Improved chemometric approach for XRF data treatment: application to the reverse glass paintings from the Lipari collection

The Aeolian cultural heritage preserves hundreds of testimonies of the past that have passed through six millennia of history. Among these, the Archeological Park of the Aeolian Islands with the Museum Luigi Bernabo Brea (Italy) preserves a valuable set of artworks, which are related to a little-known 'popular' figurative heritage. It is an assemblage of small glass foils decorated using the technique of reverse painting, datable to between the end of the 17(th) century and the end of the 18(th) century, and actually under investigation by historians. Here, an X-ray fluorescence (XRF) spectroscopy study (performed with portable equipment) is combined with a multivariate approach that allows us to define the best way to process the data to detect compositional differences and similarities among the glass supports. The Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were applied both on normalized spectra and on normalized peak areas in order to establish the chemometric approach with the highest grouping ability. Results showed that the analysis of the normalized area provides the most reliable grouping based on the different elemental compositions, without problems coming from the background or peak-shape distortions. The obtained results can be used by researchers involved in the analysis of XRF data as a guideline to perform chemometrics. Furthermore, regarding the reverse glass, they can be divided into different typologies based on composition differences, providing a further discrimination criterion for historians involved in the study of the collection to determine the provenance and dating of the items.

Automated summary

This study combines portable X-ray fluorescence spectroscopy with multivariate analysis to investigate glass supports in the archaeological park of the Aeolian Islands. The analysis of normalized peak areas provides a reliable grouping based on elemental compositions, offering a guideline for chemometrics in XRF data analysis.