Abstract
When analyzing heterogeneous samples using spectroscopy, the light scattering effect introduces non-linearity into the measurements and deteriorates the prediction accuracy of conventional linear models. This paper compares the prediction performance of two categories of chemometric methods: pre-processing techniques to remove the non-linearity and non-linear calibration techniques to directly model the non-linearity. A rigorous statistical procedure is adopted to ensure reliable comparison. The results suggest that optical path length estimation and correction (OPLEC) and Gaussian process (GP) regression are the most promising among the investigated methods. Furthermore, the combination of pre-processing and non-linear models is explored with limited success being achieved.