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«BULLETIN OF THE IRKUTSK STATE UNIVERSITY. GEOARCHAEOLOGY, ETHNOLOGY, AND ANTHROPOLOGY SERIES»
ISSN 2227-2380 (Print)

List of issues > «Geoarchaeology, Ethnology, and Anthropology Series». 2025. Vol 51

Potential of Multivariate Statistical Methods for Interpreting Portable X-ray Fluorescence Analysis Data from Ceramics: Based on Middle Neolithic Assemblages of the Baikal-Yenisei Siberia

Full text (russian)
Author(s)

I. M. Berdnikov, I. S. Shegutov, N. B. Sokolova1

1 Irkutsk State University, Irkutsk, Russian Federation

Abstract
The results of portable X-ray fluorescence analysis (pXRF) of Middle Neolithic ceramics (53 vessels) of Baikal-Yenisei Siberia from excavations at the Ust-Belaya, Derevnya Martynova, Indon, Popovskii Lug, and Generalov sites are presented. It is established that multivariate statistical methods, particularly principal component analysis and cluster analysis, offer the best opportunities for interpreting pXRF data. These methods reduce data dimensionality and more clearly identify groups of vessels with analogous properties, even with similar geochemical characteristics of the raw materials and moulding compounds. The degree of their effectiveness depends on different factors and varies in each specific case. pXRF demonstrated the best potential for differentiating vessels of the same type and potentially identifying the number of individual group of potters using the Posolskaya ceramics from the Generalov site as an example. Since there are no clay deposits suitable for pottery in the immediate vicinity of the site, all the vessels were likely made elsewhere, and each group of hunter-gatherers who periodically visited this site had their own sources of raw materials. No such clear differentiation is observed in the materials from the Ust-Belaya and Derevnya Martynova sites, although multivariate analysis methods have revealed several groups of vessels that could have belonged to different group of potters. We believe this situation is due to the availability of clay raw materials suitable for pottery in the Angara River valley, where Quaternary loams are widespread on elevated surfaces, and numerous manifestations of eluvial clays and loams developed on the weathering crusts of various early deposits are also recorded. This means that the hunter-gatherers who inhabited these territories during the Neolithic had no need to specifically search for raw materials, and different group of potters could exploit the same sources within the area they occupied over a period of time. This is clearly demonstrated by the collection of Ust-Belaya ceramics from the Derevnya Martynova site, where vessels of quite different appearance exhibit similar raw material and moulding compounds. Clearly, a larger sample size is required to achieve a higher resolution in differentiating ceramics from such archaeological sites.
About the Authors

Berdnikov Ivan Mikhailovich, Candidate of Sciences (History), Senior Researcher, Deputy Director for Science of Scientific Research Center “Baikal Region”, Irkutsk State University; 1, K. Marx st., Irkutsk, 664003, Russian Federation e-mail: yan-maiski@yandex.ru

Shegutov Ivan Sergeevich, Junior Researcher, Scientific Research Center “Baikal Region”, Irkutsk State University; 1, K. Marx st., Irkutsk, 664003, Russian Federation e-mail: shegutow@gmail.com

Sokolova Natalia Borisovna, Junior Researcher, Scientific Research Center “Baikal Region”, Irkutsk State University; 1, K. Marx st., Irkutsk, 664003, Russian Federation e-mail: snb-87@mail.ru 

For citation
Berdnikov I. M., Shegutov I. S., Sokolova N. B. Potential of Multivariate Statistical Methods for Interpreting Portable X-ray Fluorescence Analysis Data from Ceramics: Based on Middle Neolithic Assemblages of the Baikal-Yenisei Siberia. Bulletin of the Irkutsk State University. Geoarchaeology, Ethnology, and Anthropology Series. 2025, Vol. 51, pp. 33–48. https://doi.org/10.26516/2227-2380.2025.51.33 (In Russ.)
Keywords
Baikal-Yenisei Siberia, Middle Neolithic, Ust-Belaya ceramics, Posolskaya ceramics, portable X-ray fluorescence analysis, multivariate statistical methods.
UDC
902.65(571.53)
DOI
https://doi.org/10.26516/2227-2380.2025.51.33
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