A threshold-based weather model for predicting stripe rust infection in winter wheat

Article


El Jarroudi, Moussa, Kouadio, Louis, Bock, Clive H., El Jarroudi, Mustapha, Junk, Jürgen, Pasquali, Matias, Maraite, Henri and Delfosse, Philippe. 2017. "A threshold-based weather model for predicting stripe rust infection in winter wheat." Plant Disease: an international journal of applied plant pathology. 101 (5), pp. 693-703. https://doi.org/10.1094/PDIS-12-16-1766-RE
Article Title

A threshold-based weather model for predicting stripe rust infection in winter wheat

ERA Journal ID2647
Article CategoryArticle
AuthorsEl Jarroudi, Moussa (Author), Kouadio, Louis (Author), Bock, Clive H. (Author), El Jarroudi, Mustapha (Author), Junk, Jürgen (Author), Pasquali, Matias (Author), Maraite, Henri (Author) and Delfosse, Philippe (Author)
Journal TitlePlant Disease: an international journal of applied plant pathology
Journal Citation101 (5), pp. 693-703
Number of Pages11
Year2017
PublisherAmerican Phytopathological Society
Place of PublicationUnited States
ISSN0191-2917
1943-7692
Digital Object Identifier (DOI)https://doi.org/10.1094/PDIS-12-16-1766-RE
Abstract

Wheat stripe rust (caused by Puccinia striiformis f. sp. tritici) is a major threat in most wheat growing regions worldwide, which potentially causes substantial yield losses when environmental conditions are favorable. Data from 1999-2015 for three representative wheat-growing sites in Luxembourg were used to develop a threshold-based weather model for predicting wheat stripe rust. First, the range of favorable weather conditions using a Monte Carlo simulation method based on the Dennis model were characterized. Then, the optimum combined favorable weather variables (air temperature, relative humidity, and rainfall) during the most critical infection period (May-June) was identified and was used to develop the model. Uninterrupted hours with such favorable weather conditions over each dekad (i.e., 10-day period) during May-June were also considered when building the model. Results showed that a combination of relative humidity > 92% and 4°C < temperature < 16°C for a minimum of 4 continuous hours, associated with rainfall ≤ 0.1 mm (with the dekad having these conditions for 5-20% of the time), were optimum to the development of a wheat stripe rust epidemic. The model accurately predicted infection events: probabilities of detection were ≥ 0.90 and false alarm ratios were ≤ 0.38 on average, and critical success indexes ranged from 0.63 to 1. The method is potentially applicable to studies of other economically important fungal diseases of other crops or in different geographical locations. If weather forecasts are available, the threshold-based weather model can be integrated into an operational warning system to guide fungicide applications.

KeywordsYellow rust, disease model, Monte Carlo method, Puccinia striiformis
ANZSRC Field of Research 2020300409. Crop and pasture protection (incl. pests, diseases and weeds)
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Byline AffiliationsUniversity of Liege, Belgium
International Centre for Applied Climate Science
Department of Agriculture, United States
Abdelmalek Essaâdi University, Morocco
Luxembourg Institute of Science and Technology, Luxembourg
University of Milan, Italy
Catholic University of Leuven, Belgium
Institution of OriginUniversity of Southern Queensland
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Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale
Kouadio, Louis, Newlands, Nathaniel K., Davidson, Andrew, Zhang, Yinsuo and Chipanshi, Aston. 2014. "Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale." Remote Sensing. 6 (10), pp. 10193-10214. https://doi.org/10.3390/rs61010193
Brown rust disease control in winter wheat: II. Exploring the optimization of fungicide sprays through a decision support system
El Jarroudi, Moussa, Kouadio, Louis, Giraud, Frederic, Delfosse, Philippe and Tychon, Bernard. 2014. "Brown rust disease control in winter wheat: II. Exploring the optimization of fungicide sprays through a decision support system." Environmental Science and Pollution Research. 21 (7), pp. 4809-4818. https://doi.org/10.1007/s11356-014-2557-9
Brown rust disease control in winter wheat: I. Exploring an approach for disease progression based on night weather conditions
El Jarroudi, Moussa, Kouadio, Louis, Delfosse, Philippe and Tychon, Bernard. 2014. "Brown rust disease control in winter wheat: I. Exploring an approach for disease progression based on night weather conditions." Environmental Science and Pollution Research. 21 (7), pp. 4797-4808. https://doi.org/10.1007/s11356-013-2463-6
An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty
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
Profitability of using warning system for foliar disease of wheat in the Grand-Duchy of Luxembourg
El Jarroudi, M., Kouadio, L., Beyer, M., Tychon, B. and Delfosse, P.. 2013. "Profitability of using warning system for foliar disease of wheat in the Grand-Duchy of Luxembourg." 2013 APS-MSA Joint Meeting. United States 10 - 14 Aug 2013 United States. American Phytopathological Society. https://doi.org/10.1094/PHYTO-103-6-S2.1