ORBi: Mahtour Abdeslam - Site-specific Septoria Leaf Blotch Risk Assessment in Winter Wheat using Weather-Radar Rainfall Estimates

Reference : Site-specific Septoria Leaf Blotch Risk Assessment in Winter Wheat using Weather-Radar R...


	Document type :	Scientific journals : Article
	Discipline(s) :	Life sciences : Environmental sciences & ecology Life sciences : Phytobiology (plant sciences, forestry, mycology...) Life sciences : Agriculture & agronomy
	To cite this reference:	http://hdl.handle.net/2268/82668

Title :	Site-specific Septoria Leaf Blotch Risk Assessment in Winter Wheat using Weather-Radar Rainfall Estimates
Language :	English
Author, co-author :	Mahtour, Abdeslam [Université de Liège - ULg > > > Doct. sc. (sc. & gest. env. - Bologne)]
	El Jarroudi, Moussa [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 [Université de Liège - ULg > Département des sciences et gestion de l'environnement > Département des sciences et gestion de l'environnement >]
Publication date :	2011
Journal title :	Plant Disease
Publisher :	American Phytopathological Society
Volume :	10.1094/PDIS-07-10-0482
Audience :	International
ISSN :	0191-2917
Keywords :	[en] Weather-Radar Rainfall ; Septoria Leaf Blotch ; Winter Wheat ; PROCULTURE ; Warning systems
Abstract :	[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.
Research units :	Université de Liège
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/2268/82668
DOI :	10.1094/PDIS-07-10-0482
Other URL :	http://apsjournals.apsnet.org/doi/abs/10.1094/PDIS-07-10-0482

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Restricted access	PlantdiseaseMahtourPDIS-07-10-0482.pdf	Abstract	Publisher postprint	430.53 kB	Request copy

All documents in ORBi are protected by a user license.

Dspace v1.5