Examining Ancient Human Enamel Diagenesis With ATR-FTIR

Objectives: Studies have shown that diagenesis affects skeletal elements, which can affect the quality of stable isotope data obtained from those materials. The most common ways to evaluate diagenetic alteration are the infrared splitting factor (IRSF) and carbon-phosphate ratios (C/P), commonly analyzed using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. Here, we evaluate levels of enamel diagenesis to assess data quality for the Bioarchaeology Stable Isotope Research Lab (BSIRL) at Vanderbilt University and to contribute to existing enamel preservation discourse. We hypothesize an inverse correlation between diagenetic alteration and preservation of archaeological materials.
Methods: We used ATR-FTIR to analyze 185 chemically processed enamel samples from Belen, New Mexico (n = 38), Auquimarca, Peru (n = 49), Kichpanha, Northern Belize (n = 48), and Huari, Peru (n = 50). Full spectra (from 450 cm^-1 to 4000 cm^-1) were collected using OMNIC software at 64 scans at 8 cm^-1 resolution. Here, we focus on peaks and valleys at intensities 605, 590, and 565 cm^-1 (IRSF), as well as 1035 and 1415 cm^-1 (C/P). Boundaries were set to determine whether the enamel has been diagenetically altered (IRSF: 3.1-4.0; C/P: 0.08-0.2).
Results: Preliminary results show that Belen and Huari have fewer samples that have undergone diagenesis (Belen =12% and Huari =8%) relative to Auquimarca (20%) and Kichpanha (38%). This suggests that the dental enamel does undergo diagenesis and altered samples should be eliminated from further analysis.
Conclusions: Enamel preservation aligns with predictions that sites with poorly preserved bones and teeth (based on macro-observations) yielded more samples with evidence of diagenesis. Further analysis of enamel samples must be done to confirm this trend. However, preliminary results show that enamel from geographical regions like the neotropics or subtropics, which tend to have poorer sample preservation, should undergo additional quality control checks, thus ensuring data validity.