A user-friendly decision support system for supporting grape downy mildew control in Chinese vineyards

Reducing fungicide use is a global priority for agricultural nations. Decision support systems (DSSs) help farmers optimize spraying schedules by assessing crop disease risk. However, a practical DSS specifically designed for grape downy mildew ( Plasmopara viticola ) has not yet been reported for China. . In this study, we developed a user-friendly DDS to support grape downy mildew management, which serves as a signal for the first spraying application. Furthermore, the tool employs a binary risk classification system (low vs. high) to recommend optimal spraying timings during the secondary infection period. The DSS has been embedded in the WeChat mini-program "Grape Defender" and deployed across 13 provinces in China. Model evaluation was conducted using two datasets: (a) a multi-year (2021–2024) experimental trial conducted across two cities, and (b) climate data collected from 13 provinces. We then compared a model-based fungicide application approach with a regular method in terms of disease incidence and number of spray applications in the two cities, and then we provide prediction services in 13 major grape-growing provinces across China. The DDS reduced fungicide applications by 43.75% in two experimental cities while maintaining comparable disease control, with increase in disease incidence no exceeding 11%relative to the regular management group. Simulations further projected 73 high-risk infection events across 13 provinces in 2025, suggesting that disease management efforts should primarily focus on June to August rather than May. The “Grape Defender” DSS, which will be freely accessible, supports customized strategies tailored to local climates and grape varieties in China.