Cropin AI powers PepsiCo’s potato sourcing across 27,000 Indian farmers
Cropin is providing plot-level yield, irrigation and disease intelligence for PepsiCo’s potato supply chain across 3,000 hectares of contract farms. The platform uses satellite and weather data to generate 45-day yield forecasts and disease alerts up to 15 days ahead.
What happened
Cropin’s AI platform is supporting PepsiCo’s potato procurement from 27,000 Indian farmers, with plot-level yield, irrigation and disease monitoring. Arya.ag
Key facts
- 27,000 Indian farmers
- 3,000 hectares of contract farms
- four years of satellite and weather data
- sub-five-metre plot resolution
- 45-day potato yield forecasts
- 15-day disease prediction window
- storage food loss reduced from over 7% to under 1%
- farmer income improvement of nearly 20-30%
- PepsiCo programme yield improvement of up to 25%
- potential income increase of about ₹5,200 per acre
- crop disease threats cut by 80%
Why this matters
Food manufacturers, input suppliers and farm-services platforms should view Cropin-like capabilities as strategic partnership or acquisition targets that can secure proprietary sourcing data and deepen grower relationships.
What to watch
- Reported improvement in potato yield, grade quality, disease-loss reduction, or PepsiCo procurement-cost volatility after one to two crop cycles.
- Expansion beyond 27,000 farmers, 3,000 hectares, or into additional PepsiCo crops and geographies.
- Evidence that forecast outputs are connected to contracts, storage decisions, factory utilization, or retail promotion planning.
- New farmer incentives for digital recordkeeping, irrigation compliance, or regenerative agriculture outcomes.
- Competitor food brands or large agri-input firms deploying similar satellite-led intelligence platforms in India.
- Regulatory scrutiny or farmer pushback around agricultural data ownership and AI-generated crop recommendations.
- Integrate Cropin forecasts into procurement, cold-storage allocation, and snack-factory production planning rather than using them only for agronomy alerts.
- Offer participating farmers input recommendations, disease-response protocols, and contract incentives tied to data sharing and crop-quality outcomes.
- Use multi-season field results to quantify avoided crop loss, reduced water use, forecast accuracy, and lower spot-purchase costs.
- Expand the model to climate-vulnerable potato belts and evaluate adjacent crops used in PepsiCo India's food portfolio.
- Establish farmer-data governance rules covering consent, access, advisory use, and commercial value created from plot-level intelligence.