Case Studies
Real industrial applications of spectroscopy intelligence — from field trials to live operational deployments.
Palm Oil: Fresh Fruit Bunch (FFB) Quality Assessment
Oil Extraction Rate (OER) from Fresh Fruit Bunches is the key economic driver in palm oil milling. Traditional Soxhlet extraction is accurate but slow — making at-scale incoming FFB grading impractical. NIR enables rapid on-site prediction to improve operational and financial performance.
Challenge
- Traditional OER measurement by Soxhlet extraction is slow and lab-bound
- FFB quality varies significantly — grading determines purchase price
- Without rapid screening, high-OER bunches cannot be prioritised
- FFA accumulation causes quality degradation if harvest timing is poor
Spectroscopy Approach
- NIR screening at the collection site (Point 1) for initial grading
- NIR quantification at the mill gate (Point 2) for purchase verification
- Models built against Soxhlet-extracted OER reference data
- Predictions delivered in <30 seconds per bunch
Parameters Predicted
- Oil Content / Oil Extraction Rate (OER)
- Free Fatty Acid (FFA) Content
- Moisture Content
Outcome
- Enables fair, transparent FFB pricing based on real oil content
- Reduces reliance on slow and expensive lab-based OER testing
- Improves mill scheduling and processing efficiency
- Reduces financial losses from purchasing low-quality FFB at full price
Two-point NIR screening — from plantation collection to mill gate — delivers rapid OER, FFA and moisture prediction, enabling fair pricing, better scheduling and higher extraction efficiency.