ArticleClimate services2025
A weather-forecast driven early warning system for wheat blast disease: User-centered design, validation, and scaling in Bangladesh and Brazil.
Article in Climate services, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Early sowing enhances genotypic performance in mitigating the risk of wheat blast-induced yield loss: evidence from a 23-year simulation study in Bangladesh.Frontiers in plant science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We describe the user-centered design (UCD) of a numerical weather-forecast-driven early warning system (EWS) as a climate service for managing wheat blast, a fungal disease capable of causing complete crop yield losses that is strongly dependent on weather conditions. Our mixed-methods process was guided by stakeholder input on the design, testing, and refinement of the EWS from agricultural extension organizations, meteorological departments, and farmers' groups in Bangladesh and Brazil, where concerns about blast disease risks are high. The UCD process led to a wheat blast disease prediction model, server systems, and user-facing enhancements, including an open-source dashboard (https://beattheblastews.net/) that displays historical, real-time, and forecasted weather data, along with geographically explicit disease predictions, to support informed decision-making on wheat blast management. We describe the back- and front-end design of the dashboard, which supports disease risk forecasting, hindcasting, and the dissemination of early warning advisories co-designed with user organizations. We validated the EWS through comparisons with field observations in both countries. Model results generally agreed with disease incidence records, and model hindcasting confirmed alignment with disease outbreak patterns in Bangladesh and Brazil. Collaboration between agricultural research, meteorological and extension organizations in developing and supplying weather forecasts, disease management advisories, and early warning systems-along with presenting hindcast validation results to stakeholders-led to the formal endorsement of the EWS in both countries. This process also enabled the registration and training of over 14,500 extension officers, lead farmers, and farmers' cooperative members who now receive advisories via email, SMS, agro-meteorological bulletins, smartphone applications, WhatsApp and social media messages. These tools support them in interpreting and sharing wheat blast early warnings with farmers to improve disease preparadness and management actions in both countries.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.