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Dumont, B. (2014). Uncertainty linked to crop modelling in order to develop decision support tools. PhD, PhD. Ph.D. thesis, Université de Liège, Liège.
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Mansouri, M., Dumont, B., & Destain, M. - F. (2014). Predicting Grain Protein Content of Winter Wheat..
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Mansouri, M., Dumont, B., & Destain, M. - F. (2014). Bayesian methods for predicting and modelling winter wheat biomass..
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Mansouri, M., Dumont, B., & Destain, M. - F. (2012). Bayesian methods for predicting LAI and soil moisture..
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Dumont, B., Basso, B., Bodson, B., Destain, J. - P., & Destain, M. - F. (2016). Assessing and modeling economic and environmental impact of wheat nitrogen management in Belgium. Env. Model. Softw., 79, 184–196.
Abstract: Future progress in wheat yield will rely on identifying genotypes & management practices better adapted to the fluctuating environment Nitrogen (N) fertilization is probably the most important practice impacting crop growth. However, the adverse environmental impacts of inappropriate N management (e.g., lixiviation) must be considered in the decision-making process. A formal decisional algorithm was developed to tactically optimize the economic & environmental N fertilization in wheat. Climatic uncertainty analysis was performed using stochastic weather time-series (LARS-WG). Crop growth was simulated using STICS model. Experiments were conducted to support the algorithm recommendations: winter wheat was sown between 2008 & 2014 in a classic loamy soil of the Hesbaye Region, Belgium (temperate climate). Results indicated that, most of the time, the third N fertilization applied at flag-leaf stage by farmers could be reduced. Environmental decision criterion is most of the time the limiting factor in comparison to the revenues expected by farmers. (C) 2016 Elsevier Ltd. All rights reserved.
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