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See detailOptimisation de l'utilisation des ressources en eau du bassin du Kou pour des usages agricoles
Traore, Farid ULg; Dembélé, Youssouf; Tychon, Bernard ULg

Scientific conference (2010, May 28)

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See detailBulletin agrométéorologique - Situation au 30 avril 2010
Tychon, Bernard ULg; Djaby, Bakary ULg; Denis, Antoine ULg et al

in Bulletin Agrométéorologique (2010), 8(1), 1-4

La période hivernale fut caractérisée par des températures inférieures aux moyennes des 20 dernières années. L’hiver fut également marqué par d’abondantes chutes de neige. Les sommes de températures ... [more ▼]

La période hivernale fut caractérisée par des températures inférieures aux moyennes des 20 dernières années. L’hiver fut également marqué par d’abondantes chutes de neige. Les sommes de températures calculées depuis le début du mois de janvier sont inférieures d’environ 170 degrés.jours par rapport à la situation moyenne, ce qui signifie un retard moyen des cultures d’une bonne semaine, voire davantage. Les images satellites montrent cependant que ce retard calculé à partir du cumul de températures serait en grande partie rattrapé fin avril. En dehors du retard phénologique calculé par une de nos deux méthodes, aucun autre élément agrométéorologique important n’est à signaler. Aucune prévision de rendement n’est faite à ce stade. [less ▲]

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See detailClimatological characteristics of NDVI time series: challenges and constraints
Horion, Stéphanie; Tychon, Bernard ULg; Cornet, Yves ULg

in Bulletin de la Société Géographique de Liège (2010), 54

Many studies already investigated the impact of climate change and climate variability on vegetation at global and continental scales. Low resolution satellite imagery is one of the main sources of ... [more ▼]

Many studies already investigated the impact of climate change and climate variability on vegetation at global and continental scales. Low resolution satellite imagery is one of the main sources of information. In this paper, we describe a strategy to improve the quality of 10-daily time series of Normalized Difference Vegetation Index derived from SPOT-VEGETATION. A specifi c methodology was also defi ned in order to identify optimal test sites for the analysis of climate control on intra-annual dynamic of croplands. Finally two cases studies are presented to illustrate this research and in particular the non linear relationship between NDVI and meteorological parameters during the growing season. [less ▲]

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See detailUtilisation des prises de vue aérienne à basse altitude pour le suivi des activités hydro-agricoles. Cas du bassin du Kou.
Wellens, Joost ULg; Diallo, M.; Dakouré, D. et al

Conference (2010, March)

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See detailPromouvoir des approches innovantes de recherche-développement en matière de GIRE au Burkina Faso.
Wellens, J.; Diallo, M.; Gardin, N. et al

Conference (2010, March)

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See detailRemote sensing assessement of irrigated areas extension in the Kou watershed
Traore, Farid ULg; Tychon, Bernard ULg

Scientific conference (2010, January 12)

The Kou watershed is a geographical space having important water resources, whose are used between: drinking water supply of Bobo-Dioulasso city (Burkina-Faso’s second most important city) and surrounding ... [more ▼]

The Kou watershed is a geographical space having important water resources, whose are used between: drinking water supply of Bobo-Dioulasso city (Burkina-Faso’s second most important city) and surrounding localities; agriculture through very important irrigated surfaces; industry; fauna and flora preservation, through a minimal sanitary debit guaranteed. Since some decades, one observes more and more increased pressure on Kou water resources. From an agricultural point of view, a comparative visual observation of irrigated surfaces during the years 1980 and during years 2000 shows an increase of surfaces. It would be then appropriate to establish a potential of irrigation of the set of available water resources in order to estimate maximal irrigable surfaces by water resources. Thus, this study has for goal the evaluation of Kou watershed irrigated zones surface, with the help of remote sensing. In order to facilitate irrigated zones detection, the study will focused on the period between January and June, where all cultures are irrigated with Kou watershed surface water and/or groundwater. The chosen methodology is images classification in order to extract irrigated zones surface. We had for this study a set of images and various data: Landsat-4 TM, Landsat-5 TM, Landsat-7 ETM+, SPOT 5, aerial views, agro meteorological data, cartographic data (GIS), data investigation reports, etc. Because of images various origins, we conducted images pretreatment that essentially consisted in image reflectance calibration. This operation appears to be indispensable when working with images from coming different sensors. Classification methods that we used are: a maximum likelihood classification, then a decision tree classification applied to images for which vegetation index (NDVI) has been calculated. The later classification method has been introduced in order to permit a better discrimination between natural vegetation and crops which can often react in similar spectral ranges. This method is based on threshold detection of vegetation classes. Classification methods used allowed us to estimate until a certain point irrigated surfaces, without having, however, a finer information. With 30 m spatial resolution images covering a survey zone with "reduced" to "mean" agricultural lands size, it is sometimes enough difficult to discern natural vegetation pixels from crop pixels. So, we should have considered mixed classes of pixels that strongly skewed our final results. The overall accuracy of our classifications are between 70% and 90%, with Kappa coefficients between 0.4 and 0.85. These Kappa coefficients our results between "tolerable" and "good". However, our evaluations seem to be near enough of those gotten by the means of hydro agricultural inventories led on the same zone. The committed mistakes remain in an interval of +/-20%. [less ▲]

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See detailMEASURING SOIL ORGANIC CARBON IN CROPLANDS AT REGIONAL SCALE USING AIRBORNE IMAGING SPECTROSCOPY
Stevens, Antoine; Udelhoven, Thomas; Denis, Antoine ULg et al

in Geoderma (2010), 158

Conventional sampling techniques are often too expensive and time consuming to meet the amount of data required in soil monitoring or modelling studies. The emergence of portable and flexible ... [more ▼]

Conventional sampling techniques are often too expensive and time consuming to meet the amount of data required in soil monitoring or modelling studies. The emergence of portable and flexible spectrometers could provide the large amount of spatial data needed. In particular, the ability of airborne imaging spectroscopy to cover large surfaces in a single campaign and to study the spatial distribution of soil properties with a high spatial resolution represents an opportunity for improving the monitoring of soil characteristics and soil threats such as the decline of soil organic matter in the topsoil. However, airborne imaging spectroscopy has been generally applied over small areas with homogeneous soil types and surface conditions. Here, five hyperspectral images acquired with the AHS-160 sensor (430 nm–2540 nm) were analysed with the objective to map soil organic carbon (SOC) at a regional scale. The study area, covering a surface of ∼420 km2 and located in Luxembourg, is characterized by different soil types and a high variation in SOC contents. Reflectance data were related to surface SOC contents of bare croplands by means of 3 different multivariate calibration techniques: partial least square regression (PLSR), penalized-spline signal regression (PSR) and support vector machine regression (SVMR). The performance of these statistical tools was tested under different combinations of calibration/validation sets (global and local calibrations stratified according to agro-geological zones, soil type and image number). Under global calibration, the Root Mean Square Error in the Predictions reached 5.3–6.2 g C kg−1. Under local calibrations, this error was reduced by a factor up to 1.9. SOC maps of bare agricultural fields were produced using the best calibration model. Two map excerpts were shown, which display intra- and inter-field variability of SOC contents possibly related to topography and land management. [less ▲]

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See detailWheat yield and PAI decreasing shape curve
Kouadio, Amani Louis ULg; Tychon, Bernard ULg

Conference (2010, January)

Estimation of cereal-crop production is considered as a priority in most crop research programmes due to the relevance of food grain to world agricultural production. Today, a large number of ... [more ▼]

Estimation of cereal-crop production is considered as a priority in most crop research programmes due to the relevance of food grain to world agricultural production. Today, a large number of agrometeorological models for crop yield assessment are available with various levels of complexity and empiricism. A preliminary study was performed with simulated data of wheat yield and LAI derived from the WOFOST/CGMS agrometeorological model. The main hypothesis underlying this study is that it’s possible to improve wheat yield estimates from metrics stretched from LAI decreasing curves. This preliminary study showed that wheat yield can be estimated by metrics stretched from simulated LAI curve-fitting done by a modified Gompertz function [G =A*exp (-exp(-k(t-m)))] and a logistic function [G = A / 1+exp(-k(t-m)); where G is the green LAI (gLAI), A the initial percentage of LAI, m the position of the inflexion point in the decreasing part of the LAI curve and k the relative senescence rate. In 2009 a large field campaign in the Grand-Duchy of Luxembourg and France was done to check the validity of such approach with field data. Hemispheric images were taken on 18 winter wheat fields during the crop cycle, preferentially from inflorescence emergence to maturity. The variable of interest, green PAI (Plant Area Index), was retrieved after analyses of images by the CAN-EYE software (v. 6.1). Data used as input to establish the model of wheat yield estimate are the value of observed PAImax, and metrics k and m, stretched from observed PAI curves fitted by Gompertz and logistic functions. The model obtained by multilinear regression with these variables reveals that wheat yield can be estimated, at the scale of the plot, with a r² ≈ 0.70 and a RMSE = 0.87 t/ha (RRMSE = 9%). The validation of such approach at the scale of an agricultural zone or region will be performed in the next step of our study, by using remote sensing data (air temperature, PAI or LAI) and phenology data as input. Such simple models may be considered as a first yield estimates that may be completed, if justified, by other agrometeorological models in order to provide a better integrated yield assessment. [less ▲]

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See detailAppropriation et vulgarisation d'outils d'aide à la décision dans la co-gestion du périmètre irrigué de la Vallée du Kou (sud-ouest du Burkina Faso)
Wellens, Joost ULg; Nitcheu, Martial; Diallo, Mamadou et al

Report (2010)

Dans le cadre d’un programme national de sécurité alimentaire datant des années 60, un périmètre rizicole irrigué de 1.200 ha, appelé la Vallée du Kou, a été établi dans le Sud-ouest du Burkina Faso (Bama ... [more ▼]

Dans le cadre d’un programme national de sécurité alimentaire datant des années 60, un périmètre rizicole irrigué de 1.200 ha, appelé la Vallée du Kou, a été établi dans le Sud-ouest du Burkina Faso (Bama). Long temps conjointement géré par l’Etat et toute une série d’agences d’aide au développement, tout appui s’est brutalement arrêté en 1993 laissant les agriculteurs à peine préparé pour assumer la relève de la gestion. Le résultat : un ancien beau périmètre succombe dans un théâtre typique de gestion anarchique. Différentes structures de coopératives ont tenté depuis, de gérer leur petite part du périmètre passant outre aux règles et sans aucun respect pour leurs voisins. Les travaux de maintenance avaient disparu, les récoltes étaient en baisses et l’eau disponible ne satisfaisaient plus aux besoins laissant presque un quart des champs en jachères. Observant l’état de plus en plus dégradé du périmètre et conscient de leurs faibles capacités de gestion, l’Union des Coopératives Rizicole de Bama (UCRB) s’est finalement adressée à un opérateur externe (AEDE), expérimenté dans le domaine de l’eau et de l’agriculture, pour obtenir un appui. Cette assistance est déployée à deux niveaux. Premièrement, l’installation d’un conseiller permanent en irrigation sur le périmètre intervenant comme appui technique auprès des agriculteurs et chargé d’établir un inventaire technique et objectif sur l’état du périmètre et de sa gestion. Deuxièmement, des études plus techniques ont été établies afin de quantifier les problèmes de gestion et de proposer des solutions en termes d’occupations des parcelles et de distribution d’eau plus durables. Ceci a notamment nécessité la mise en place et l’application de l’outil de gestion de périmètre irrigué SIMIS. A travers les différentes étapes, des réunions participatives ont été organisées au niveau de l’union des coopératives ainsi qu’au niveau des différentes coopératives. Les producteurs ont été écoutés, et des plans et solutions proposés et discutés. Si nécessaire, des compromis étaient cherchés et représentés pour approbation. Quelques mois seulement après la mise en place de cet appui-conseil, une augmentation de l’occupation des parcelles dans le périmètre a été constatée et une distribution en eau plus équitable enregistrée. Côté producteurs, une satisfaction générale a été notée et ils souhaitent à présent s’engager davantage dans cette gestion externe du périmètre. D’autres périmètres ont également manifesté leur intérêt. [less ▲]

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See detailModelling climate control on cropland and grassland development using phenologically tuned variables
Horion, Stéphanie; Tychon, Bernard ULg; Cornet, Yves ULg

in Geophysical Research Abstracts (2010), 12

Many studies already investigated the impact of climate change and climate variability on vegetation at global and continental scales. Using time series of remote sensing and climate data, Nemani et al ... [more ▼]

Many studies already investigated the impact of climate change and climate variability on vegetation at global and continental scales. Using time series of remote sensing and climate data, Nemani et al. (2003) analyzed trends in Net Primary Production in relation with changes in climate and showed that, between 1982 and 1999, primary productivity increased by 6% globally in response to climate change. This study also stressed the need to take into account the spatial variability of climatic constraints to plant growth when analyzing the climate change impact on vegetation. Others authors described different phenomenon linked with climate change such as increases of seasonal NDVI amplitude and growing season duration in the Northern high latitude or changes in circumpolar photosynthetic activities. Understanding the interactions between climate and vegetation is also a key issue in our PhD research. Our objective is to identify the meteorological factors which limit the development of croplands and grasslands in relation with their geographical localization. For that purpose, we acquired 10-daily time series of the Normalized Difference Vegetation Index, NDVI, derived from SPOT-VEGETATION and 7 meteorological parameters (Tmean, Tmin, Tmax, Rain, Rad, ETP, Rain-ETP) derived from ERA40 re-analyses and the operational ECMWF (European Centre for Medium-Range Weather Forecast) atmospheric model. Cross-correlations between NDVI and each one of the meteorological parameters were analysed for a set of 25 regions over Europe and Africa: 15 agricultural regions and 10 regions covered by grassland or savannas. Unlike others studies, we did not consider the vegetation globally but we focussed on two types of vegetation: croplands and grasslands. This is quite important considering the role of phenology on the vegetation cycle and its relation with climate. Moreover the analysis was not realised using yearly estimates but using 10-daily products. In order to avoid stationarity related issue, a specific methodology was developed taking into account the phenological cycle of the vegetation under consideration. Preliminary results showed that the relation between a meteorological limiting factor, e.g. precipitation, and NDVI can not be considered as linear during the year or even during the growing season. Interactions must to be studied at a smaller time scale than the growing season in order to identify properly the limiting factors to plant growth taking into account its phenology. Moreover the main limiting factors are variable from a region to another. In our analysis we also considered the possibility of a delayed response of the vegetation or a cumulated effect of meteorological events (up to 3 months). Our methodology will be presented during the conference and results will be discussed and illustrated by some test cases. [less ▲]

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See detailCombining remote sensing imagery of both fine and coarse spatial resolution to estimate crop evapotranspiration and quantifying its influence on crop growth monitoring
Sepulcre-Canto, Guadalupe; Gellens-Meulenberghs, Françoise; Arboleda, Alirio et al

in Geophysical Research Abstracts (2010)

This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the ... [more ▼]

This study has been carried out in the framework of the GLOBAM -Global Agricultural Monitoring system by integration of earth observation and modeling techniques- project whose objective is to fill the methodological gap between the state of the art of local crop monitoring and the operational requirements of the global monitoring system programs. To achieve this goal, the research aims to develop an integrated approach using remote sensing and crop growth modeling. This paper concerns the use of MSG geostationnary satellite data for the calculation of Actual Evapotranspiration and its integration into a crop growth model. [less ▲]

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See detailChapter 6 : Agrometeorological forecasting
Gommes, René; Das, Haripada; Mariani, Luigi et al

in WMO/CAgM Guide to Agricultural Meteorological Practices (GAMP) WMO n° 134 (2010)

This chapter presents a set of tools and techniques for crop yield forecasting.

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See detailDésertification des parcours arides au Maroc
Mahyou, Hamid ULg; Tychon, Bernard ULg; Balaghi, Riad et al

in Tropicultura (2010), 28(2), 107-114

Rangeland or natural arid pastures of Morocco are ecosystems where there is a natural or seminatural vegetation composed of steppes, shrubs and grassland. They cover about 82% of the Moroccan arid lands ... [more ▼]

Rangeland or natural arid pastures of Morocco are ecosystems where there is a natural or seminatural vegetation composed of steppes, shrubs and grassland. They cover about 82% of the Moroccan arid lands. These areas represent livelihoods for thousands of people and protect the country from desertification. Despite the importance of the rangelands and the threat of desertification, it is surprising that up to date there is no comprehensive assessment of their condition and their evolution, hindering any plan for desertification alleviation. However, the available information on selected pilot areas shows that these rangelands are threatened by desertification. It’s associated with biodiversity loss and contributes to climate change. The leading causes of land degradation are the human actions combined with climate. The establishment of a comprehensive surveillance system based on remote sensing, biophysics and socio-economic data must be envisaged to provide policymakers with an operational tool adapted to the spatio-temporal monitoring of desertification. [less ▲]

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See detailManaging climatic risks for enhanced food security : key information capabilities
Balaghi, Riad; Badjeck, M.-C.; Djaby, Bakary ULg et al

in Procedia Environmental Sciences (2010), 1

Food security is expected to face increasing challenges from climatic risks that are more and more exacerbated by climate change, especially in the developing world. This document lists some of the main ... [more ▼]

Food security is expected to face increasing challenges from climatic risks that are more and more exacerbated by climate change, especially in the developing world. This document lists some of the main capabilities that have been recently developed, especially in the area of operational agroclimatology, for an efficient use of natural resources and a better management of climatic risks. Many countries, including the developing world, now benefit from well-trained staff in the use of climate data, physical and biological information and knowledge to reduce negative climate impacts. A significant volume of data and knowledge about climate–agriculture relationships is now available and used by students, scientists, technicians, agronomists, decision-makers and farmers alike, particularly in the areas of climate characterization, land suitability and agroecological zoning, seasonal climate forecasts, drought early warning systems and operational crop forecasting systems. Climate variability has been extensively modelled, capturing important features of the climate through applied statistical procedures, agroclimatic indices derived from raw climatic data and from remote sensing. Predictions of climate at seasonal to interannual timescales are helping decision-makers in the agricultural sector to deal more effectively with the effects of climate variability. Land suitability and agroclimatic zoning have been used in many countries for agricultural planning, thanks to the availability of new and comprehensive methodologies; developments in climate, soil and remote sensing data collection and analysis; and improved applications in geographic information systems (GIS). Drought early warning systems are available worldwide at both national and international levels. These systems are helping decisionmakers and farmers to take appropriate decisions to adapt to short-term climatic risks. Also, operational crop forecasting systems are now becoming available at the regional and national levels. In some developed countries, several efficient and well tested tools are now available for optimizing on-farm decisions based on the combination of crop simulation models and seasonal forecasts. However, in developing countries few tools have been developed to efficiently manage crops at the farm level to cope with climate variability and climate risks. Climate change impacts on agriculture and food security have been assessed in international studies using specific and efficient methodologies and tools. Adaptation to climate change and variability can also be facilitated through effective planning and implementation of strategies at the political level. The role of technological progress, risk transfer mechanisms and financial instruments and their easy accessibility to rural people are critical elements of climate risk management. [less ▲]

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See detailExploring the potential of crop specific green area index time series to improve yield estimation at regional scale
Duveiller, Gregory; de Wit, Allard; Kouadio, Amani Louis ULg et al

in Sobrino, J. A. (Ed.) Proceedings of the 3rd International Symposium on Recent Advances in Quantitative Remote Sensing (RAQRS'III) (2010)

Crop status, such as the Green Area Index (GAI), can be retrieved from satellite observations by modelling and inverting the radiative transfer within the canopy. Providing such information along the ... [more ▼]

Crop status, such as the Green Area Index (GAI), can be retrieved from satellite observations by modelling and inverting the radiative transfer within the canopy. Providing such information along the growing season can potentially improve crop growth modelling and yield estimation. However, such approaches have proven difficult to apply on coarse resolution satellite data due to the fragmented land cover in many parts of the World. Advances in operational crop mapping will sooner or later allow the production of crop maps relatively early in the crop growth season, thereby providing an opportunity to sample pixels from medium/coarse spatial resolution data with relatively high cover fraction of a particular crop type to derive crop specific GAI time series. This research explores how to use such time series derived from MODIS to produce indicators of crop yield using two approaches over part of Belgium. The first method consists in looking at metrics of the decreasing part of the GAI curves when senescence occurs. Such metrics, like the position of the inflexion point, have been shown to be significantly correlated to yield. The second approach is to optimize the WOFOST model used in the European Crop Growth Monitoring System (CGMS) based on the GAI time series. Results show that, although the optimized model shows considerably better performance than the model running on the default parameter, the model is sometimes outperformed by the simpler metric approach. In all cases, indicators including remote sensing information provide better estimates that the average yield of previous years. [less ▲]

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See detailGMFS Final report Stage 1 and Stage 2
Gilliams, Sven; Bydekerke, Lieven; Delrue, Josefien et al

Report (2009)

Global Monitoring for Food Security (GMFS) is a Global Monitoring for Environment and Security (GMES) Service Element (GSE) project, part of the European Space Agency (ESA) contribution to the European ... [more ▼]

Global Monitoring for Food Security (GMFS) is a Global Monitoring for Environment and Security (GMES) Service Element (GSE) project, part of the European Space Agency (ESA) contribution to the European Union (EU) /ESA GMES Programme. GMFS aims to establish an operational service for crop monitoring in support of Food Security Monitoring to serve policy makers and operational users. The GMFS project started in March 2003 as part of Stage 1 of the ESA Earthwatch GMES services Element “Service Consolidation Actions”, and was continued in October 2005 as part of the Stage 2 of the ESA Earth watch GMES services Element – “Scaling Up Consolidated GMES Services”. In this document an overview is given of the work done throughout the previous six years. GMFS aimed at monitoring crop state /vegetation condition at continental and national scale. Low resolution Earth Observation (EO) data was used for monitoring purposes at continental scale, while at national scale products were based upon medium and high resolution data, field work and agro-meteorological models. The project was guided by a project strategy group with members from the United States Agency for International Development - Famine Early Warning System Network (USAID-FEWSNET), Directorate General for Development (DG-DEV), Consultative Group on International Agricultural Research - International Wheat Improvement Center (CGIAR-CIMMYT), European Commission Joint Research Center (EC-JRC), United Nations World Food Programme (WFP) and United Nations Food and Agricultural Organisation (FAO). The goal of the project in Stage 1 (March 2003 –November 2004) was to consolidate an early warning system for food security. This started off by an intensive literature review and setting up an initial service for the Centre de Suivi Ecologique (CSE) in Dakar Senegal. In the second Phase of Stage 1 activities focussed more on the actual service delivery and setting up activities with users. Those activities included the monitoring agricultural production for Senegal, monitoring agriculture in Malawi and giving support to the Crop and Food Supply Assessment Mission (CFSAM) of FAO /WFP. Additionally, services were set up for the centre Agro-Hydro-Météorologique (AGRHYMET) as a result of a meeting between AGHRYMET and Vlaamse Instelling voor Technologisch Onderzoek (VITO). During 2005 the early warning service was continued to support GMFS users although there was at that time no formal contract to do so. At the start of the Second Stage, in October 2005, a GMFS user executive board, consisting of one representative from: EC-JRC, FAO, WFP, Southern Africa Development Community Regional Remote Sensing Unit (SADC-RRSU), Regional Centre for Mapping of Resources for Development (RCMRD) and AGRHYMET, was set up to support the consortium in defining the correct services and to review the work. Since the focus for the Second Stage was on up scaling the consolidated services, it was decided that the early warning service and support to the CFSAM were to be continued, the agricultural mapping service was to be expanded to more countries - namely, Senegal, Sudan, Ethiopia, Malawi and Zimbabwe - and extra services on yield modeling using remote sensing and agro-meteorological models were to be provided. During the second year of this stage, the services were even more extended with, support to the Ministry of Agriculture and Meteorological Department in Mozambique, extra activities in Ethiopia and Sudan and support to the regional centers on operational use of the ESA Data Dissemination System (DDS). [less ▲]

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See detailAssessing the Accuracy of Simulation Model for Septoria Leaf Blotch Disease Progress on Winter Wheat.
El Jarroudi, Moussa ULg; Delfosse, Philippe; Maraite, Henri et al

in Plant Disease (2009), 93

A mechanistic model, PROCULTURE, for assessing the development of each of the last five leaf layers and the progress of Septoria leaf blotch, caused by Septoria tritici (teleomorph Mycosphaerella ... [more ▼]

A mechanistic model, PROCULTURE, for assessing the development of each of the last five leaf layers and the progress of Septoria leaf blotch, caused by Septoria tritici (teleomorph Mycosphaerella graminicola), has been applied on susceptible and weakly susceptible winter wheat (Triticum aestivum) cultivars in two locations (Everlange and Reuland) in Luxembourg over a 3-year period (2000 to 2002). A double performance assessment of PROCULTURE was conducted in this study. First, the capability of PROCULTURE to correctly simulate S. tritici incidence was checked. Second, the model's ability to accurately estimate disease severity was assessed on the basis of the difference between simulated and observed levels of disease development at each leaf layer. The model accurately predicted disease occurrence in the 2000 and 2002 seasons, on susceptible and semi-susceptible cultivars, with a probability of detection (POD) exceeding 0.90. However, in 2001, even though the POD never fell below 0.90, the false alarm ratio (FAR) was too high to consider the simulations satisfactory. Concerning the evaluation of disease severity modeling, statistical tests revealed accurate simulations performed by PROCULTURE for susceptible cultivars in 2000 and 2002. By contrast, for weakly susceptible cultivars, the model overestimated disease severity, especially for the upper leaves, for the same period. [less ▲]

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See detailBulletin agrométéorologique - Situation au 31 août 2009
Tychon, Bernard ULg; Scohy, Laureline; Denis, Antoine ULg et al

in Bulletin Agrométéorologique (2009), 7(3), 1-4

Les conditions atmosphériques de juillet et août ont permis aux cultures d’hiver de boucler leurs cycles dans d’excellentes conditions. Pour les cultures de printemps par contre, le mois d’août chaud et ... [more ▼]

Les conditions atmosphériques de juillet et août ont permis aux cultures d’hiver de boucler leurs cycles dans d’excellentes conditions. Pour les cultures de printemps par contre, le mois d’août chaud et sec aura pu accélérer la sénescence et créer ça et là des stress hydriques en particulier pour le maïs et la pomme de terre qui sont plus sensibles à la sécheresse que la betterave. Les rendements prédits pour la pomme de terre sont en-dessous de la moyenne, ils sont proches de la moyenne pour le maïs tandis qu’ils sont largement supérieurs pour la betterave. Des différences parfois importantes sont simulées entre les différentes régions agricoles. [less ▲]

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See detailSIMIS: Scheme Irrigation Management Information System - Formation
Nitcheu, Martial; Midekor, Akoly; Diallo, Mamadou et al

Learning material (2009)

SIMIS est un outil d’aide à décision vaste et complexe. Il permet de gérer tout périmètre irrigué sans trop de problèmes. SIMIS est constitué de programmes différents et indépendants permettant: 1) Calcul ... [more ▼]

SIMIS est un outil d’aide à décision vaste et complexe. Il permet de gérer tout périmètre irrigué sans trop de problèmes. SIMIS est constitué de programmes différents et indépendants permettant: 1) Calcul des exigences en eau de la culture; 2) Elaboration d’un plan d’irrigation: Le module permet de comparer par zone les exigences nettes et brutes en irrigation, les débits requis et les débits disponibles; 3) Elaboration des programmes d’irrigation: Différents modèles de distribution d’eau existent basé sur la rotation, basé sur l’approvisionnement proportionnel, orienté vers la demande et basé sur l’approvisionnement continu; 4) Suivi de la consommation en eau: Il compare les débits mesurés dans les canaux avec les débits du programme d’irrigation; 5) Gestion financière: calcul de la redevance eau, de gestion de la maintenance et indicateurs de performances. [less ▲]

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See detailFirst Report of Wheat Leaf Rust in the Grand Duchy of Luxembourg and the Progress of its Appearance over the 2003–2008 Period
El Jarroudi, Moussa ULg; Giraud, Frédéric; Vrancken, Carine et al

in Plant Disease (2009), 93

Wheat leaf rust caused by Puccinia triticina Eriks. was identified for the first time in 2000 in the Grand Duchy of Luxembourg on the basis of orange-to-brown, round-to-ovoid, erumpent uredinia (1 to 1.5 ... [more ▼]

Wheat leaf rust caused by Puccinia triticina Eriks. was identified for the first time in 2000 in the Grand Duchy of Luxembourg on the basis of orange-to-brown, round-to-ovoid, erumpent uredinia (1 to 1.5 mm in diameter) scattered on the upper and lower leaf surfaces and producing orange-brown urediniospores that are subgloboid, approximately 20 μm in diameter, and with up to eight germ pore scattered in thick, echinulate walls. In a second phase, wheat was monitored weekly (starting from Zadoks growth stage 30, pseudo stem erection) during the 2003–2008 cropping seasons for wheat leaf rust. Disease severity (percentage of leaf area with symptoms) was recorded in four, replicated field experiments located in three villages (Diekirch District: Reuler; and Grevenmacher District: Burmerange and Christnach), which are representative of the different agroclimatological zones of Luxembourg. A significant difference in severity was observed between the sites (P < 0.01) and the years (P < 0.05). Over the 6-year period, Burmerange and Reuler consistently showed the highest and lowest disease severity, respectively. In 2003 and 2007, Burmerange (a southern site with the highest average spring temperatures of 13.6 and 14.0°C, respectively) showed the highest disease severity with 66 and 57%, respectively, whereas the lowest severity (<1% for both years) was observed in the north at Reuler (site with the lowest average spring temperatures of 12.0 and 12.4°C, respectively). Christnach, located midway between Reuler and Burmerange, showed an intermediate disease severity with 7% (2003) and 22% (2007). The disease appeared at growth stages 77 (late milk) and 87 (hard dough) in the period 2003–2005, but at an earlier stage (45, boots swollen) for 2006–2008 (P < 0.001). In 2005, low severity was recorded due to a severe drought during May, June, and July. A reason for this earlier appearance of leaf rust occurrences in the two districts may be related to an increase in the average spring temperature (average March to May temperature for Luxembourg was 8.3°C for the 1971–2000 period, 9.5°C for the 2003–2005 period, 9.9°C for the 2006–2008 period, 2007 was exceptional with 11.9°C, P < 0.01). In the past, cereal disease management strategies were oriented toward the control of predominant and yield-reducing diseases such as that caused by Septoria tritici Desm. Because the succession of mild winters and warm springs during the last 5 years allowed the early occurrence and the fast development of wheat leaf rust in the Grand Duchy of Luxembourg, it is advisable to take this disease into account in fungicide application schemes. [less ▲]

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