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

El Jarroudi, Moussa and Kouadio, Louis ORCID: https://orcid.org/0000-0001-9669-7807 and Bock, Clive H. and El Jarroudi, Mustapha and Junk, Jürgen and Pasquali, Matias and Maraite, Henri and Delfosse, Philippe (2017) A threshold-based weather model for predicting stripe rust infection in winter wheat. Plant Disease, 101 (5). pp. 693-703. ISSN 0191-2917


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.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Historic - Institute for Agriculture and the Environment
Faculty/School / Institute/Centre: Historic - Institute for Agriculture and the Environment
Date Deposited: 19 Oct 2017 00:52
Last Modified: 17 Apr 2018 01:30
Uncontrolled Keywords: Yellow rust, disease model, Monte Carlo method, Puccinia striiformis
Fields of Research (2008): 07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070308 Crop and Pasture Protection (Pests, Diseases and Weeds)
Fields of Research (2020): 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3004 Crop and pasture production > 300409 Crop and pasture protection (incl. pests, diseases and weeds)
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences
Identification Number or DOI: https://doi.org/10.1094/PDIS-12-16-1766-RE
URI: http://eprints.usq.edu.au/id/eprint/30722

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