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Author  |
de Wit, A.; Rötter, R.P.; Palosuo, T.; Bergjord, A.K.; Virchenko, O.; Kleshenko, A. |
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Title |
Simulating the impact of winter conditions on the survival and yield potential of winter wheat |
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Conference Article |
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Year |
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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Call Number |
MA @ admin @ |
Serial |
4905 |
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Author |
Coucheney, E.; Eckersten, H.; Jansson, P.E.; Ewert, F.; Gaiser, T.; Hoffmann, H.; Lewan, E. |
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Title |
The role of spatial patterns of soil types for data aggregation effects in crop modelling |
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Conference Article |
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Year |
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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Call Number |
MA @ admin @ |
Serial |
4902 |
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Author |
Constantin, J.; Bergez, J.-E.; Raynal, H.; Hoffmann, H.; Ewert, F. |
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Title |
Impact of maize management variability modeled as decision rules on yield and Drainage at the regional scale |
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Conference Article |
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Year |
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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4913 |
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Author |
Conradt, T.; Gornott, C.; Wechsung, F. |
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Title |
Extending and improving regionalized winter wheat and silage maize yield regression models for Germany: Enhancing the predictive skill by panel definition through cluster analysis |
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Journal Article |
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Year |
2016 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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216 |
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68-81 |
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Keywords |
cluster analysis; crop yield estimation; germany; multivariate regression; silage maize; winter wheat; climate-change; canadian prairies; crop yield; temperature; responses; environments; variability; cultivar; china |
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Abstract |
Regional agricultural yield assessments allowing for weather effect quantifications are a valuable basis for deriving scenarios of climate change effects and developing adaptation strategies. Assessing weather effects by statistical methods is a classical approach, but for obtaining robust results many details deserve attention and require individual decisions as is demonstrated in this paper. We evaluated regression models for annual yield changes of winter wheat and silage maize in more than 300 German counties and revised them to increase their predictive power. A major effort of this study was, however, aggregating separately estimated time series models (STSM) into panel data models (PDM) based on cluster analyses. The cluster analyses were based on the per-county estimates of STSM parameters. The original STSM formulations (adopted from a parallel study) contained also the non-meteorological input variables acreage and fertilizer price. The models were revised to use only weather variables as estimation basis. These consisted of time aggregates of radiation, precipitation, temperature, and potential evapotranspiration. Altering the input variables generally increased the predictive power of the models as did their clustering into PDM. For each crop, five alternative clusterings were produced by three different methods, and similarities between their spatial structures seem to confirm the existence of objective clusters about common model parameters. Observed smooth transitions of STSM parameter values in space suggest, however, spatial autocorrelation effects that could also be modeled explicitly. Both clustering and autocorrelation approaches can effectively reduce the noise in parameter estimation through targeted aggregation of input data. (C) 2015 Elsevier B.V. All rights reserved. |
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English |
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ISSN |
0168-1923 |
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Notes |
CropM, ft_macsur |
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Call Number |
MA @ admin @ |
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4709 |
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Author |
Coles, G.D.; Wratten, S.D.; Porter, J.R. |
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Title |
Food and nutritional security requires adequate protein as well as energy, delivered from whole-year crop production |
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Journal Article |
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Year |
2016 |
Publication |
PeerJ |
Abbreviated Journal |
PeerJ |
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Volume |
4 |
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Pages |
17 |
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Keywords |
Agroecology; Forage utilisation; Food costs; Nutrition; Whole-year; production; New Zealand; Food access; Food security; humans |
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Abstract |
Human food security requires the production of sufficient quantities of both high-quality protein and dietary energy. In a series of case-studies from New Zealand, we show that while production of food ingredients from crops on arable land can meet human dietary energy requirements effectively, requirements for high-quality protein are met more efficiently by animal production from such land. We present a model that can be used to assess dietary energy and quality-corrected protein production from various crop and crop/animal production systems, and demonstrate its utility. We extend our analysis with an accompanying economic analysis of commercially available pre-prepared or simply-cooked foods that can be produced from our case-study crop and animal products. We calculate the per-person, per-day cost of both quality-corrected protein and dietary energy as provided in the processed foods. We conclude that mixed dairy/cropping systems provide the greatest quantity of high quality protein per unit price to the consumer, have the highest food energy production and can support the dietary requirements of the highest number of people, when assessed as all-year-round production systems. Global food and nutritional security will largely be an outcome of national or regional agroeconomies addressing their town food needs. We hope that lour model will be used for similar analyses of food production systems in other countries, agroecological zones and economies. |
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Address |
2016-09-13 |
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English |
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ISSN |
2167-8359 |
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Notes |
CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4774 |
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