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See detailCharacterisation of Luvisol compaction under two different tillage systems and field traffic zones by assessing soil mechanical properties
Taguem Ngoualadjio, Eric Martial ULiege; Destain, Marie-France ULiege; ROISIN, Christian et al

Conference (2017, June 20)

Compaction of arable soils is a consequence of tillage systems and agricultural machinery traffic year after year. Its negative effects on crop production and on the environment have been put into ... [more ▼]

Compaction of arable soils is a consequence of tillage systems and agricultural machinery traffic year after year. Its negative effects on crop production and on the environment have been put into evidence by several studies. However, soil compaction is a complex phenomenon and the understanding of the involved mechanisms related to agricultural practices still remains limited. This contribution aims to study the influence of the interaction between traffic intensity and tillage system on soil compaction. Soil samples were taken from topsoil (0.07-0.25 m), plough pan (0.30-0.35 m) and subsoil (0.35 – 0.52 m), on plots under long-term reduced tillage (RT) and conventional tillage (CT). For each tillage system, intensive traffic zones (IT) and non-intensive traffic zones (NT) were considered. Swelling index (Cs), compression index (Cc), precompression stress (Pc) obtained by oedometer test, porosity (n) and water content obtained by gravimetric determination were chosen to characterise the soil mechanical properties. An analysis of covariance (ANCOVA) was performed to study the effect of the depth, the tillage and the traffic intensity on the variables measured, with the water content as covariable. The results show that, after ten years of reconversion from CT to RT, the plough pan is still present in RT and its compaction appears as important as in CT ( nRT-30cm = 36.9% , nCT-30cm = 38.0%, p-value = 0.098). In subsoil, the compression index was high in CT, as well as in RT (CcRT = 0.150 kPa-1, CcCT = 0.148 kPa-1, p-value = 0.617), involving that this layer remains susceptible to compaction under heavy loads. Moreover, the mean value of the precompression stress (meanPc = 92±34 kPa) remains lower than stresses induced by heavy machines such as beet harvesters. The results also show that the presence of two traffic zones induces a spatial heterogeneity in the field (CcIT = 0.138 kPa-1; CcNT = 0.154 kPa-1, p-value = 0.031). These main results could be used in computational modelling to develop decision support systems to mitigate the effects of soil compaction. [less ▲]

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See detailClassifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change
Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R. et al

in Agricultural Systems (2017)

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models ... [more ▼]

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities. [less ▲]

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See detailDetection of nitrogen stress on winter wheat by multispectral machine vision
Marlier, Guillaume ULiege; Gritten, Fanny; Leemans, Vincent ULiege et al

Conference (2016, August 01)

Hand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the ... [more ▼]

Hand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting nitrogen concentration. The tests were carried out on parcels submitted to nitrogen inputs varying from 0 to 180 kg N.ha-1. Reference Nc measurements were obtained by the Kjeldahl method and a Hydro N-Tester (Yara). The developed imaging system comprised a CMOS camera and a set of 22 interference filters ranging from 450 to 950 nm mounted on a wheel steered by a stepper motor. The image acquisition and the motor rotation were controlled by a program written in C++. The crop was imaged vertically at one meter height. The raw images presented 1280×1024 pixels covering an area of approximately 0.25 m² and were recorded with a 12-bit luminance resolution. To deal with the natural irradiance variability of the scene, a white reference was used and the integration time was automatically adjusted for each image. The image treatment included the segmentation of Photosynthetically Active Leaves (PAL) by using Bayes theorem and the computation of the mean PAL reflectance after correction of background and illumination fluctuations. Nc was estimated on the basis of the 22 filters by the Partial Least Square (PLS) method and by four filters selected by the Best Subset Selection (BSS) method. In comparison with the Kjeldahl method, the estimation of Nc by means of the Hydro N-Tester, the PLS method and the BSS method (filters 600-80, 950-100, 650-40 and 450-80 nm) gave determination coefficients equal to 0.53, 0.63, and 0.62, respectively. This indicated that the full multi-spectral approach gave significantly better Nc estimation than a portable device and suggested that a camera equipped with four filters would give similar results. [less ▲]

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See detailQuantification of nitrogen stress on winter wheat by multispectral vision based on reflectance measurements and textural descriptors
Marlier, Guillaume ULiege; Gritten, Fanny; Fraipont, Guillaume ULiege et al

Conference (2016, June 27)

Hand-held sensors (SPAD meter, N-Tester, …) are used for detecting the leaves nitrogen concentration (Nc) on the basis of an optical detection of the chlorophyll concentration. These devices are active ... [more ▼]

Hand-held sensors (SPAD meter, N-Tester, …) are used for detecting the leaves nitrogen concentration (Nc) on the basis of an optical detection of the chlorophyll concentration. These devices are active sensors: an internal radiation source emits light and transmission through a leaf is measured in the red (650 nm) and in the near-infrared (920 nm) spectral regions. These devices present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. In this context, the objective of the paper is to analyse the potential of different image parameters for estimating nitrogen concentration. The tests were carried out on parcels submitted to total nitrogen inputs of 180 kg N.ha-1 but with different fertilization modalities. Reference Nc measurements were obtained by the Kjeldahl method and a Hydro N-Tester (Yara). The developed imaging system comprised a CMos camera and a set of 22 interference filters ranging from 450 to 950 nm mounted on a wheel steered by a stepper motor. The image acquisition and the motor rotation were controlled by a program written in C++. The crop was imaged vertically at one meter height. The raw images presented 1280x1024 pixels covering an area of approximately 0.5x0.4 m and were recorded with a 12-bit luminance resolution. To deal with the natural irradiance variability of the scene, a white reference was used and the integration time was automatically adjusted for each image. The image treatment included the segmentation of Photosynthetically Active Leaves (PAL) by using Bayes theorem and the computation of the mean PAL reflectance after correction of background and illumination fluctuations. Nc was estimated on the basis of the 22 filters by Partial Least Square (PLS) method and by four filters selected by Best Subset Selection (BSS). In comparison with the Kjeldahl method, the estimation of Nc by the Hydro N-Tester, the PLS and the BSS (filters 600-80, 950-100, 650-40 and 450-80 nm) gave determination coefficient and standard error respectively equal to of 0.53, 0.29 %; 0.67, 0.21%; 0.56 and 0.25%. This indicated that the full multi-spectral approach gave significantly better Nc estimation than a portable device and suggested that a camera equipped with four filters would give similar results. In addition to these promising results, the Nc measurement were correlated to leaf area measurements and textural descriptors. For this purpose, image analysis based on Grey Level Co-occurrence Matrix (GLCM), Fourier transform and spatial autocorrelation were performed to characterize the nitrogen state of the crop. [less ▲]

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See detailSelection of wavelengths for the quantification of nitrogen concentration in winter wheat by multispectral vision
Marlier, Guillaume ULiege; Leemans, Vincent ULiege; Destain, Marie-France ULiege et al

Poster (2016, April 18)

Hand-held sensors (SPAD meter, N-Tester, …) are used for detecting the leaves nitrogen concentration (Nc) on basis of an optical detection of the chlorophyll concentration. These devices are active ... [more ▼]

Hand-held sensors (SPAD meter, N-Tester, …) are used for detecting the leaves nitrogen concentration (Nc) on basis of an optical detection of the chlorophyll concentration. These devices are active sensors: an internal radiation source emits light and transmission through a leaf is measured in the red (650 nm) and in the near-infrared (920 nm) spectral regions. These devices present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for detecting nitrogen concentration. The tests were carried out on parcels submitted to nitrogen inputs varying from 0 to 180 kg N.ha-1. Reference Nc measurements were obtained by the Kjeldahl method and a Hydro N-Tester (Yara). The developed imaging system comprised a CMos camera and a set of 22 interference filters ranging from 450 to 950 nm mounted on a wheel steered by a stepper motor. The image acquisition and the motor rotation were controlled by a program written in C++. The crop was imaged vertically at one meter height. The raw images presented 1280*1024 pixels covering an area approximately 0.5*0.4 m and were recorded with a 12 bits luminance resolution. To deal with the natural irradiance variability of the scene, a white reference was used and the integration time was automatically adjusted for each image. The image treatment included the segmentation of Photosynthetically Active Leaves (PAL) by using Bayes theorem and the computation of the mean PAL reflectance after correction of background and illumination fluctuations. Nc was estimated on basis of the 22 filters by Partial Least Square (PLS) method and by four filters selected by Best Subset Selection (BSS). In comparison with the Kjeldahl method, the estimation of Nc by the Hydro N-Tester, the PLS and the BSS (filters 600-80, 950-100, 650-40 and 450-80 nm) gave determination coefficient and standard error respectively equal to of 0.53, 0.29 %; 0.67, 0.21%; 0.56 and 0.25%. This indicated that the full multi-spectral approach gave significantly better Nc estimation than a portable device and suggested that a camera equipped with four filters would give similar results. [less ▲]

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See detailClassifying simulated wheat yield responses to changes in temperature and precipitation across a european transect
Fronzek, S.; Pirttioja, N.; Carter, T. R. et al

Conference (2016, March)

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See detailAssessing and modeling economic and environmental impact of wheat nitrogen management in Belgium
Dumont, Benjamin ULiege; Basso, Bruno; Bodson, Bernard ULiege et al

in Environmental Modelling & Software (2016), 79

Future progress in wheat yield will rely on identifying genotypes and management practices better adapted to the fluctuating environment. Nitrogen (N) fertilization is probably the most important practice ... [more ▼]

Future progress in wheat yield will rely on identifying genotypes and 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 and 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 and 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. [less ▲]

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See detailRisk assessment of soil compaction in the Walloon region in Belgium
D'Or, Dimitri; Destain, Marie-France ULiege

in Mathematical Geosciences (2016)

It is well known that soil compaction affects root growth and disrupts the activity of soil microfauna and microorganisms, resulting in yield loss. With the more intensive use of heavy machines in ... [more ▼]

It is well known that soil compaction affects root growth and disrupts the activity of soil microfauna and microorganisms, resulting in yield loss. With the more intensive use of heavy machines in agriculture and forestry, the risk of soil compaction is increasing. In this study, precompression stress (Pc) was chosen as an indicator of the susceptibility of soils to compaction and was calculated using pedotransfer functions (PTFs). PTFs involve eight variables related to the hydraulic and mechanical behaviour of soils: organic matter content; bulk density; air capacity; available water capacity; non-plant available water capacity; saturated hydraulic conductivity; cohesion; and angle of internal friction. Combining these PTFs with geostatistics and Monte Carlo simulations, Pc maps were produced at the regional scale for Wallonia in Belgium, accompanied by uncertainty quantification maps. These maps were then used to produce compaction risk maps based on common scenarios. The results showed that the modal Pc map was coherent with the spatial distribution of the main variables, namely soil texture and organic matter content. The risk maps enabled areas with a compaction risk in both agricultural and forestry contexts to be identified. These maps could be useful in drawing up soil protection measures and policies. [less ▲]

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See detailEffect of wheel traffic on the physical properties of a Luvisol
Destain, Marie-France ULiege; Roisin, Christian; Dalcq, Anne-Catherine ULiege et al

in Geoderma (2016), 262

The effects of machine traffic were assessed on a Luvisol in a temperate climate area in Belgium. Soil samples were taken from topsoil (0.07-0.25 m) and subsoil (0.35-0.50 m), on plots under long-term ... [more ▼]

The effects of machine traffic were assessed on a Luvisol in a temperate climate area in Belgium. Soil samples were taken from topsoil (0.07-0.25 m) and subsoil (0.35-0.50 m), on plots under long-term reduced tillage (RT) and conventional tillage (CT). Cone index (CI), bulk density (BD) and precompression stress (Pc) were chosen as indicators of mechanical strength. Mercury intrusion porosimetry was used to characterize the soil microporosity structure. It was presented in two forms: (i) cumulative pore volume vs. equivalent pore radius r, from which four classes of porosity were defined: r < 0.2 μm, 0.2 ≤ r < 9 µm, 9 ≤ r < 73 µm and r ≥ 73 μm; (ii) pore-size distribution (PSDs). In the reference situation where there had been no recent passage of machines, the voids with 0.2 ≤ r < 9 µm were the most important class in RT topsoil. The voids with r ≥ 73 µm represented the main porosity class in the topsoil of CT. In the subsoil, for both tillage systems, the porosity was almost equally distributed between voids with 0.2 ≤ r < 9 µm and voids with r greater than 9 µm. Machine traffic was carried out when the soil water content was close to the optimum Proctor. Although unfavourable, these wet conditions often occur during the beet harvesting period in Belgium. The highest modifications in soil structure (increase in BD and Pc, reduction of macroporosity r ≥ 73 μm) were observed in the topsoil of CT. More limited modifications were noticed in the soil structure of RT topsoil and subsoil layers but these latter are problematic in that the soil would no longer be loosened by subsequent tillage. These modifications could lead to soil consolidation as a result of wheel traffic year after year. [less ▲]

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See detailImpacts of wheel traffic on the physical properties of a Luvisol under reduced and conventional tillage
Saur, Marie-Laure ULiege; Destain, Marie-France ULiege; Roisin, Christian et al

Poster (2016)

Soil compaction is a complex mechanism which results in a decrease of soil porosity and an increase of soil strength. Such effects may reduce crop yield since they are harmful for root growth, germination ... [more ▼]

Soil compaction is a complex mechanism which results in a decrease of soil porosity and an increase of soil strength. Such effects may reduce crop yield since they are harmful for root growth, germination, mesofauna and bacterial life. Soil compaction may also reduce hydraulic conductivity which increases the risk of runoff, contamination of surface water, erosion and emission of greenhouse gases due to anaerobic processes. In the context of sustainable agriculture, it is crucial to characterise the impact of the agricultural techniques on the compaction state in the arable layer due to machine traffic. For this purpose, Soil samples were taken in a Luvisol at different depths, on plots under longterm reduced tillage (RT) and conventional tillage (CT). The impact of wheel traffic on the physical properties of the soils was also studied. The experimental approach consists in measuring traditional macroscopic soil properties such as bulk density and precompression stress, and combining them with pore size distribution obtained by mercury intrusion porosimetry. Automatic cone index measurements were initially performed to map the soil resistance and easily identify the sampling depths. The measurements revealed a plough pan at 30-cm depth under both CT and RT. Nevertheless, the subsoil under RT showed pieces of evidence of a natural regeneration process of the microporosity. The impact of wheel traffic was studied in RT and CT plots. It was shown that the passage of heavy machine such as beet harvester coupled to water content close to the optimum proctor is clearly unfavourable in terms of compaction. The measurements revealed large modifications of soil structure in the topsoil of CT, whereas the soil structure slightly changes through depth. However, the latter remains the more problematic case since the soil will not be loosened by tillage anymore, resulting in strongly compacted soil years after years. In addition to the experimental approach, numerical modelling was used in order to predict the soil compaction. A finite element method was used and the soil behaviour was modelled by an elastoplastic law (modified Cam-Clay model). The model parameters were calibrated from the experimental measurements. The simulations allowed to compare the porosity and the surface deformation after wheel traffic with the experiments. The variations of machine weight and tyre pressure were numerically studied and it was showed that the machine weight has an influence in the topsoil and the subsoil, whereas the tyre pressure affects only the topsoil. [less ▲]

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

in Precision Agriculture (2015), 16(4), 361-384

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 detailComparison of soil porosity structure under conventional and reduced tillage
Destain, Marie-France ULiege; Roisin, Christian; Marmi, Abdeljalil ULiege et al

Conference (2015, July)

The soil porosity structures under conventional (CT) and reduced tillage (RT) were compared on a Luvisol (Belgium) on a field experiment initiated in 2003. The total porosity n was computed from the bulk ... [more ▼]

The soil porosity structures under conventional (CT) and reduced tillage (RT) were compared on a Luvisol (Belgium) on a field experiment initiated in 2003. The total porosity n was computed from the bulk density (BD) and the microporosity structure was analysed by mercury intrusion porosimetry (MIP) in the range 0.003 to 73μm. It was presented in two forms: (i) cumulative pore volume vs equivalent pore radius r, from which four classes of porosity were defined: r < 0.2μm (microporosity); 0.2 ≤ r < 9µm (mesoporosity); 9 ≤ r < 73µm (MIP macroporosity); r ≥ 73μm (macroporosity); (ii) pore-size distribution (PSD). Besides the MIP measurements, the intrinsic behaviour of soil samples was investigated in one-dimensional compression tests. At 0.10m depth, n was 7% lower under RT than CT and corresponded mainly to a reduction of macroporosity r ≥ 73 μm which corresponds to pores in which water movement is important (P<0.05). The plough pan structure under CT was clearly different from other layers. It presented a higher precompression stress (Pc>160kPa) related to an increased proportion of small voids. When converting CT to RT, this compacted layer was still persistent after 10 years at 0.30m depth. With BD reaching 1.7Mgm-3, this layer could restrict the gas/water fluxes with negative environmental consequences. In the subsoil, n was similar under CT and RT (44%) but the porosity structure of RT was more favourable than under CT. Indeed, the macroporosity r ≥ 73 μm was 10% higher under RT than CT and the radius of the more represented pores was increased (3.2μm in RT versus 2.7μm in CT). This suggested that process of recovering the textural porosity due to long-term climatic and biological processes had begun in the subsoil of RT. [less ▲]

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See detailAdapting Nitrogen management to the increasing climatic uncertainty
Dumont, Benjamin ULiege; Basso, Bruno; Bodson, Bernard ULiege 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 detailA comparison of within-season yield prediction algorithms based on crop model behaviour analysis
Dumont, Benjamin ULiege; Basso, Bruno; Leemans, Vincent ULiege 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 detailClimatic risk assessment to improve nitrogen fertilisation recommendations : A strategic crop model-based approach
Dumont, Benjamin ULiege; Basso, Bruno; Bodson, Bernard ULiege 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 ULiege; Basso, Bruno; Bodson, Bernard ULiege et al

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

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See detailWheat yield sensitivity to climate change across a European transect for a large ensemble of crop models
Pirttioja, N.; Carter, Timothy; Fronzek, S. et al

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

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See detailA crop model ensemble analysis of temperature and precipitation effects on wheat yield across a European transect using impact response surfaces"
Pirttioja, Nina; Carter, Timothy; Fronzek, Stefan et al

in Climate Research (2015), 65

This study aims to explore the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and ... [more ▼]

This study aims to explore the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat (Triticum aestivum) yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect in Europe. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of 1981–2010 baseline daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour may depart markedly from the average, ensemble median responses across sites and crop varieties indicate that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields are more sensitive to temperature than precipitation changes at the Finnish site while sensitivities are mixed at the German and Spanish sites. Precipitation effects diminish under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development. [less ▲]

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See detailPredicting biomass and grain protein content using Bayesian methods
Mansouri, Majdi ULiege; Destain, Marie-France ULiege

in Stochastic Environmental Research & Risk Assessment (2015)

This paper deals with the problem of predicting biomass and grain protein content using improved particle filtering (IPF) based on minimizing the Kullback–Leibler divergence. The performances of IPF are ... [more ▼]

This paper deals with the problem of predicting biomass and grain protein content using improved particle filtering (IPF) based on minimizing the Kullback–Leibler divergence. The performances of IPF are compared with those of the conventional particle filtering (PF) in two comparative studies. In the first one, we apply IPF and PF at a simple dynamic crop model with the aim to predict a single state variable, namely the winter wheat biomass, and to estimate several model parameters. In the second study, the proposed IPF and the PF are applied to a complex crop model (AZODYN) to predict a winter-wheat quality criterion, namely the grain protein content. The results of both comparative studies reveal that the IPF method provides a better estimation accuracy than the PF method. The benefit of the IPF method lies in its ability to provide accuracy related advantages over the PF method since, unlike the PF which depends on the choice of the sampling distribution used to estimate the posterior distribution, the IPF yields an optimum choice of this sampling distribution, which also utilizes the observed data. The performance of the proposed method is evaluated in terms of estimation accuracy, root mean square error, mean absolute error and execution times. [less ▲]

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