Key Takeaways:
- Treefera has launched Market Intelligence, a probabilistic forecasting product for ag and soft commodities.
- The platform delivers yield and production area forecasts with quantified uncertainty.
- In December 2025, Treefera forecast U.S. corn yield within 1% of the USDA’s final estimate.
- Forecasts are updated weekly and delivered as structured, quant-ready datasets.
- Coverage includes major commodities such as corn, wheat, sugar, cocoa, coffee, and cattle.
Treefera Introduces Probabilistic Forecasting for Ag & Soft Commodities
Treefera, an AI-native first-mile intelligence platform for agricultural and soft commodities, has launched Market Intelligence, a new data product providing yield and production area forecasts expressed as probabilistic ranges across seasonal and multi-year horizons.
The platform is designed to offer earlier supply visibility by directly analyzing field-level signals using satellite data and AI-driven production models. In December 2025, Treefera forecast U.S. corn yield at 187.6 bushels per acre. The U.S. Department of Agriculture’s final January 2026 estimate was 186.5 bushels per acre, placing Treefera’s forecast within 1% of the official figure. The forecast was delivered four weeks ahead of consensus formation and expressed as a probabilistic distribution.
Built for Trading and Procurement Decisions
Market Intelligence is tailored for commodity traders, analysts, and procurement teams seeking earlier insight into yield, planted area, and supply shifts.
According to the company, its deep learning models:
- Detect crop-specific production areas with 92% accuracy.
- Generate in-season yield forecasts with over 90% accuracy.
- Update forecasts weekly as growing conditions evolve.
Rather than relying on survey-based or top-down methodologies, Treefera aggregates millions of satellite observations, weather variables, and biological growth indicators at the field level. Outputs are structured as commodity-by-country datasets designed for integration into trading systems and back-testing workflows.
Current coverage includes U.S. corn, winter and spring wheat, sugar in India, cocoa in Ghana, coffee in Brazil, and cattle across major producing regions. Expansion is underway into soy, palm oil, rice, cotton, and natural rubber.
Treefera's Technical Approach: Crop Isolation and Growth-Stage Weighting
Treefera’s yield model incorporates two core elements:
Phenology-Aware Modelling
The system weights yield sensitivity toward critical growth stages, such as tasselling and silking in corn, aligning forecasts with biological yield drivers.
Single-Crop Canopy Isolation
Crop-specific canopy signals are isolated rather than relying on blended vegetation indices. Models are trained on single-crop datasets to improve detection accuracy.
The company states that this approach enables probabilistic forecasts with quantified uncertainty and provides a lead-time advantage ranging from four weeks to three months ahead of other market sources.
Treefera Structured Data Delivery and Forward Modelling
Clients receive weekly sub-regional yield and area datasets, five-year point-in-time hindcasts for validation, and monthly intelligence reports outlining supply implications. Deliverables include updated CSV datasets and supporting methodology documentation.
“For ag & soft commodities, markets still rely heavily on survey-based data compiled after the fact,” said Jonathan Horn, CEO and Founder of Treefera. “Our platform applies AI-native modelling to satellite observation and scientific production models, continuously assimilating new data to generate probabilistic supply forecasts with quantified uncertainty.”
Treefera’s Market Intelligence product is available globally across major agricultural and soft commodity markets.
