New Strategies in Archaeometric Provenance Analyses of Volcanic Rock Grinding Stones : Examples from Iulia Libica (Spain) and Sidi Zahruni (Tunisia)
Casas Duocastella, Lluís (Universitat Autònoma de Barcelona. Departament de Geologia)
Di Febo, Roberta (Universitat Autònoma de Barcelona. Departament de Geologia)
Anglisano, Anna (Universitat de Girona. Departament de Ciències Ambientals)
Pitarch Martí, Àfrica (Universitat de Barcelona. Departament d'Arts i Conservació-Restauració)
Queralt, Ignasi (Institut de Diagnosi Ambiental i Estudis de l'Aigua)
Carreras Monfort, César (Universitat Autònoma de Barcelona. Departament de Ciències de l'Antiguitat i de l'Edat Mitjana)
Fouzai, Boutheina (École Nationale D'ingénieurs de Gafsa. Département Génie Chimique Industriel et Minier (Tunísia))

Data:	2024
Resum:	Archaeometry can help archaeologists in many ways, and one of the most common archaeometric objectives is provenance analysis. Volcanic rocks are often found in archaeological sites as materials used to make grinding tools such as millstones and mortars or as building materials. Petrographic characterization is commonly applied to identify their main mineralogical components. However, the provenance study of volcanic stones is usually undertaken by comparing geochemical data from reference outcrops using common descriptive statistical tools such as biplots of chemical elements, and occasionally, unsupervised multivariate data analysis like principal component analysis (PCA) is also used. Recently, the use of supervised classification methods has shown a superior performance in assigning provenance to archaeological samples. However, these methods require the use of reference databases for all the possible provenance classes in order to train the classification models. The existence of comprehensive collections of published geochemical analyses of igneous rocks enables the use of the supervised approach for the provenance determination of volcanic stones. In this paper, the provenance of volcanic grinding tools from two archaeological sites (Iulia Libica, Spain, and Sidi Zahruni, Tunisia) is attempted using data from the GEOROC database through unsupervised and supervised approaches. The materials from Sidi Zahruni have been identified as basalts from Pantelleria (Italy), and the agreement between the different supervised classification models tested is particularly conclusive. In contrast, the provenance of the materials from Iulia Libica remained undetermined. The results illustrate the advantages and limitations of all the examined methods.
Ajuts:	Ministerio de Ciencia e Innovación CEX2018-000794-S Agència de Gestió d'Ajuts Universitaris i de Recerca 2021/SGR-00089
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Archaeometry ; Volcanic stone ; Grinding tools ; Provenance studies ; Supervised methods ; Machine learning ; Clustering ; XRF
Publicat a:	Minerals, Vol. 14, Issue. 7 (July 2024) , art. 639, ISSN 2075-163X

DOI: 10.3390/min14070639

25 p, 23.1 MB

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