Reference : Site-specific Septoria Leaf Blotch Risk Assessment in Winter Wheat using Weather-Radar R...
Scientific journals : Article
Life sciences : Agriculture & agronomy
Life sciences : Environmental sciences & ecology
Life sciences : Phytobiology (plant sciences, forestry, mycology...)
http://hdl.handle.net/2268/82668
Site-specific Septoria Leaf Blotch Risk Assessment in Winter Wheat using Weather-Radar Rainfall Estimates
English
Mahtour, Abdeslam mailto [Université de Liège - ULg > > > Doct. sc. (sc. & gest. env. - Bologne)]
El Jarroudi, Moussa mailto [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Département des sciences et gestion de l'environnement >]
Delobbe, Laurent [> >]
Hoffmann, Lucien [> >]
Maraite, Henri [> >]
Tychon, Bernard mailto [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Département des sciences et gestion de l'environnement >]
2011
Plant Disease
American Phytopathological Society
10.1094/PDIS-07-10-0482
Yes (verified by ORBi)
International
0191-2917
[en] Weather-Radar Rainfall ; Septoria Leaf Blotch ; Winter Wheat ; PROCULTURE ; Warning systems
[en] 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.
Université de Liège
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/2268/82668
10.1094/PDIS-07-10-0482
http://apsjournals.apsnet.org/doi/abs/10.1094/PDIS-07-10-0482

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