Russian and Chinese Scientists Develop Crop Failure Forecasting System
The system achieves up to 80% accuracy.
Researchers from the Space Research Institute of the Russian Academy of Sciences, Lomonosov Moscow State University and Chengdu University of Technology have joined forces to develop an intelligent system that can predict crop failures in advance. The system requires only soil and weather data to operate.
The researchers based their development on the WOFOST crop growth model, adapting it to Russian conditions. The algorithm creates a digital twin of a plant and predicts its development based on weather and environmental parameters. Forecast accuracy reaches 80%.
“Creating digital twins of plants that account for the characteristics of each region makes it possible, first, to assess crop conditions at an early stage based on regional soil and climate norms. This essentially provides the foundation for an early warning system for potential crop failures. Second, using climate scenarios for 2050 and 2100, it makes it possible to assess the potential yields of Russia’s key crops under changing climate conditions,” said Dmitry Plotnikov, head of the Remote Assessment and Monitoring Methods Sector at the Space Research Institute of the Russian Academy of Sciences.
