References of "Destain, Jean-Pierre"
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See detailA comparison of within-season yield prediction algorithms based on crop model behaviour analysis
Dumont, Benjamin ULg; Basso, Bruno; Leemans, Vincent ULg et al

in Agricultural and Forest Meteorology (2015), 204

The development of methodologies for predicting crop yield, in real-time and in response to different agro-climatic conditions, could help to improve the farm management decision process by providing an ... [more ▼]

The development of methodologies for predicting crop yield, in real-time and in response to different agro-climatic conditions, could help to improve the farm management decision process by providing an analysis of expected yields in relation to the costs of investment in particular practices. Based on the use of crop models, this paper compares the ability of two methodologies to predict wheat yield (Triticum aestivum L.), one based on stochastically generated climatic data and the other on mean climate data. It was shown that the numerical experimental yield distribution could be considered as a log-normal distribution. This function is representative of the overall model behaviour. The lack of statistical differences between the numerical realisations and the logistic curve showed in turn that the Generalised Central Limit Theorem (GCLT) was applicable to our case study. In addition, the predictions obtained using both climatic inputs were found to be similar at the inter and intra-annual time-steps, with the root mean square and normalised deviation values below an acceptable level of 10% in 90% of the climatic situations. The predictive observed lead-times were also similar for both approaches. Given (i) the mathematical formulation of crop models, (ii) the applicability of the CLT and GLTC to the climatic inputs and model outputs, respectively, and (iii) the equivalence of the predictive abilities, it could be concluded that the two methodologies were equally valid in terms of yield prediction. These observations indicated that the Convergence in Law Theorem was applicable in this case study. For purely predictive purposes, the findings favoured an algorithm based on a mean climate approach, which needed far less time (by 300-fold) to run and converge on same predictive lead time than the stochastic approach. [less ▲]

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See detailAdapting Nitrogen management to the increasing climatic uncertainty
Dumont, Benjamin ULg; Basso, Bruno; Bodson, Bernard ULg et al

in Shirmohammadi, Adel; Bosch, David; Muñoz-Carpena, Rafa (Eds.) Proceedings of the 1st ASABE Climate Change Symposium - Adaptation and Mitigation (2015, May)

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See detailClimatic risk assessment to improve nitrogen fertilisation recommendations : A strategic crop model-based approach
Dumont, Benjamin ULg; Basso, Bruno; Bodson, Bernard ULg et al

in European Journal of Agronomy (2015), 65(10-17),

Within the context of nitrogen (N) management, since 1950, with the rapid intensification of agriculture, farmers have often applied much larger fertiliser quantities than what was required to reach the ... [more ▼]

Within the context of nitrogen (N) management, since 1950, with the rapid intensification of agriculture, farmers have often applied much larger fertiliser quantities than what was required to reach the yield potential. However, to prevent pollution of surface and groundwater induced by nitrates, The European Community launched The European Nitrates Directive 91/6/76/EEC. In 2002, in Wallonia (Belgium), the Nitrates Directive has been transposed under the Sustainable Nitrogen Management in Agriculture Program (PGDA), with the aim of maintaining productivity and revenue for the country’s farmers, while reducing the environmental impact of excessive N application. A feasible approach for addressing climatic uncertainty lies in the use of crop models such as the one commonly known as STICS (simulateur multidisciplinaire pour les cultures standard). These models allow the impact on crops of the interaction between cropping systems and climatic records to be assessed. Comprehensive historical climatic records are rare, however, and therefore the yield distribution values obtained using such an approach can be discontinuous. In order to obtain better and more detailed yield distribution information, the use of a high number of stochastically generated climate time series was proposed, relying on the LARS-Weather Generator. The study focused on the interactions between varying N practices and climatic conditions. Historically and currently, Belgian farmers apply 180 kg N ha−1, split into three equal fractions applied at the tillering, stem elongation and flag-leaf stages. This study analysed the effectiveness of this treatment in detail, comparing it to similar practices where only the N rates applied at the flag-leaf stage were modified. Three types of farmer decision-making were analysed. The first related to the choice of N strategy for maximising yield, the second to obtaining the highest net revenue, and the third to reduce the environmental impact of potential N leaching, which carries the likelihood of taxation if inappropriate N rates are applied. The results showed reduced discontinuity in the yield distribution values thus obtained. In general, the modulation of N levels to accord with current farmer practices showed considerable asymmetry. In other words, these practices maximised the probability of achieving yields that were at least superior to the mean of the distribution values, thus reducing risk for the farmers. The practice based on applying the highest amounts (60–60–100 kg N ha−1) produced the best yield distribution results. When simple economical criteria were computed, the 60–60–80 kg N ha−1 protocol was found to be optimal for 80–90% of the time. There were no statistical differences, however, between this practice and Belgian farmers’ current practice. When the taxation linked to a high level of potentially leachable N remaining in the soil after harvest was considered, this methodology clearly showed that, in 3 years out of 4, 30 kg N ha−1 could systematically be saved in comparison with the usual practice. [less ▲]

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See detailOptimisation of the Nitrogen fertilisation in the context of climate change
Dumont, Benjamin ULg; Basso, Bruno; Bodson, Bernard ULg et al

in Soussana, Jean-Francois (Ed.) Proceedings of the Climate Smart Agriculture 2015 conference (2015, March)

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See detail4. La fumure azotée
Meza Morales, Walter ULg; Monfort, Bruno; Dumont, Benjamin ULg et al

in Watillon, Bernard; Bodson, Bernard (Eds.) Livre Blanc Céréales (2015, February 25)

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See detailSystematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions
Dumont, Benjamin ULg; Basso, Bruno; Leemans, Vincent ULg et al

in Precision Agriculture (2014)

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 ... [more ▼]

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. [less ▲]

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See detailLivre Blanc Céréales
Bodson, Bernard ULg; Destain, Jean-Pierre ULg

Book published by Gembloux Agro-Bio Tech (2014)

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See detailLivre Blanc céréales
Destain, Jean-Pierre ULg; Bodson, Bernard ULg

Book published by Université de Liège (2014)

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See detail4. La fumure azotée
Meza Morales, Walter ULg; Monfort, Bruno; Dumont, Benjamin ULg et al

in Bodson, Bernard; Destain, Jean-Pierre (Eds.) Livre Blanc céréales (2014, February 26)

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See detailParameter identification of the STICS crop model, using an accelerated formal MCMC approach
Dumont, Benjamin ULg; Leemans, Vincent ULg; Mansouri, Majdi ULg et al

in Environmental Modelling & Software (2014), 52

This study presents a Bayesian approach for the parameters’ identification of the STICS crop model based on the recently developed Differential Evolution Adaptive Metropolis (DREAM) algorithm. The ... [more ▼]

This study presents a Bayesian approach for the parameters’ identification of the STICS crop model based on the recently developed Differential Evolution Adaptive Metropolis (DREAM) algorithm. The posterior distributions of nine specific crop parameters of the STICS model were sampled with the aim to improve the growth simulations of a winter wheat (Triticum aestivum L.) culture. The results obtained with the DREAM algorithm were initially compared to those obtained with a Nelder-Mead Simplex algorithm embedded within the OptimiSTICS package. Then, three types of likelihood functions implemented within the DREAM algorithm were compared, namely the standard least square, the weighted least square, and a transformed likelihood function that makes explicit use of the coefficient of variation (CV). The results showed that the proposed CV likelihood function allowed taking into account both noise on measurements and heteroscedasticity which are regularly encountered in crop modelling [less ▲]

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See detailAssessing the potential of an algorithm based on mean climatic data to predict wheat yield
Dumont, Benjamin ULg; Leemans, Vincent ULg; Ferrandis, Salvador et al

in Precision Agriculture (2014), 15(3)

The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in ... [more ▼]

The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3-4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days. [less ▲]

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See detailNitrogen fertilisation recommendations : could they be improved using stochastically generated climates in conjunction with crop models ?
Dumont, Benjamin ULg; Basso, Bruno; Meza Morales, Walter ULg et al

in Proceedings of the 12th ICPA (2014)

Accurate determination of optimal Nitrogen (N) recommendations which ensure maximization of farmer's revenue while minimizing the environmental constraint is maybe among the major challenges in ... [more ▼]

Accurate determination of optimal Nitrogen (N) recommendations which ensure maximization of farmer's revenue while minimizing the environmental constraint is maybe among the major challenges in agriculture. Crop models have the potential to deal with such aspects and could thus be used to develop decision support systems. However unknown future weather conditions remains the key point of accurate yield forecast. This paper presents the results of a preliminary study that aims to supply the unknown future with stochastically generated climatic conditions. Coupling the methodology with appropriate decision rules led to a generic decision support system able to guide the N management practices. [less ▲]

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See detailHow can long-term experimental plots can help us to understand the sustainability of different phosphorus inputs ?
Renneson, Malorie ULg; dufey, Joseph; Roisin, Christian et al

Poster (2014)

During the last twenty years, we observed a constant reduction of mineral fertilizer use, due to prices increase and environmental awareness, and an increase of crop removal, leading to a phosphorus (P ... [more ▼]

During the last twenty years, we observed a constant reduction of mineral fertilizer use, due to prices increase and environmental awareness, and an increase of crop removal, leading to a phosphorus (P) budget decrease. These changes are feared for a decrease of soil P content, which is already observed in some regions in Wallonia. However, P being an essential element for plant growth, is a such management compatible with yield maintaining? Are the current cropping systems sustainable? To answer to the questions, different studies are made. However, long-term data are rarely available to understand the influence of cropping systems on the soil behavior, leaching risks or to choose adequate indicators of P. To answer to these questions in our soils, 2 experimental plots of the Walloon Agricultural Research Center. These experimental plots were established in 1967 and 1959 in order to evaluate the effect of, respectively, 3 P and K input levels and different organic inputs on the production. Soils samples were taken in plots and analyzed in laboratory. So, different P indicators and edaphic parameters were determined. This study showed that all indicators are coherent with P levels and correlated with yields but no many differences can be shown between fertilizer types. Meanly, zero P-input engenders a decrease of yield of 7%, while a double input increases yield of 2% in comparison to plots with an input corresponding to crop export. So, financially, the zero P-input option is rarely profitable in the long-term and double input of P removed is never financially sustainable. Leaching into deeper soils levels was studied with analysis of deeper horizons which indicated any leaching , even in plots with double inputs. Indeed, soil P contents in depth were similar in these plots than those with no P-inputs or soils under forest cover. So, to conclude, these plots help to study the sustainability of cropping systems in real situations and to determine appropriate management of P. [less ▲]

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See detailA comparison of within-season yield prediction methodologies
Dumont, Benjamin ULg; Basso, Bruno; Bodson, Bernard ULg et al

Conference (2013, November)

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See detailLivre Blanc - Céréales
Destain, Jean-Pierre ULg; Bodson, Bernard ULg

Book published by Gembloux-Agro Bio Tech - Edition septembre 2013 (2013)

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See detailHow can long-term experimental plots can help us to understand the sustainability of different phosphorus inputs ?
Renneson, Malorie ULg; Dufey, Joseph; Roisin, Christian et al

Poster (2013, September)

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See detailYield variability linked to climate uncertainty and nitrogen fertilisation
Dumont, Benjamin ULg; Basso, Bruno; Leemans, Vincent ULg et al

in Stafford, John V. (Ed.) Precision agriculture '13 (2013, July)

At the parcel scale, crop models such as STICS are powerful tools to study the effects of variable inputs such as management practices (e.g. nitrogen (N) fertilisation). In combination with a weather ... [more ▼]

At the parcel scale, crop models such as STICS are powerful tools to study the effects of variable inputs such as management practices (e.g. nitrogen (N) fertilisation). In combination with a weather generator, we built up a general methodology that allows studying the yield variability linked to climate uncertainty, in order to assess the best N practice. Our study highlighted that, applying the Belgian farmer current N practice (60 60 60 kgN.ha-1), the yield distribution was found to be very asymmetric with a skewness of -1.02 and a difference of 5% between the mean (10.5 t.ha-1) and the median (11.05 t.ha-1) of the distribution. Which implied that, under such practice, the probability for farmers to achieve decent yields, in comparison of the mean of the distribution, was the highest. [less ▲]

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