Gro’s Yield Forecast Models use a suite of machine-learning models to estimate in-season yields at the district, province, and/or national levels on a daily basis. Gro's China Wheat Yield Forecast Model employs two separate models to track one public and one private data source for forecasts of province-level wheat yield.
Customers Use the Model to
Why It Matters
China is a major player in crop production and consumption patterns, driving global trends and trade dynamics. The country is the world’s largest wheat producer, with production of approximately 130 million tonnes per year, or one-fifth of the global total. While China uses nearly all its wheat output domestically, variations in its huge production can have big implications for global wheat balance sheets. As most of China’s crop is winter wheat, conditions during the months of March and April are a significant harbinger of the size of the harvest at the start of summer.
These machine-learning models are driven by inputs reflecting long-term trends as well as in-season changes. The models run daily throughout the growing season, and rely on province-by-province signals derived using our domain expertise. Proprietary land cover data, built using high resolution satellite imagery, is an essential component to improve the predictive power of the model. Major model inputs and features include: