ORIGINAL RESEARCH article
Front. Earth Sci.
Sec. Geochemistry
Geochemistry-based Machine Learning approach applied to archaeological provenance study: the obsidian blades of Tulūl al-Baqarat (Iraq)
Provisionally accepted
- 1Istituto di Geoscienze e Georisorse Consiglio Nazionale delle Ricerche, Pisa, Italy
- 2Universita degli Studi di Torino Dipartimento di Scienze della Terra, Turin, Italy
- 3Universita degli Studi di Torino, Turin, Italy
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Machine learning approach was applied to geochemical analysis of nine obsidian blades discovered in the archaeological site of Tulūl al-Baqarat (4th millennium BCE, Iraq) aiming at unravelling the provenance of the natural material (volcanic glass, obsidian) employed for carving the studied tools. To accomplish this, we measured the geochemical composition of each archaeological tool to characterize the material, using non-invasive and non-destructive techniques. Obtained data were compared with other compositional data from obsidian sources in volcanic districts of the Near East combining major, minor and trace elements. Significantly useful were the Zr and Rb minor elements, which have a remarkable discriminatory capacity in large volcanic contexts. To obtain more detailed discriminations we also applied the Principal Component Analysis modelling (PCA: covariate matrix) and automatically compared these compositional data via Machine Learning approach. Obsidian tools from Tulūl al-Baqarat show a rhyolitic composition and a geochemical fingerprint that allowed to exclude most obsidian outcrops in Turkish and Armenian volcanic sites as original source, due to different minor elements abundance and PCA analysis results. The most interesting outcome of our study indicates that obsidian blades resulted geochemically comparable to volcanic glasses from Nemrut Dağ stratovolcano (South-eastern Turkey), according with the results (averaged probability) obtained via machine learning approach. The possible provenance from Nemrut Dağ stratovolcano is remarkable, because it is located on the Turkish route of the Tigris River, supporting the evidence of a trade network and broad exchange activity since 4th Millennium BCE from Turkey and the South Near East, up to the shores of the Persian Gulf.
Keywords: obsidian, provenance reconstruction, machine learning, Bingöl, Nemrut Dağ
Received: 29 Jul 2025; Accepted: 27 Oct 2025.
Copyright: © 2025 Vaggelli, Cossio, Borghi, Lippolis and Ghignone. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Gloria Vaggelli, gloria.vaggelli@cnr.it
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