References of "Mahtour, Abdeslam"
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See detailPerformance of leaf wetness sensor used in winter wheat disease management
Mahtour, Abdeslam ULg; El Jarroudi, Moussa ULg; Hoffmann, Lucien et al

Poster (2011, May 26)

Wetness on crop leaves has particular epidemiological significance because many fungal diseases affect plants only when free moisture is present on leaves. The leaf wetness sensor detects the presence of ... [more ▼]

Wetness on crop leaves has particular epidemiological significance because many fungal diseases affect plants only when free moisture is present on leaves. The leaf wetness sensor detects the presence of wetness on a leaf’s surface, enabling researchers and producers to forecast disease and protect plant canopies, and consequently to optimize fungicide application and often reduce environmental load. This research project aimed at better understanding the leaf wetness duration and its influence in winter wheat disease. Measurement of surface wetness duration by three electronic flat-plate sensors (Model 237-Campbell Scientific, Inc) in wheat fields were compared with tactile and visual observations in replicated field experiments at the site of Arlon (Belgium) during the period May-July 2006 and April-July 2007. Performances of the sensor were evaluated against SWEB model outputs and visual observations of disease symptoms. On the field, dew-onset and dry-off of wetness on leaves were observed visually (with a flash light for dew-onset) at 15-minute intervals. Each sensor was placed close the flag leaf. For the three sensors, the two dew-onset and dry-off times measured in both 2006 and 2007 crop seasons gave a leaf wetness duration (LWD) which was on average one hour less than visual observations. In order to establish a relationship between the surface wetness periods and wheat foliar diseases, LWD was compared with the Septoria leaf blotch (SLB) development risk (main winter wheat disease). A minimal surface wetness duration favourable to infection for SLB was established. [less ▲]

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See detailSite-specific Septoria Leaf Blotch Risk Assessment in Winter Wheat using Weather-Radar Rainfall Estimates
Mahtour, Abdeslam ULg; El Jarroudi, Moussa ULg; Delobbe, Laurent et al

in Plant Disease (2011), 10.1094/PDIS-07-10-0482

The Septoria leaf blotch prediction model PROCULTURE was used to assess the impact on simulated infection rates when using rainfall estimated by radar instead of rain gauge measurements. When comparing ... [more ▼]

The Septoria leaf blotch prediction model PROCULTURE was used to assess the impact on simulated infection rates when using rainfall estimated by radar instead of rain gauge measurements. When comparing infection events simulated by PROCULTURE using radar- and gauge-derived data, the probability of detection (PODs) of infection events was high (0.83 on average), and the false alarm ratio (FARs) of infection events was not negligible (0.24 on average). For most stations, FARso of infection events decreased to 0 and PODso increased (0.85 on average) when the model outputs for both datasets were compared against visual observations of disease symptoms. An analysis of 148 infection events over three years at four locations showed no significant difference in the number of infection events of simulations using either dataset, indicating that, for a given location, radar estimates were as reliable as rain gauges for predicting infection events. Radar also provided better estimates of rainfall occurrence over a continuous space than weather station networks. The high spatial resolution provides radar with an important advantage that could significantly improve existing warning systems. [less ▲]

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See detailSensitivity of simulated surface wetness duration to meteorological variations in three different regions of Grand-Duchy of Luxembourg
Mahtour, Abdeslam ULg; El Jarroudi, Moussa ULg; Hoffmann, Lucien et al

Poster (2010, November 23)

Surface wetness duration (SWD) is an important factor influencing the occurrence of winter wheat diseases. For this reason, SWD is extremely important for the management of crop protection activities. In ... [more ▼]

Surface wetness duration (SWD) is an important factor influencing the occurrence of winter wheat diseases. For this reason, SWD is extremely important for the management of crop protection activities. In order to understand the SWD variability and its influence on winter wheat disease, the objective of this study was to (i) determine the sensitivity of our model on varying input plant parameters and (ii) to evaluate the influence of simulated SWD to meteorological variations in three different climatic regions of the Grand-Duchy of Luxembourg (EVERLANGE, OBERCORN and SCHIMPACH). In this work, an agrometeorological model known as the Surface Wetness Energy Balance (SWEB) was applied for the simulation of SWD. The model was previously applied in another study for winter wheat cultivars and was adapted for use with agrometeorological data easily available from standard meteorological monitoring stations. Based on weather data and simulated SWD data, sensitivity analyses were performed to compare the effects of relative humidity, air temperature, wind speed and net radiation on wetness duration over one growing season (March-July) at three test sites. The results indicated that the sensitivities were very similar at three sites and there was no spatial trend (i.e. difference between locations) in the sensitivities. However, the model is most sensitive to relative humidity and differences between 0.5 and 25 h (per month) SWD were found when increasing/decreasing relative humidity by 10%. The model was least sensitive to changes in air temperature, showing differences of only 0.5–2 h (per month) in SWD. Intermediate sensitivity is found for rainfall, net radiation and wind speed. Among the input plant parameters values, SWD was most sensitive to the maximum fraction of canopy allowed as wet surface area, leaf area index, maximum water storage per unit area and least sensitive to crop height. The sensitivity to parameter values was less important compared to the sensitivity to the meteorological variable relative humidity. [less ▲]

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See detailImages radar des précipitations et durée d’humectation simulée pour l’évaluation des risques potentiels d’infection du blé d’hiver par la septoriose
Mahtour, Abdeslam ULg

Doctoral thesis (2010)

Summary - Weather-Radar Rainfall Measurement and Simulated Surface Wetness Duration for Septoria Leaf Blotch Risk Assessment. The persistence of free moisture on leaves, mainly as a result of ... [more ▼]

Summary - Weather-Radar Rainfall Measurement and Simulated Surface Wetness Duration for Septoria Leaf Blotch Risk Assessment. The persistence of free moisture on leaves, mainly as a result of precipitation in the form of rainfall or dew, plays a major role during the process of plant infection by most fungal pathogens. Acquiring rainfall and leaf moisture information is needed for accurate and reliable disease prediction and management. The objective of this research is to contribute to improve forecasting Septoria leaf blotch and other fungal pathogens on winter wheat in Belgium and Luxembourg. In the first part of this work, the potential of weather-radar rainfall estimates for plant disease forecasting is discussed. At first step, we focused on assessing the accuracy and limitations of radar-derived precipitation estimates, compared with rain-gauge data. In a second step, the Septoria leaf blotch prediction model PROCULTURE was used to assess the impact on the simulated infection rate of using, as input data, rainfall estimated by radar instead of rain gauge measurements. When comparing infection events simulated by PROCULTURE using radar-derived estimates and reference rain gauge measurements, the probability of detection (POD) of infection events was high (0.83 on average), and the false alarm ratio (FAR) of infection events was not negligible (0.24 on average). FAR decreased to 0 and POD increased (0.85 on average) for most stations, when the model outputs for both datasets were compared against visual observations of Septoria leaf blotch symptoms. Analysis of 148 infection events observed over three years at four locations showed no significant difference in the number of simulated infection events using either radar assessments or gauge measurements. This suggests that, for a given location, radar estimates are just as reliable for predicting infection events as rain gauges. As radar is able to estimate rainfall occurrence over a continuous space, unlike weather station networks that do observations at only a limited number of points, it has the great advantage of being able to predict the risk of infection at each point within an area of interest with an accuracy equivalent to rain gauge observations. This gives radar an important advantage that could significantly improve existing warning systems. In the second part, a physical model based on the energy balance, known as the Surface Wetness Energy Balance (SWEB), was applied for the simulation of Surface Wetness Duration (SWD) on winter wheat canopy. The model, developed in the United States on grapes canopies, was adapted for the winter wheat cultivars and was applied for use with agrometeorological data easily available from standard weather stations and weather-radar rainfall estimates. The SWEB model simulates surface wetness duration for both dew and rain events. The model was validated with data measured by sensors and with visual observations of SWD conducted in experimental plots during two cropping seasons in 2006 and 2007. The wetness was observed visually by assessing the presence or absence of surface water on leaves. Based on the results, the SWEB model appeared to underestimate surface wetness duration and especially for the dry-off events when compared statistically to visual observations. The error, on average, is generally less than 90 minutes. In order to establish a relationship between the surface wetness periods and Septoria leaf blotch development risk on the top three leaves, the SWEB model SWD outputs were compared with the number of hours of high probability of infection simulated by PROCULTURE as well as with visual plant diseases observations. A minimal surface wetness duration of favourable infection conditions for Septoria tritici was established. It is now required to develop an operational system that would integrate weather radar, surface wetness duration and foliar epidemic model. In this work, we have analyzed the advantages and limitations of the radar system as input to models and its ability for spatial interpolation of rainfall. We also tested the model for the determination of surface wetness periods required for Septoria Leaf Blotch Risk development. The proposed approach could be integrated in the existing system. Finally this approach shows once more the "happy marriage" between agrometeorology and plant disease management. [less ▲]

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See detailSpatial heterogeneity of leaf wetness duration in winter wheat canopy and its influence on plant disease epidemiology
Mahtour, Abdeslam ULg; El Jarroudi, Moussa ULg; Giraud et al

in Phytopathology (2010)

Leaf wetness duration (LWD) is an important factor influencing the occurrence of plant disease epidemiology. Despite considerable efforts to determine LWD, little attention has been given to study its ... [more ▼]

Leaf wetness duration (LWD) is an important factor influencing the occurrence of plant disease epidemiology. Despite considerable efforts to determine LWD, little attention has been given to study its variability within the canopy. The objective of this study was to evaluate its spatiotemporal variability in wheat fields in a heterogeneous landscape. The spatiotemporal variability of LWD was evaluated in a site close to Arlon (Belgium) during the period May to July 2006 and 2007. LWD measurements were made using a set of flat plate sensors deployed at five different distances from a 18 m high hedge (5, 10, 20, 50, 100 m). Each set of two sensors was placed horizontally close the flag leaf. In addition, we collected the amount of dew water that deposited on rigid epoxy plates placed next to each sensors. Experimental results showed that LWD measurements revealed substantial heterogeneity among sensor positions. LWD is longer for sensors closer to the hedge mainly because of its shadowing effect. 3 to 4 hours of difference was observed between sensors located at 5 m and those located at 100 m, and besides, a significant quantitative difference (p < 0.0001) of dew deposit was observed between area beside hedge and those placed at 100 m. In summary, this study provides new information on how wetness is distributed on wheat leaves according to the distance from a hedge. This leads to local microclimate conditions that will contribute to the disease spatial heterogeneity. [less ▲]

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See detailSpatial Heterogeneity of Leaf Wetness Duration in Winter Wheat Canopy and Its Influence on Plant Disease Epidemiology.
Mahtour, Abdeslam ULg; El Jarroudi, Moussa ULg; Giraud, Frédéric et al

in Phytopathology (2010)

The leaf wetness duration (LWD) is one of the most important factors influencing the occurrence of plant diseases epidemiology. Despite considerable efforts to determine LWD, little attention has been ... [more ▼]

The leaf wetness duration (LWD) is one of the most important factors influencing the occurrence of plant diseases epidemiology. Despite considerable efforts to determine LWD, little attention has been given to studies its variability in the canopy. The objective of this study was to evaluate the spatio-temporal variability in the field sites cultivated in a heterogeneous landscape. The spatial-temporal variability of LWD was evaluated in winter wheat canopy close to the hedge at Arlon (Belgium) during the period May to July 2006 and 2007. LWD measurements were made using flat plate sensors deployed at five different distances from the hedge (5, 10, 20, 50, 100 m). Each set of two sensors was placed horizontally close the flag leaf (L1) facing north. Parallel to these qualitative measures of wetness we made samples of the quantity of dew deposited on rigid epoxy plates (75 x 60 mm) placed next to each set of sensors (two plates per sensor and sampling). Experimental results show that the LWD measurements revealed substantial heterogeneity among sensors positions. LWD is longer for the sensors located at distance proximate the hedge. Three to four hours of difference was observed between sensors located at 5 m and those located at 100 m, and besides, a significant quantitative difference (p<0.0001) of dew deposit was observed between area beside hedge and those placed at 100m. In summary, this study gives a good idea of how wetness appears at the different range of the hedge. So the diversity of situations favor occurrence of very local microclimate conditions that may initiate disease in specific locations of the plot and not in others. [less ▲]

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