Weather-based predictive modeling of wheat stripe rust infection in Morocco

El Jarroudi, Moussa and Lahlali, Rachid and Kouadio, Louis ORCID: https://orcid.org/0000-0001-9669-7807 and Denis, Antoine and Belleflamme, Alexandre and El Jarroudi, Mustapha and Boulif, Mohammed and Mahyou, Hamid and Tychon, Bernard (2020) Weather-based predictive modeling of wheat stripe rust infection in Morocco. Agronomy, 10 (2):10020280.

[img]
Preview
Text (Published version)
agronomy-10-00280.pdf
Available under License Creative Commons Attribution 4.0.

Download (2MB) | Preview

Abstract

Predicting infections by Puccinia striiformis f. sp. tritici, with sufficient lead times, helps determine whether fungicide sprays should be applied in order to prevent the risk of wheat stripe rust (WSR) epidemics that might otherwise lead to yield loss. Despite the increasing threat of WSR to wheat production in Morocco, a model for predicting WSR infection events has yet to be developed. In this study, data collected during two consecutive cropping seasons in 2018–2019 in bread and durum wheat fields at nine representative sites (98 and 99 fields in 2018 and 2019, respectively) were used to develop a weather-based model for predicting infections by P. striiformis. Varying levels of WSR incidence and severity were observed according to the site, year, and wheat species. A combined effect of relative humidity > 90%, rainfall ≤ 0.1 mm, and temperature ranging from 8 to 16 ◦C for a minimum of 4 continuous hours (with the week having these conditions for 5% to 10% of the time) during March–May were optimum to the development of WSR epidemics. Using the weather-based model, WSR infections were satisfactorily predicted, with probabilities of detection ≥ 0.92, critical success index ranging from 0.68 to 0.87, and false alarm ratio ranging from 0.10 to 0.32. Our findings could serve as a basis for developing a decision support tool for guiding on-farm WSR disease management, which could help ensure a sustainable and environmentally friendly wheat production in Morocco.


Statistics for USQ ePrint 38314
Statistics for this ePrint Item
Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Date Deposited: 27 May 2020 06:28
Last Modified: 03 Jun 2020 05:11
Uncontrolled Keywords: yellow rust; disease risk; wheat; sustainable agriculture
Fields of Research : 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070106 Farm Management, Rural Management and Agribusiness
07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070308 Crop and Pasture Protection (Pests, Diseases and Weeds)
Identification Number or DOI: 10.3390/agronomy10020280
URI: http://eprints.usq.edu.au/id/eprint/38314

Actions (login required)

View Item Archive Repository Staff Only