Case Studies
Real industrial applications of spectroscopy intelligence — from field trials to live operational deployments.
Rice Quality Parameter - Multi-Component NIR Analysis
Rice quality is defined by multiple interdependent parameters that each require separate traditional laboratory methods — slow, costly and impractical for routine incoming QC. NIR spectroscopy enables simultaneous prediction of all key parameters in a single scan.
Parameters Predicted
- Amylose Content — Main factor influencing physicochemical attributes of rice starch
- Protein Content — Influences physical attributes of cooked rice
- Moisture Content — Critical for safe storage and shelf life
- Alkali Diffusion Content — Determines cooking and eating quality
Spectroscopy Approach
- NIR spectroscopy — single scan predicts all four parameters simultaneously
- Non-destructive testing — samples intact after measurement
- No sample preparation required
- Applicable to whole grain, milled rice and flour formats
Validation
- Calibrated against certified reference laboratory methods for each parameter
- Validated across multiple rice varieties and origins
- High accuracy and precision confirmed across parameter ranges
Outcome
- Single scan replaces four separate laboratory methods
- Real-time results enable rapid incoming QC decisions
- Dramatically reduces per-sample testing cost and time
- Scalable to mills, traders, importers and government inspection
One NIR scan simultaneously delivers Amylose, Protein, Moisture and Alkali Diffusion Content — replacing four separate laboratory analysis workflows with a single, non-destructive measurement.