Weather-based predictive modeling of Cercospora beticola infection events in sugar beet in Belgium

Article


El Jarroudi, Moussa, Chairi, Fadia, Kouadio, Louis, Antoons, Kathleen, Sallah, Abdoul-Hamid Mohamed and Fettweis, Xavier. 2021. "Weather-based predictive modeling of Cercospora beticola infection events in sugar beet in Belgium." Journal of Fungi. 7 (9). https://doi.org/10.3390/jof7090777
Article Title

Weather-based predictive modeling of Cercospora beticola infection events in sugar beet in Belgium

ERA Journal ID213247
Article CategoryArticle
AuthorsEl Jarroudi, Moussa (Author), Chairi, Fadia (Author), Kouadio, Louis (Author), Antoons, Kathleen (Author), Sallah, Abdoul-Hamid Mohamed (Author) and Fettweis, Xavier (Author)
Journal TitleJournal of Fungi
Journal Citation7 (9)
Article Number777
Number of Pages21
Year2021
PublisherMDPI AG
Place of PublicationSwitzerland
ISSN2309-608X
Digital Object Identifier (DOI)https://doi.org/10.3390/jof7090777
Web Address (URL)https://www.mdpi.com/2309-608X/7/9/777
Abstract

Cercospora leaf spot (CLS; caused by Cercospora beticola Sacc.) is the most widespread and damaging foliar disease of sugar beet. Early assessments of CLS risk are thus pivotal to the success of disease management and farm profitability. In this study, we propose a weather-based modelling approach for predicting infection by C. beticola in sugar beet fields in Belgium. Based on reported weather conditions favoring CLS epidemics and the climate patterns across Belgian sugar beet-growing regions during the critical infection period (June to August), optimum weather conditions conducive to CLS were first identified. Subsequently, 14 models differing according to the combined thresholds of air temperature (T), relative humidity (RH), and rainfall (R) being met simultaneously over uninterrupted hours were evaluated using data collected during the 2018 to 2020 cropping seasons at 13 different sites. Individual model performance was based on the probability of detection (POD), the critical success index (CSI), and the false alarm ratio (FAR). Three models (i.e., M1, M2 and M3) were outstanding in the testing phase of all models. They exhibited similar performance in predicting CLS infection events at the study sites in the independent validation phase; in most cases, the POD, CSI, and FAR values were ≥84%, ≥78%, and ≤15%, respectively. Thus, a combination of uninterrupted rainy conditions during the four hours preceding a likely start of an infection event, RH > 90% during the first four hours and RH > 60% during the following 9 h, daytime T > 16 °C and nighttime T > 10 °C, were the most conducive to CLS development. Integrating such weather-based models within a decision support tool determining fungicide spray application can be a sound basis to protect sugar beet plants against C. beticola, while ensuring fungicides are applied only when needed throughout the season.

KeywordsCercospora beticola; fungal foliar disease; plant disease risk; integrated plant disease management
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020300409. Crop and pasture protection (incl. pests, diseases and weeds)
Byline AffiliationsUniversity of Liege, Belgium
Centre for Applied Climate Sciences
Royal Belgian Institute for Beet Improvement, Belgium
Institution of OriginUniversity of Southern Queensland
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Newlands, Nathaniel K., Zamar, David S., Kouadio, Louis A., Zhang, Yinsuo, Chipanshi, Aston, Potgieter, Andries, Toure, Souleymane and Hill, Harvey S. J.. 2014. "An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty." Frontiers in Environmental Science. 2, pp. 1-21. https://doi.org/10.3389/fenvs.2014.00017
A comparison of raters and disease assessment methods for estimating disease severity for purposes of hypothesis testing
Bock, Clive, El Jarroudi, Moussa, Kouadio, Louis, Mackels, Christophe, Chiang, Kuo-Szu and Delfosse, Philippe. 2014. "A comparison of raters and disease assessment methods for estimating disease severity for purposes of hypothesis testing." Phytopathology: International Journal of the American Phytopathological Society. 104 (11), pp. 15-16.
Importance of a well-distributed frequency of measurements in the senescence monitoring of winter wheat and yield estimates
Kouadio, Louis, Djaby, Bakary, El Jarroudi, Moussa and Tychon, Bernard. 2012. "Importance of a well-distributed frequency of measurements in the senescence monitoring of winter wheat and yield estimates." Journal of Agricultural Science and Technology . 2 (12), pp. 1203-1213.
Estimating winter wheat yield through the decreasing phase of its green area [Cinetique de decroissance de la surface verte et estimation du rendement du ble d'hiver]
Kouadio, Amani Louis, Djaby, Bakary, Duveiller, Gregory, El Jarroudi, Moussa and Tychon, Bernard. 2012. "Estimating winter wheat yield through the decreasing phase of its green area [Cinetique de decroissance de la surface verte et estimation du rendement du ble d'hiver]." Biotechnology, Agronomy, Society and Environment. 16 (2), pp. 179-191.
Typology of the main fungal diseases affecting winter wheat in the Grand Duchy of Luxembourg
El Jarroudi, Moussa, Kouadio, Louis, Delfosse, Philippe, Giraud, Frederic, Junk, Jurgen, Hoffmann, Lucien, Maraite, Henri and Tychon, Bernard. 2012. "Typology of the main fungal diseases affecting winter wheat in the Grand Duchy of Luxembourg." Journal of Agricultural Science and Technology . 2 (12), pp. 1386-1399.
Spatial distribution of calibrated WOFOST parameters and their influence on the performances of a regional yield forecasting system
Djaby, Bakary, de Wit, Allard, Kouadio, Louis, El Jarroudi, Moussa and Tychon, Bernard. 2013. "Spatial distribution of calibrated WOFOST parameters and their influence on the performances of a regional yield forecasting system." Sustainable Agriculture Research. 2 (4), pp. 12-29. https://doi.org/10.5539/sar.v2n4p12
Disease severity assessment in epidemiological studies: accuracy and reliability of visual estimates of Septoria leaf blotch (SLB) in winter wheat
El Jarroudi, Moussa, Kouadio, Louis, Mackels, Christophe, Tychon, Bernard, Delfosse, Philippe and Bock, Clive H.. 2014. "Disease severity assessment in epidemiological studies: accuracy and reliability of visual estimates of Septoria leaf blotch (SLB) in winter wheat." 2014 APS-CPS Joint Meeting. Minneapolis, United States of America 09 - 13 Aug 2014 United States. American Phytopathological Society. https://doi.org/10.1094/PHYTO-104-11-S3.1