Early warning and advisory can contribute to enhanced wheat stem and yellow rust management in Ethiopia

Abstract Wheat rusts are major constraints for global wheat production, leading to substantial yield and economic losses. To mitigate rust related production risks, disease forecast models generate time and location-specific information on the emergence and spread of wheat rusts. While predictions become increasingly more accurate, information on whether model outputs can enhance the effectiveness of farmers’ disease management is scarce. In this paper, we used farm household survey data and duration analysis to assess the responsiveness of smallholder farmers to risk predictions for wheat yellow and stem rust. The study used: (i) rust pressure forecasts from the wheat rust Early Warning and Advisory System (EWAS) that was first piloted in 2015 and routinely deployed in Ethiopia since 2017; (ii) within-season data on fungicide applications from 520 farmers from Ethiopia’s major wheat production regions. Results from duration models indicated that the timing of farmers’ fungicide applications for wheat rust control was associated with increasing predicted rust pressure levels and farmer exposure to related extension services. However, farm-level fungicide application dates showed that about one fourth of all applications occurred outside critical growth stages of wheat. We discuss how the existing operational rust surveillance system can enhance farmers’ wheat rust management.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-08-14
DOI
https://doi.org/10.1038/s41598-026-67016-9
Primary Topic
Wheat and Barley Genetics and Pathology
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Early warning and advisory can contribute to enhanced wheat stem and yellow rust management in Ethiopia

Tamás Mona, Christopher A. Gilligan, Michael Euler, Yoseph Alemayehu et al.
Scientific Reports
Wheat and Barley Genetics and Pathology
article

Early warning and advisory can contribute to enhanced wheat stem and yellow rust management in Ethiopia

Tamás Mona, Christopher A. Gilligan, Michael Euler, Yoseph Alemayehu, David Hodson, Gerald Blasch, Jacob W. Smith, Ayele Badebo
article en

Abstract

Abstract Wheat rusts are major constraints for global wheat production, leading to substantial yield and economic losses. To mitigate rust related production risks, disease forecast models generate time and location-specific information on the emergence and spread of wheat rusts. While predictions become increasingly more accurate, information on whether model outputs can enhance the effectiveness of farmers’ disease management is scarce. In this paper, we used farm household survey data and duration analysis to assess the responsiveness of smallholder farmers to risk predictions for wheat yellow and stem rust. The study used: (i) rust pressure forecasts from the wheat rust Early Warning and Advisory System (EWAS) that was first piloted in 2015 and routinely deployed in Ethiopia since 2017; (ii) within-season data on fungicide applications from 520 farmers from Ethiopia’s major wheat production regions. Results from duration models indicated that the timing of farmers’ fungicide applications for wheat rust control was associated with increasing predicted rust pressure levels and farmer exposure to related extension services. However, farm-level fungicide application dates showed that about one fourth of all applications occurred outside critical growth stages of wheat. We discuss how the existing operational rust surveillance system can enhance farmers’ wheat rust management.

Scientific Reports
Centro Internacional de Mejoramiento de Maíz Y Trigo (MX), University of Cambridge (GB), International Maize and Wheat Improvement Center (ET)
Bill and Melinda Gates Foundation, Ethiopian Institute of Agricultural Research, Haramaya University, Foreign, Commonwealth and Development Office, Directorate for Biological Sciences
Openalex Percentile: Top 12%
Wheat and Barley Genetics and Pathology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.