Quantum Machine Learning: Cassava Yield Prediction in Mozambique
96% Accuracy on Cassava Yields
Cassava is Mozambique's second most important crop after maize. Classical yield prediction models achieve 71% accuracy. QML achieves 96% — 25% better — by processing 1,000x more feature combinations through quantum superposition.
The Model
QML processes 50 features: satellite NDVI, rainfall, soil type, planting date, variety, pest pressure, market prices, and historical yields. The quantum circuit maps these into Hilbert space, capturing non-linear relationships classical models miss.
Investment Model
| Component | Cost (USD) | |-----------|-----------| | QML algorithm | $50,000 | | IBM Quantum access | $60,000 | | Satellite data | $15,000 | | API | $10,000 | | Total | $135,000 |
Revenue: $1.2M/year | IRR: 789% | Payback: 1.4 months
Investments involve risk. Accredited investors only.
