NIR Calibration and Chemometrics
A practical guide to NIR calibration development: how PLS regression works, how to build and validate calibration models, avoid overfitting, and transfer calibrations.
Why Calibration is Core
How PLS Regression Works
Calibration Validation: How to Know Your Model Works
Frequently Asked Questions
- What is the difference between calibration and validation in NIR?
- Calibration is the process of building the mathematical model that maps spectral data to composition — you collect representative samples, analyze them by reference methods, measure their spectra, and use regression (usually PLS) to find the relation...
- What is RMSEP and why does it matter?
- RMSEP is the root mean square error of prediction — the average prediction error of your model on a validation set. If your RMSEP for moisture is 0.5%, you can expect real-world predictions to average 0.5% away from the true value. For commercial use...
- How many samples do I need for a robust calibration?
- The rule of thumb is 50–100 samples minimum for a single-constituent model, with more needed if composition ranges are wide or there's high spectral noise. For multi-constituent models (protein, moisture, fat all together), 80–150 samples is typical....