Chemical Differentiation of Osseous and Nonosseous Materials Using Scanning Electron Microscopy–Energy-Dispersive X-Ray Spectrometry and Multivariate Statistical Analysis

Identification of osseous materials is generally established on gross anatomical features. However, highly fragmented or taphonomically altered materials may be problematic and may require chemical analysis. This research was designed to assess the use of scanning electron microscopy–energy-dispersive X-ray spectrometry (SEM/EDX), elemental analysis, and multivariate statistical analysis (principal component analysis) for discrimination of osseous and nonosseous materials of similar chemical composition. Sixty samples consisting of osseous (human and nonhuman bone and dental) and non-osseous samples were assessed. After outliers were removed a high overall correct classification of 97.97% was achieved, with 99.86% correct classification for osseous materials. In addition, a blind study was conducted using 20 samples to assess the applicability for using this method to classify unknown materials. All of the blind study samples were correctly classified resulting in 100% correct classification, further demonstrating the efficiency of SEM/EDX and statistical analysis for differentiation of osseous and nonosseous materials.