Organic residue analysis in biomolecular archaeology provides critical insights into past human practices. However, its application is often hindered by analytical challenges. Traditional single-biomarker approaches are highly susceptible to interference issues, such as contamination and matrix effects. These challenges are exacerbated in high-value artifacts, such as figured vases, which frequently undergo post-excavation washing, restoration, and strict sampling restrictions, thereby demanding highly sensitive and interference-robust methods. To address this, we propose a multivariate analytical framework based on the simultaneous profiling of 12 corroborated molecular markers, including wine acids and fatty acids. This strategy was applied to investigate funerary figured vases from Falerii Veteres (central Italy), targeting residues associated with ritual symposia, where wine was historically blended with honey and dairy products. Crucially, the multivariate approach was utilized not only for data interpretation but also for analytical optimization via experimental design. Maximizing the geometric mean of the chromatographic peak areas obtained via high-performance liquid chromatography coupled with high-resolution mass spectrometry enabled the simultaneous optimization of the analytical response across all 12 target analytes. Principal component analysis of the archaeological vessels and modern mock-up references demonstrated that this multi-biomarker framework successfully mitigates single-marker vulnerabilities, effectively discriminating between substance classes by leveraging chemical patterns across the entire analyte suite.

A combined multivariate approach for the analysis of organic residues in Faliscan figured vases / Bosi, A., Negozio, M., Frasca, C., Pola, A., Marini, F., Ciccola, A., Favero, G., Serafini, I.. - In: ANALYTICAL METHODS. - ISSN 1759-9660. - (2026). [10.1039/d6ay01076h]

A combined multivariate approach for the analysis of organic residues in Faliscan figured vases

Adele Bosi
Primo
;
Martina Negozio;Claudia Frasca;Angela Pola;Federico Marini;Alessandro Ciccola;Gabriele Favero;Ilaria Serafini
Ultimo
2026

Abstract

Organic residue analysis in biomolecular archaeology provides critical insights into past human practices. However, its application is often hindered by analytical challenges. Traditional single-biomarker approaches are highly susceptible to interference issues, such as contamination and matrix effects. These challenges are exacerbated in high-value artifacts, such as figured vases, which frequently undergo post-excavation washing, restoration, and strict sampling restrictions, thereby demanding highly sensitive and interference-robust methods. To address this, we propose a multivariate analytical framework based on the simultaneous profiling of 12 corroborated molecular markers, including wine acids and fatty acids. This strategy was applied to investigate funerary figured vases from Falerii Veteres (central Italy), targeting residues associated with ritual symposia, where wine was historically blended with honey and dairy products. Crucially, the multivariate approach was utilized not only for data interpretation but also for analytical optimization via experimental design. Maximizing the geometric mean of the chromatographic peak areas obtained via high-performance liquid chromatography coupled with high-resolution mass spectrometry enabled the simultaneous optimization of the analytical response across all 12 target analytes. Principal component analysis of the archaeological vessels and modern mock-up references demonstrated that this multi-biomarker framework successfully mitigates single-marker vulnerabilities, effectively discriminating between substance classes by leveraging chemical patterns across the entire analyte suite.
2026
organic residues; LC-HRMS; chemometrics
01 Pubblicazione su rivista::01a Articolo in rivista
A combined multivariate approach for the analysis of organic residues in Faliscan figured vases / Bosi, A., Negozio, M., Frasca, C., Pola, A., Marini, F., Ciccola, A., Favero, G., Serafini, I.. - In: ANALYTICAL METHODS. - ISSN 1759-9660. - (2026). [10.1039/d6ay01076h]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1773582
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