ToolFusion
📋 Case Study

Australian Broadacre Wheat Harvest Optimization

Yield variability >18% across fields despite identical settings; suspected sensor drift and calibration mismatches

🏗️ Project Overview

Integrated fleet of 38 New Holland CR10.90 combines and Case IH 1400 sprayers across 400k ha

🎯 Challenge

Yield variability >18% across fields despite identical settings; suspected sensor drift and calibration mismatches

🔧 Design Approach

Applied ISOXML schema validation + SPN scaling correction across all harvest and application logs; recalibrated yield mass flow (SPN 513) and grain moisture (SPN 518) using field-truthed offsets

📐 Design Diagram

Australian Broadacre Wheat Harvest Optimization Yield Variability >18% Sensor Drift & Calibration Mismatches ISOXML Schema Validation + SPN Scaling Correction SPN 518 Moisture Offset: −1.2% SPN 513 Scaling Factor: 1.047 Cross-SPN Calibration Sync Field-Truthed Offsets Challenge Processing Calibration

AI-generated project design illustration

📐 Key Calculations

Moisture Calibration Offset

Field Moisture – Reported Moisture
Result: -1.2%
Corrected over-application of drying energy

Yield Mass Flow Scaling Factor Adjustment

Calibration Factor = Measured Yield / Reported Yield
Result: 1.047
Reconciled 4.7% under-reporting bias

📊 Results

Yield variability reduced to 6.1%, fuel use per ton decreased by 9.2%, post-harvest drying costs cut by $1.8M annually

💡 Lessons Learned

  • •ISOXML version mismatch caused task file misalignment
  • •SPN 518 (grain moisture) requires temperature-compensated scaling
  • •Field validation must precede fleet-wide scaling updates

✅ Key Takeaways

  • 1ISOXML version mismatch caused task file misalignment
  • 2SPN 518 (grain moisture) requires temperature-compensated scaling
  • 3Field validation must precede fleet-wide scaling updates