Reference : Systematic analysis of site-specific yield distributions resulting from nitrogen mana...
Scientific journals : Article
Life sciences : Agriculture & agronomy
Life sciences : Environmental sciences & ecology
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/173632
Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions
English
Dumont, Benjamin mailto [Université de Liège - ULiège > Sciences et technologie de l'environnement > Agriculture de précision >]
Basso, Bruno [Michigan State University, Lansing, MI, USA > Dpt. of Geological sciences > > > >]
Leemans, Vincent mailto [Université de Liège - ULiège > Sciences et technologie de l'environnement > Agriculture de précision >]
Bodson, Bernard mailto [Université de Liège - ULiège > Sciences agronomiques > Phytotechnie des régions tempérées >]
Destain, Jean-Pierre mailto [Université de Liège - ULiège > Sciences agronomiques > Phytotechnie des régions tempérées >]
Destain, Marie-France mailto [Université de Liège - ULiège > Sciences et technologie de l'environnement > Agriculture de précision >]
Aug-2015
Precision Agriculture
Springer
16
4
361-384
Yes (verified by ORBi)
International
1385-2256
1573-1618
Secaucus
NJ
[en] Nitrogen management ; Climatic variability ; Weather Generator ; STICS Soil-crop model ; Pearson system ; Probability risk assessment
[en] 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.
SPW (DGARNE - DGO3)
Suivi en temps réel de l’environnement d’une parcelle agricole par un réseau de micro-capteurs en vue d’optimiser l’apport en engrais azotés
Researchers ; Professionals ; General public
http://hdl.handle.net/2268/173632
10.1007/s11119-014-9380-7
http://link.springer.com/article/10.1007/s11119-014-9380-7
The final publication is available at http://link.springer.com/article/10.1007/s11119-014-9380-7

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