Journal Article

FZJ-2020-04356

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Weather-Based Predictive Modeling of Wheat Stripe Rust Infection in Morocco

El Jarroudi, M. (Corresponding author) ; Lahlali, R. ; Kouadio, L. ; Denis, A. ; Belleflamme, A.FZJ* ; El Jarroudi, M. ; Boulif, M. ; Mahyou, H. ; Tychon, B.

2020
MDPI Basel

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Please use a persistent id in citations: http://hdl.handle.net/2128/26116  doi:10.3390/agronomy10020280

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

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Contributing Institute(s):

1. Agrosphäre (IBG-3)

Research Program(s):

1. 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) (POF3-255)

Appears in the scientific report 2020

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Database coverage:
; ; ; ; Article Processing Charges ; Clarivate Analytics Master Journal List ; Current Contents - Agriculture, Biology and Environmental Sciences ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; Fees ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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