Abstract
The aim of this work is to explore the potential of Fourier Transform Infrared (FTIR) spectroscopy and chemometric analysis as a tool to differentiate ceramics having different provenance. We propose a new spectral FTIR data pretreatment method for Principal Component Analysis (PCA) as the selection of a proper algorithm and its application could play an important role in minimizing the manipulation of data. We consider the data in the spectral region between 400 and 1500cm−1, since this range takes into account the contribution of the fingerprints of inorganic compounds (below 1000cm−1), and the carbonate absorption band at about 1400cm−1. Normalization of FTIR data between 0 and 1 has been followed by the calculation of the second derivative, without the smoothing of data; thus resulting in minimizing the manipulation of experimental data and reducing the influence on PCA. The proposed procedure has been applied to ancient potteries from Khirbet al-Batrawy (Jordan), Motya (Trapani, Italy) and the Palatine Hill (Rome, Italy). A series of elaborations with PCA, step by step, is proposed to reduce the number of variables (from more than 1000 to ~200). This allowed the identification of the discriminating vibrational bands for each group obtained by PCA to explain the separation of samples on the basis of their mineralogical composition. The application of the statistical data processing proposed here allowed for the discrimination of different ceramic productions.
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