Robustness of models developed by multivariate calibration. Part II: The influence of pre-processing methods

In order to improve the robustness of these calibration methods for industrial applications, an overview is presented of the existing methods, usually used to enhance prediction-model performance. The first part focuses on geometric spectral pre-processing methods, such as normalization methods, smoothing and derivatives. The second part discusses dimensionality-reduction methods, represented by orthogonalization and variable-selection methods. The impact of each method on the enhancement of the robustness of models developed by MVC is analyzed and discussed.