Novel model optimization algorithm improves robustness of near-infrared spectroscopy models

Novel model optimization algorithm improves robustness of near-infrared spectroscopy models

A research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has proposed a novel model optimization algorithm—External Calibration-Assisted Screening (ECA)— that significantly enhances the prediction robustness of near-infrared spectroscopy (NIRS) quantitative models. The findings are published in Analytica Chimica Acta.