References of "Leemans, Vincent"
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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 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 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 detailBayesian methods for predicting LAI and soil water content
Mansouri, Majdi ULg; Dumont, Benjamin ULg; Leemans, Vincent ULg et al

in Precision Agriculture (2014), 15(2), 184-201

LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was ... [more ▼]

LAI of winter wheat (Triticum aestivum L.) and soil water content of the topsoil (200 mm) and of the subsoil (500 mm) were considered as state variables of a dynamic soil-crop system. This system was assumed to progress according to a Bayesian probabilistic state space model, in which real values of LAI and soil water content were daily introduced in order to correct the model trajectory and reach better future evolution. The chosen crop model was mini STICS which can reduce the computing and execution times while ensuring the robustness of data processing and estimation. To predict simultaneously state variables and model parameters in this non-linear environment, three techniques were used: Extended Kalman Filtering (EKF), Particle Filtering (PF), and Variational Filtering (VF). The significantly improved performance of the VF method when compared to EKF and PF is demonstrated. The variational filter has a low computational complexity and the convergence speed of states and parameters estimation can be adjusted independently. Detailed case studies demonstrated that the root mean square error (RMSE) of the three estimated states (LAI and soil water content of two soil layers) was smaller and that the convergence of all considered parameters was ensured when using VF. Assimilating measurements in a crop model allows accurate prediction of LAI and soil water content at a local scale. As these biophysical properties are key parameters in the crop-plant system characterization, the system has the potential to be used in precision farming to aid farmers and decision makers in developing strategies for site-specific management of inputs, such as fertilizers and water irrigation. [less ▲]

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See detailASSESSMENT OF PLANT LEAF AREA MEASUREMENT BY USING STEREO- VISION
Leemans, Vincent ULg; Dumont, Benjamin ULg; Destain, Marie-France ULg

in 2013 International Conference on 3D Imaging (IC3D) - Proceedings (2013, December)

The aim of this study is to develop an alternative measurement for the leaf area index (LAI), an important agronomic parameter for plant growth assessment. A 3D stereo-vision technique was developed to ... [more ▼]

The aim of this study is to develop an alternative measurement for the leaf area index (LAI), an important agronomic parameter for plant growth assessment. A 3D stereo-vision technique was developed to measure both leaf area and corresponding ground area. The leaf area was based on pixel related measurements while the ground area was based on the mean distance from the leaves to the camera. Laboratory and field experiments were undertaken to estimate the accuracy and the precision of the technique. Result showed that, though the leaves-camera distance had to be estimated precisely in order to have accurate measurement, the precision of the LAI evaluation, after regression, was equivalent to the reference measurements, that is to say around 10% of the estimated value. This shows the potential of the 3D measurements compared with tedious reference measurements. [less ▲]

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See detailLeaf area and leaf orientation measurement by using stereo-vision
Leemans, Vincent ULg; Dumont, Benjamin ULg; Destain, Marie-France ULg

Conference (2013, September 03)

This paper presents a 3D stereo-vision system aiming at the measurement of plant characteristics. The method is intended to be used in an Ecotron where the availability of plant material is limited and ... [more ▼]

This paper presents a 3D stereo-vision system aiming at the measurement of plant characteristics. The method is intended to be used in an Ecotron where the availability of plant material is limited and where crop should be characterised non destructively. The plants were not considered as individuals, it was the crop as a whole that was characterised. The leaf area index (LAI) was measured. It is an important property of vegetation, since it determines the photosynthetic primary production, the plant evaporation and characterises the plant growth. The average leaf angle (ALA) was also measured. For the computation, leaf pixels were differentiated from soil pixels by using linear discriminant analysis. The stereo vision system computed the distance to the camera of each pixel in the image in the region where the pixels are present in both images. The observed area was computed on the basis of the average distance of the leaf pixels in the region. The leaf area was evaluated for each triplet of adjacent pixels by computing the cross product of the vectors defined by those three points. The sum gave the leaf area for the same region. The area of these triangles was summed for all the pixels in the region and the ratio to the observed area gave the LAI. The ALA was the mean orientation of the pixel triplets. After calibration, the method was found to present a coefficient of correlation of 0.93 with destructive reference measurements and a precision of 0.12 for the LAI. It was possible to measure the LAI and the ALA from the germination up to the ripening stage with a minimum of work load. [less ▲]

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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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See detailA Site-Specific Grain Yield Response Surface : Computing the Identity Card of a Crop Under Different Nitrogen Management Scenarios
Dumont, Benjamin ULg; Basso, Bruno; Leemans, Vincent ULg et al

in The acts of the EFITA2013 congress (2013, June)

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) fertilization). 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) fertilization). In combination with a weather generator, we propose a general methodology that allows studying the yield variability linked to climate uncertainty, in order to assess the best practices in applying fertilizers. Our study highlights that, using the usual practice of Belgian farmers, namely applying three doses of 60kgN/ha, the yield’s distribution presents the highest degree of asymmetry. This implies the highest probability to achieve yields superior to the mean. The computed return time of expected yield shows that 9 years out of 10, a grain yield of 7.26 tons.ha-1 could at least be achieved. [less ▲]

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See detailGame species monitoring using road–based distance sampling in association with thermal imagers: a covariate analysis
Morelle, Kevin ULg; Bouché, Philippe; Lehaire, François ULg et al

in Animal Biodiversity and Conservation (2012), 35(2), 253-265

Monitoring of game species populations is necessary to adequately assess culling by hunters in areas where natural large predators are absent. However, game managers have to control several species and ... [more ▼]

Monitoring of game species populations is necessary to adequately assess culling by hunters in areas where natural large predators are absent. However, game managers have to control several species and they often lack of an efficient and convenient survey design method. Monitoring several species at that same time over large areas could thus be cost– and time–effective. We tested the influence of several factors during monitoring of three common game species, (wild boar, roe deer and red fox, using road–based distance sampling in association with thermal imagers. This pilot survey based on 20 night counts in five contrasting sites studied the effect of several covariates (species, thermal imaging, observer, group size, and habitat type) on the detection probabilities. No differences were observed between thermal imagers and group sizes , but we found differences between observers . Expected differences were also observed between species and between habitat type. Our results show that the detectability of low cost thermal imaging equipment is similar to that of more expensive methods, highlighting new possibilities for the use of thermal imagery by game managers. Although adjustments should be made to the study design our findings suggest that large–scale multi–species monitoring could be an efficient method for common game species. [less ▲]

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See detailVers un système de prédiction du rendement en temps réel
Dumont, Benjamin ULg; Ferrandis Vallterra, Salvador ULg; Leemans, Vincent ULg et al

Poster (2012, October 16)

L'objectif de cette recherche est le développement d'un outil capable de prédire les rendements d'une culture de blé en temps réel, au fur et à mesure que la saison avance. Pour atteindre cet objectif ... [more ▼]

L'objectif de cette recherche est le développement d'un outil capable de prédire les rendements d'une culture de blé en temps réel, au fur et à mesure que la saison avance. Pour atteindre cet objectif, nous avons développé une méthodologie qui repose sur l'adjonction des éléments suivants : (i) le modèle de culture STICS (INRA, France), (ii) un réseau de capteurs sans fil pour le monitoring des variables agro-environnementales (éKo system, The Crossbow technologies, USA) et (iii) une base de données météorologiques. [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 Vallterra, Salvador ULg et al

in Proceedings of the 11th International Conference on Precision Agriculture (2012, July)

Real-time non-invasive determination of crop biomass and yield prediction are maybe among the major challenges in agriculture. But unknown future weather remains the key point of accurate yield forecast ... [more ▼]

Real-time non-invasive determination of crop biomass and yield prediction are maybe among the major challenges in agriculture. But unknown future weather remains the key point of accurate yield forecast. This paper presents the results of a preliminary study that aims to supply the unknown future by daily mean climatic data. The results show that under the Belgian weather, this approach is relevant. Furthermore, the developed methodology appears to be a powerful diagnosis tool of the remaining yield potential under ongoing weather. [less ▲]

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See detailA method for plant leaf area measurement by using stereo vision
Leemans, Vincent ULg; Dumont, Benjamin ULg; Destain, Marie-France ULg et al

in Proceedings of CIGR-AgEng 2012 International Conference on Agricultural Engineering (2012, July)

This paper presents a method for the measurement of LAI of wheat in situ. By using stereoscopic images a 3D map was computed. One colour image was segmented to identify plant regions and the 3D leaf area ... [more ▼]

This paper presents a method for the measurement of LAI of wheat in situ. By using stereoscopic images a 3D map was computed. One colour image was segmented to identify plant regions and the 3D leaf area was computed on these regions. The result showed that the precision was about the same as for the reference measurements but required a lesser workload. [less ▲]

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See detailA first step towards a real-time predictive yield support system.
Dumont, Benjamin ULg; Leemans, Vincent ULg; Ferrandis Vallterra, Salvador ULg et al

in Agriculture & Engineering for a Healthier Life (2012)

Real-time non-invasive determination of crop biomass and yield prediction are maybe among the major challenges in agriculture. But unknown future weather remains the key point of accurate yield forecast ... [more ▼]

Real-time non-invasive determination of crop biomass and yield prediction are maybe among the major challenges in agriculture. But unknown future weather remains the key point of accurate yield forecast. This paper presents the results of a preliminary study that aims to supply the unknown future by daily mean climatic data. The results show that, under the Belgian weather, this approach is relevant. Furthermore, the developed methodology appears to be a powerful diagnosis tool of the remaining yield potential under ongoing weather. [less ▲]

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See detailAutomatic grading of Bi-colored apples by multispectral machine vision
Unay, Devrim; Gosselin, Bernard; Kleynen, Olivier et al

in Computers & Electronics in Agriculture (2011)

In this paper we present a novel application work for grading of apple fruits by machine vision. Following precise segmentation of defects by minimal confusion with stem/calyx areas on multispectral ... [more ▼]

In this paper we present a novel application work for grading of apple fruits by machine vision. Following precise segmentation of defects by minimal confusion with stem/calyx areas on multispectral images, statistical, textural and geometric features are extracted from the segmented area. Using these features, statistical and syntactical classifiers are trained for two- and multi-category grading of the fruits. Results showed that feature selection provided improved performance by retaining only the important features, and statistical classifiers outperformed their syntactical counterparts. Compared to the state-of-the-art, our two-category grading solution achieved better recognition rates (93.5% overall accuracy). In this work we further provided a more realistic multi-category grading solution, where different classification architectures are evaluated. Our observations showed that the single-classifier architecture is computationally less demanding, while the cascaded one is more accurate. [less ▲]

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See detailEvaluation of the performance of infrared thermography for on-line condition monitoring of rotating machines
Leemans, Vincent ULg; Destain, Marie-France ULg; Kilundu, Bovic et al

in Engineering (2011), (3), 1030-1039

This study evaluated the possibility of infrared thermography to measure accurately the temperature of elements of a rotating device, within the scope of condition monitoring. The tested machine was a ... [more ▼]

This study evaluated the possibility of infrared thermography to measure accurately the temperature of elements of a rotating device, within the scope of condition monitoring. The tested machine was a blower coupled to a 500 kW electric motor, that operated in multiples regimes. The thermograms were acquired by a fixed thermographic camera and were processed and recorded every 15 minutes. Because the normal temperature variations could easily mask a drift caused by a failure, a corrected temperature was computed using autorecursive models. It was shown that an efficient temperature correction should compensate for the variations of the process, and for the ambient temperatures variations, either daily or seasonal. The standard deviation of the corrected temperature was of a few tenth of degree, making possible the detection of a drift of less than one degree and the prediction of potential failure. [less ▲]

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See detailREAL-TIME MONITORING OF ENVIRONMENTAL FACTORS TO MODEL WHEAT YIELD PRODUCTION
Dumont, Benjamin ULg; Leemans, Vincent ULg; Lebeau, Frédéric ULg et al

Poster (2010, September 07)

This paper presents the results of a one year preliminary study in which a real-time monitoring system was used to feed the STICS soil crop model. The monitoring system was made of a self-organising ... [more ▼]

This paper presents the results of a one year preliminary study in which a real-time monitoring system was used to feed the STICS soil crop model. The monitoring system was made of a self-organising wireless network within which microsensors collected and stored microclimatic and environmental data. As indicated by the statistical criteria (RMSE, normalized deviation and model efficiency), the optimisation of some wheat crop parameters allows the STICS model to predict the yields with good accuracy for three different soil types and seven different nitrogen application rates. [less ▲]

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See detailA sorting optimization curve with quality and yield requirements
Ooms, David ULg; Palm, Rodolphe ULg; Leemans, Vincent ULg et al

in Pattern Recognition Letters (2010), 31(9), 983-990

Binary classifiers used for sorting can be compared and optimized using receiver-operating characteristic (ROC) curves which describe the trade-off between the false positive rate and true positive rate ... [more ▼]

Binary classifiers used for sorting can be compared and optimized using receiver-operating characteristic (ROC) curves which describe the trade-off between the false positive rate and true positive rate of the classifiers. This approach is well suited for the diagnosis of human diseases where individual costs of misclassification are of great concern. While it can be applied to the sorting of merchandise or other materials, the variables described by the ROC curve and its existing alternatives are less relevant for that range of applications and another approach is needed. In this paper, quality and yield factors are introduced into a sorting optimization curve (SOC) for the choice of the operating point of the classifier, associated with the prediction of output quantity and quality. Given examples are the sorting of seeds and apples with specific requirements. In both cases the operating point of the classifier is easily chosen on the SOC, while the output characteristics of the sorted product are accurately predicted. [less ▲]

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See detailSurveillance en ligne d'une machine tournante par thermographie infrarouge
Leemans, Vincent ULg; Destain, Marie-France ULg

Conference (2009, December 07)

Des mesures par thermographie d'une machine tournante critique (ventilateur) sont réalisées en ligne pour évaluer la température d’organes, comme le moteur et les paliers. En conditions de fonctionnement ... [more ▼]

Des mesures par thermographie d'une machine tournante critique (ventilateur) sont réalisées en ligne pour évaluer la température d’organes, comme le moteur et les paliers. En conditions de fonctionnement normal, les températures montrent des variations importantes, caractérisées par un écart­-type de l’ordre de 5 °C. Elles sont liées aux variations de conditions climatiques et à l'apport de chaleur variable en fonction du processus de fabrication. Un modèle auto­récurrent avec grandeurs d'entrée (ARX) a permis d'éliminer ces variations. Le bruit sur la température corrigée est réduit à un degré Celsius, ce qui permet de mettre en évidence très tôt une dégradation au niveau des paliers principaux. Par contre, dans le cas présent, le moteur subit un encrassement et donc une augmentation de température en cours de fonctionnement qui masque l’existence d’une éventuelle détérioration. [less ▲]

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