Articles
Why Honigs Regression Changes the Way We Think About NIR Calibration
arrow_backTo the overview03 August 2026 | Perten, a PerkinElmer company
Developed by Perten’s own Dr. David Honigs, Honigs Regression takes a fundamentally different approach to NIR calibration – one that grows smarter over time rather than needing to be rebuilt.
Near-infrared spectroscopy is fast. That is one of the reasons food manufacturers value it.
But speed at the measurement stage has always come with a quieter cost: the work of keeping the model accurate as the world around it changes. Products evolve. Crop years shift. New recipe variants appear. Ingredients get reformulated. Production conditions drift. And every time those things happen, someone has to decide whether the current NIR model still fits – and what to do when it does not.
For many manufacturers, that decision leads to the same answer, again and again: build another model. Adjust the bias. Add another channel. Repeat.
This is not a failure of NIR. It is a consequence of the way conventional models are built. Honigs Regression was developed to offer a better way.
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