Vol. 155 (2025): Archivio per l'Antropologia e la Etnologia
Research Papers

Sex estimation from talus and calcaneus in a Southern Italian sample: application of discriminant functions to the documented skeletal collection of the Museum of Anthropology and Ethnology of Florence

Rosa Perna
Department of Biology - University of Florence
Tommaso Mori
Department of Biology - University of Florence
Stella Erriu
Department of Science of Antiquities - Sapienza University of Rome
Dario Ferrari
Department of Biology - University of Florence
Giorgia Ciappi
Department of Biology - University of Florence
Irene Dori
Department of Biology - University of Florence
Alessandro Riga
Department of Biology - University of Florence

Published 2025-12-01

Keywords

  • forensic anthropology,
  • bioarchaeology,
  • sexual dimorphism,
  • tarsus

How to Cite

Perna, R., Mori, T., Erriu, S., Ferrari, D., Ciappi, G., Dori, I., & Riga, A. (2025). Sex estimation from talus and calcaneus in a Southern Italian sample: application of discriminant functions to the documented skeletal collection of the Museum of Anthropology and Ethnology of Florence. Archivio Per l’Antropologia E La Etnologia, 155, 139–157. https://doi.org/10.36253/aae-3843

Abstract

This study evaluates the reliability of discriminant function equations for sex estimation based on measurements of the talus and calcaneus in a Southern Italian population. The analysis was conducted on a documented sample of 52 adult individuals (35 males, 17 females) from the Municipal Cemetery of Siracusa (Sicily), housed at the Museum of Anthropology and Ethnology of Florence. Osteometric data were collected from both sides of the talus and calcaneus. Published equations developed on Northern Italian and Korean populations were tested, and new population-specific discriminant function equations were developed for the sample under study. Both sets produced lower accuracy results compared to those obtained in their respective reference populations. The new equations developed for the Sicilian population yielded the highest classification accuracies (82-88%), outperforming previously published models. These findings emphasize the importance of developing population-specific models in forensic anthropology.