Abstract
The analysis of microscopic residues on stone tools provides one of the most direct ways to reconstruct the functions of such artifacts. However, new methods are needed to strengthen residue identifications based upon visible-light microscopy. In this work, we establish that reflectance Fourier-transform infrared microspectroscopy (FTIRM) can be used to document IR spectra of animal-tissue residues on experimental stone tools. First, we present a set of reflectance FTIRM standards for the most commonly identified animal-tissue residues on stone tools: skin, meat, fat, hair, blood, feather barbules, fish scales, and bone. We provide spectral peak assignments for each residue and demonstrate that high-quality reflectance FTIRM spectra can be generated under ideal circumstances. Second, we document the spectra for these residues when they are located on a stone substrate such as flint or obsidian. We discuss procedures for correcting spectra that are affected by specular reflection and explain the effects of spectral interference from the stone. Our results show that reflectance FTIRM is sensitive to small intra-sample differences in composition. This means that it will record the effects of decomposition in ancient residues. The methodological developments we present here will help lithic residue analysts incorporate in situ reflectance FTIRM into their analysis protocols to strengthen identifications.
Original language | English (US) |
---|---|
Journal | Journal of Archaeological Method and Theory |
Volume | 25 |
Issue number | 1 |
DOIs | |
State | Published - Mar 1 2018 |
Bibliographical note
Funding Information:Acknowledgements This work was funded by NSF grant # BCS-1420702. It was carried out at the University of Minnesota in the Evolutionary Anthropology Laboratories and in the Characterization Facility, which receives partial support from the NSF through the MRSEC program. Many thanks to Matt Edling, Greg Haugstad, Keith Manthie, Colin McFadden, Marjorie Schalles, Nora Last, Kara Kersteter, and Gil Tostevin. Thanks also to the three anonymous reviewers whose comments and suggestions helped improve the final manuscript.
Publisher Copyright:
© 2017, Springer Science+Business Media New York.
Keywords
- FTIR microspectroscopy
- lithic analysis
- residue analysis