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Dumont, B.; Basso, B.; Leemans, V.; Destain, J.P.; Bodson, B.; Destain, M.-F. |
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Title |
Yield variability linked to climate uncertainty and nitrogen fertilisation |
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2013 |
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CropM |
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9th ECPA - European Conference on Precision Agriculture, Lleida, Spain, 2013-07-07 to 2013-07-11 |
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MA @ admin @ |
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2411 |
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Dumont, B.; Basso, B.; Destain, J.-P.; Bodson, B.; Destain, M.-F. |
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Title |
A Comparison of Optimal Nitrogen Fertilisation Strategies Using Current and Future Stochastically Generated Climatic Conditions |
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2014 |
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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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no |
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MA @ admin @ |
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2412 |
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Dumont, B.; Leemans, V.; Ferrandis Vallterra, S.; Vancutsem, F.; Seutin, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
A first step towards a real-time predictive yield support system |
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2012 |
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CropM |
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CIGR-AgEng 2012, International Conference on Agricultural Engineering, Valencia (Spain)., 2012-07-07 to 2012-07-12 |
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MA @ admin @ |
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2403 |
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Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
A Site-Specific Grain Yield Response Surface : Computing the Identity Card of a Crop Under Different Nitrogen Management Scenarios |
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2013 |
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CropM |
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Proceedings of the EFITA-WCCA-CIGR 2013 - Sustainable Agriculture through ICT innovation, 2013-11-03 to 2013-11-06, Torino |
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no |
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Call Number |
MA @ admin @ |
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2408 |
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Author |
Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions |
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Journal Article |
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Year |
2015 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
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16 |
Issue |
4 |
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361-384 |
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Keywords |
nitrogen management; climatic variability; lars-wg weather generator; stics soil-crop model; pearson system; probability risk assessment; crop model stics; fertilizer nitrogen; generic model; wheat yield; maize; simulation; skewness; field; agriculture; scenarios |
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Abstract |
At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution. |
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English |
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1385-2256 |
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CropM, ft_macsur |
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MA @ admin @ |
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4519 |
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