πŸ“Š Historical Yield Data Format

Generate and validate standardized yield data formats for machine learning model training.

πŸ”’ ML-Based Yield Prediction

Run yield predictions using various machine learning algorithms and regression models.

πŸ“‘ Data Collection & Model Update Protocol

Standardized protocols for data collection, model training, and continuous improvement.

WIA-AGRI-008 Protocol Workflow

Phase Activity Frequency Data Points
1. Pre-Season Historical data collection, soil testing Annually 5-10 years history
2. Growing Season Weather monitoring, growth stage tracking Weekly Real-time sensors
3. Mid-Season Model recalibration, prediction update Monthly NDVI, weather data
4. Pre-Harvest Final yield prediction, harvest planning 2 weeks before Maturity indicators
5. Post-Harvest Actual yield recording, model validation After harvest Actual yield data
6. Annual Review Model performance analysis, retraining Annually Full season data

API Protocol Example

// Submit Yield Data
POST /api/v1/yield/submit
{
  "farmId": "KR-FARM-2025-001",
  "crop": "rice",
  "year": 2025,
  "location": {
    "province": "chungnam",
    "latitude": 36.5184,
    "longitude": 127.2158
  },
  "yield": {
    "amount": 5200,
    "unit": "kg/ha",
    "area": 2.5
  },
  "inputs": {
    "fertilizer": 220,
    "irrigation": 800,
    "pesticides": 15
  },
  "weather": {
    "avgTemp": 22.5,
    "rainfall": 850,
    "sunshine": 1800
  }
}

// Get Prediction
GET /api/v1/yield/predict?crop=rice&province=chungnam&year=2026

Response:
{
  "prediction": 5350,
  "confidence": 0.92,
  "range": [5100, 5600],
  "factors": ["favorable_rainfall", "optimal_temperature"],
  "timestamp": "2025-12-26T10:30:00Z"
}

Data Quality Standards

β€’ GPS coordinates required (Β±10m accuracy)
β€’ Weather data: hourly or daily resolution
β€’ Soil tests: minimum 3-year intervals
β€’ Yield measurement: calibrated equipment

Model Update Triggers

β€’ New harvest data available
β€’ Prediction error > 15%
β€’ Extreme weather events
β€’ Major input changes (new cultivar)

Validation Metrics

β€’ RMSE (Root Mean Square Error)
β€’ MAE (Mean Absolute Error)
β€’ RΒ² Score (>0.85 target)
β€’ Cross-validation (5-fold minimum)

πŸ”— System Integration

Connect yield predictions with market systems, supply chains, insurance, and government reporting.

Integration Ecosystem

System Integration Type Use Case Status
πŸͺ Market Pricing REST API Price forecasting based on supply predictions βœ“ Active
🚚 Supply Chain WebSocket Real-time logistics planning βœ“ Active
πŸ›‘οΈ Crop Insurance OAuth 2.0 API Risk assessment, premium calculation βœ“ Active
πŸ›οΈ Government (KOSIS) SOAP/REST National production statistics ⚠ Testing
🌾 Farm Management GraphQL Decision support systems βœ“ Active
πŸ“Š Analytics Platform Data Streaming Business intelligence, reporting βœ“ Active

Market Integration Example

Insurance Integration

β€’ Real-time risk scoring based on yield predictions
β€’ Automated claim triggers for yield < 70% prediction
β€’ Premium adjustments based on model confidence
β€’ Historical accuracy verification

Supply Chain Benefits

β€’ Advance warehouse capacity planning
β€’ Transportation optimization (2-3 months ahead)
β€’ Contract farming price negotiations
β€’ Inventory management for processors

Government Reporting

β€’ Automated submission to KOSIS (톡계청)
β€’ National food security monitoring
β€’ Subsidy program optimization
β€’ Import/export policy decisions

πŸ“± Yield Certification QR Code & Verifiable Credentials

Generate blockchain-backed yield certification QR codes for traceability and verification.