Liye Xie and Tiziana Gallo conduct collaborative research project at the University of Tulsa

September 13, 2017

In August 2017, Professor Liye Xie and PhD student Tiziana Gallo from UTM Anthropology conducted a collaborative research project in the Lithic Microwear and Technology Laboratory at the University of Tulsa with Professor Danielle Macdonald (a UofT alumnus) there.

Using an advanced, Sensofar white-light confocal microscope in the lab, the project qualifies and quantifies the wear patterns on eight experimental tools—ground stone shovels and hoes—manufactured to replicate tools found at Neolithic to early Bronze Age sites, 5000-3500 BP, in the Central Plain and Lower Yangzi Region in China. These tools were replicated by Professor Xie and were used for tilling in agricultural fields and procuring soils for constructing houses and town walls in her experiments. The micro-traces left on the experimental tool surfaces from manufacture and use can then be compared with archaeological artifacts to identify the manufacturing techniques and tool functions in the past.

This project is the finest experimental research on earth-working wear on groundstone tools. It is also the first in the world to employ the Sensofar microscope in microwear analysis on stone tool.

Financial support for the project was provided thanks to UTM Department of Anthropology Faculty Research Funds and the UTM Office of the Vice-Principal, Research. Additional information on this project is available at http://orgs.utulsa.edu/lithicmicrowear/index.php/2017/09/07/visiting-scholars-dr-liye-xie-and-tiziana-gallo/

Photos (courtesy of Danielle Macdonald):

Liye Xie and Tiziana Gallo next to the Sensofar microscope

Tiziana Gallo and Liye Xie next to the Sensofar microscope

 

 

Liye Xie, Danielle Macdonald, and Tiziana Gallo in front of the Sensofar

Liye Xie, Danielle Macdonald, and Tiziana Gallo in front of the Sensofar

 

 

Tiziana Gallo recording and decoding the micro-wear image

Tiziana Gallo recording and decoding the micro-wear image