The present study describes a multivariate strategy that can be used for automatic on-site processing of reflection mode macro FTIR mapping (MA-rFTIR) data obtained during investigation of artworks. The chemometric strategy is based on the integration of principal component analysis (PCA) with a clustering approach in the space subtended by the three lowest-order principal components and allows to automatically identify the regions of interest (ROIs) of the area scanned and to extract the average FTIR spectra related to each ROI. Thanks to the automatic data management, in-field HSI (hyperspectral imaging)-based analyses may be performed even by staff lacking specific advanced chemometric expertise, as it is sometimes the case for conservation scientists or conservators with a scientific background. MA-rFTIR was only recently introduced in the conservation field and, in this work the technique was employed to characterize the surface of metallic artefacts. The analytical protocol was employed as part of a rapid procedure to evaluate the conservation state and the performance of cleaning methods on bronze objects. Both activities are commonly part of restoration campaigns of bronzes and require an on-site analytical procedure for efficient and effective diagnosis. The performance of the method was first evaluated on aged standard samples (bronzes with a layer of green basic copper hydroxysulphate, treated with different organic coatings) and then scrutinized in situ on areas of the 16th century Neptune fountain statue (Piazza del Nettuno, Bologna, Italy) by Gianbologna.

Macroscopic mid-FTIR mapping and clustering-based automated data-reduction: An advanced diagnostic tool for in situ investigations of artworks / Sciutto G.; Legrand S.; Catelli E.; Prati S.; Malegori C.; Oliveri P.; Janssens K.; Mazzeo R.. - In: TALANTA. - ISSN 0039-9140. - ELETTRONICO. - 209:(2020), pp. 120575.120575-120575.120581. [10.1016/j.talanta.2019.120575]

Macroscopic mid-FTIR mapping and clustering-based automated data-reduction: An advanced diagnostic tool for in situ investigations of artworks

Sciutto G.;Catelli E.;Prati S.;Mazzeo R.
2020

Abstract

The present study describes a multivariate strategy that can be used for automatic on-site processing of reflection mode macro FTIR mapping (MA-rFTIR) data obtained during investigation of artworks. The chemometric strategy is based on the integration of principal component analysis (PCA) with a clustering approach in the space subtended by the three lowest-order principal components and allows to automatically identify the regions of interest (ROIs) of the area scanned and to extract the average FTIR spectra related to each ROI. Thanks to the automatic data management, in-field HSI (hyperspectral imaging)-based analyses may be performed even by staff lacking specific advanced chemometric expertise, as it is sometimes the case for conservation scientists or conservators with a scientific background. MA-rFTIR was only recently introduced in the conservation field and, in this work the technique was employed to characterize the surface of metallic artefacts. The analytical protocol was employed as part of a rapid procedure to evaluate the conservation state and the performance of cleaning methods on bronze objects. Both activities are commonly part of restoration campaigns of bronzes and require an on-site analytical procedure for efficient and effective diagnosis. The performance of the method was first evaluated on aged standard samples (bronzes with a layer of green basic copper hydroxysulphate, treated with different organic coatings) and then scrutinized in situ on areas of the 16th century Neptune fountain statue (Piazza del Nettuno, Bologna, Italy) by Gianbologna.
2020
Macroscopic mid-FTIR mapping and clustering-based automated data-reduction: An advanced diagnostic tool for in situ investigations of artworks / Sciutto G.; Legrand S.; Catelli E.; Prati S.; Malegori C.; Oliveri P.; Janssens K.; Mazzeo R.. - In: TALANTA. - ISSN 0039-9140. - ELETTRONICO. - 209:(2020), pp. 120575.120575-120575.120581. [10.1016/j.talanta.2019.120575]
Sciutto G.; Legrand S.; Catelli E.; Prati S.; Malegori C.; Oliveri P.; Janssens K.; Mazzeo R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/729049
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