Reference : Yellow rust does not like cold winters. But how to find out which temperature and tim...
Scientific journals : Article
Life sciences : Agriculture & agronomy
http://hdl.handle.net/2268/230814
Yellow rust does not like cold winters. But how to find out which temperature and time frames could be decisive in vivo?
English
Aslanov, Rufat [> >]
El Jarroudi, Moussa mailto [Université de Liège - ULiège > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > Eau, Environnement, Développement >]
Gollier, Mélanie [> >]
Pallez, Marine [> >]
Beyer, Marco [> >]
4-Jan-2019
Journal of Plant Pathology
Societa Italiana di Patologia Vegetale
Yes (verified by ORBi)
1125-4653
Italy
[en] Disease forecast ; Integrated Pest Management (IPM) ; Pesticide use ; Puccinia striiformis f. sp. tritici ; Sustainable agriculture
[en] Yellow rust epidemics caused by Puccinia striiformis f. sp. tritici were monitored in winter wheat grown without fungicides at
four locations over the years 2010–2016 in the Grand Duchy of Luxembourg (GDL) and were observed at increased frequency
since 2014. A total of 29 field case studies were subdivided into epidemic and non-epidemic cases based on the control threshold
of the disease defined in the framework of integrated pest management (IPM). Significant air temperature differences were found
between the time courses of epidemic and non-epidemic cases during seven periods and seven individual days. The longest
periods with significantly higher temperatures for epidemic cases were found between 21 and 28 days after sowing (DAS) and
between 132 and 134 DAS, corresponding approximately to the time of winter wheat emergence, when the disease may infect the
newly sown crop, and to the coldest period of the year, respectively. Average daily temperatures were 7.33 ± 0.32 °C and 10.79 ±
0.26 °C between 21 and 28 DAS for non-epidemic and epidemic cases, respectively. Between 132 and 134 DAS, average daily
temperatures were − 1.62 ± 0.74 °C and 1.58 ± 0.43 °C for non-epidemic and epidemic cases, respectively. Based on the significant
temperature differences detected, up to 86.7% of correct classifications were obtained by leave-one out cross-validation,
suggesting that some of the temperature differences identified here have considerable prognostic value for forecasting if an
economically relevant yellow rust epidemic must be expected or not.
ASTA LUXEMBOURG
Sentinelle
Researchers ; Professionals ; Students ; General public ; Others
http://hdl.handle.net/2268/230814
10.1007/s42161-018-00233-y
https://link.springer.com/article/10.1007/s42161-018-00233-y

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