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HSAT, a pioneer in agricultural data science, has revealed a major breakthrough in cocoa yield prediction—achieving accuracy levels consistently above 95%.
This achievement firmly establishes HSAT’s CropGPT platform as the most sophisticated tool currently available for global cocoa production forecasting.
The models, updated every 30 minutes, draw on billions of data points and combine satellite monitoring, ultra-local weather data, field-based crop assessments, disease tracking, and macroeconomic signals across key cocoa producers—Ivory Coast, Ghana, Ecuador, Nigeria, and Indonesia.
Predictions are validated through independent methods, including on-the-ground verification by HSAT’s global field team of over 2,000 contributors.
HSAT’s cocoa forecasting models are tailored to regional agronomic conditions and adapt in real time. Disease mapping (e.g., CSSV), AI-driven pod counting, and cumulative rainfall analysis are key innovations that allow HSAT to detect yield threats before they impact production – delivering intelligence to traders, insurers, and producers with unmatched lead time and precision.
“Our models aren’t static forecasts, they evolve each week,” said Rob Weston, founder. “We show our accuracy over the past decade, and every model is specific to crop, country, and season. This level of granularity is unique in the market.”
The cocoa insights feed directly into HSAT’s Market Forces system – enabling users to track how rainfall deficits, disease outbreaks, or FX movements impact future yields.
A detailed report on the impact of disease in Ivory Coast and Ghana – two of the world’s largest cocoa producers – is available at https://reports.cropgpt.ai/cocoadisease.
CropGPT’s forecasts are delivered through dashboards, weekly reports, APIs, and alerts – ensuring clients receive the intelligence in the format they need, at the speed they demand.