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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. [ABSTRACT FROM AUTHOR]

Abstract: Inks and paper are the main materials and components of library and archive collections. Since the beginning of paper and ink production empirical recipes have been followed, but in the 19th century with the transformation of Europe during the Industrial Revolution, the continent became the main leader for the discovery of new products and new industrial production processes. The aim of this study is to shed light on paper and ink production processes during this key historical period. In this study we have chosen some documents preserved in the archive of the Soprintendenza dei Beni Architettonici e Paesaggistici (B.A.P.) di Venezia e Laguna, held in the Palazzo Ducale (Ducal Palace) of Venice. Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FT-IR), and inductively coupled plasma-mass spectrometry (ICP-MS) allowed us to obtain a qualitative and quantitative characterization of the organic and inorganic components in both paper and inks. Cluster analysis and principal component analysis (PCA) were employed for statistical analysis of the results. [Copyright &y& Elsevier]