Chemometric approaches for document dating: Handling paper variability.

A non-destructive methodology based on Fourier Transformed Infrared Spectroscopy (FTIR) is proposed in this research to estimate the age of documents of different ages. Due the variability in the samples caused by their different chemical compositions, chemometric approaches were proposed to build one unique regression model able to determine the age of the paper regardless of its composition. PLS models were built employing Generalized Least Squares Weighting (GLSW) and Orthogonal Least Squares (OLS) filters to reduce the variability of samples from the same year. Afterwards, sparse PLS, which is an extension of the PLS model including a variable selection step, was applied to compare its performance with the preprocessing filters. All techniques proposed were compared to the initial PLS models, showing the potential of the chemometric approaches applied to FTIR data to estimate the age of unknown documents.