ecosystem models |
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Journal Article |
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2015 |
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Environmental Modelling & Software |
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Env. Model. Softw. |
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72 |
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402-417 |
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field experiments; data quality; crop modelling; data requirement; minimum data; software; different climatic zones; soil-moisture sensors; spatial variability; nitrogen dynamics; crop models; systems simulation; wheat yields; elevated co2; growth; field |
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Abstract |
Experimental field data are used at different levels of complexity to calibrate, validate and improve agroecosystem models to enhance their reliability for regional impact assessment. A methodological framework and software are presented to evaluate and classify data sets into four classes regarding their suitability for different modelling purposes. Weighting of inputs and variables for testing was set from the aspect of crop modelling. The software allows users to adjust weights according to their specific requirements. Background information is given for the variables with respect to their relevance for modelling and possible uncertainties. Examples are given for data sets of the different classes. The framework helps to assemble high quality data bases, to select data from data bases according to modellers requirements and gives guidelines to experimentalists for experimental design and decide on the most effective measurements to improve the usefulness of their data for modelling, statistical analysis and data assimilation. (C) 2015 Elsevier Ltd. All rights reserved. |
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English |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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4563 |
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Kuzniar, A.; Kowalczyk, A.; Kostuch, M. |
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Title |
Analysis of criteria for determination of less favored areas in the mountains |
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2013 |
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CropM |
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Priorities of sustainable rural development 2014-2020 in the light of scientific research. Institute of Technology and Life Sciences at Falenty, Poland., 2013-04-25 to 2013-04-26 |
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no |
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MA @ admin @ |
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2581 |
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Rötter, R.P.A.U.-, J.H.; Kassie, B.T.; Paff, K.; Palosuo, T.A.U.-, C.Y.; Tao, F.; Ewert, F.; Asseng, S.; Haakana |
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Title |
Analysis of crop yield variability and yield gaps for maize and wheat in diverse climatic zones |
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Conference Article |
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2016 |
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Berlin (Germany) |
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poster |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4922 |
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