Abstract
Human and non-human identification of unknown skeletal remains is of great importance in forensic and anthropologic contexts. However, the traditional morphological methods for bone species identification are subjective or time-consuming. Here, we utilized Fourier transform infrared (FTIR) spectroscopy and chemometric methods to determinate the spectral variances between human and non-human (i.e., pig, goat, and cow) bones. To simulate real forensic situations as much as possible, fresh, boiled, and decomposed bones were included in this study. Principal component analysis (PCA) results illustrated pig bones were more sensitive to the environmental and external factors than other species studied in this work. Thus, pig bone might not be a suitable proxy for human bone in the study of postmortem changes. More importantly, score plots of PCA results showed clear separation with a slight overlap between the human and non-human fresh bones, but it failed to distinguish the boiled and decomposed bones. Then, partial least squares discriminant analysis (PLS-DA) was employed, and both internal and external validations were conducted to assess its classification ability, which resulted in 99.72 and 99.53% accuracy, respectively. According to the loading plots of PCA and PLS-DA, the spectral diversity was mainly due to the inorganic portion (i.e., carbonates and phosphates), which can remain relatively stable under various conditions. As such, our results illustrate that FTIR spectroscopy could serve as a reliable tool to assist in bone species determination and also has great potential in real forensic cases with natural conditions.
| Original language | English |
|---|---|
| Pages (from-to) | 269-276 |
| Number of pages | 8 |
| Journal | International Journal of Legal Medicine |
| Volume | 133 |
| Issue number | 1 |
| DOIs | |
| State | Published - 14 Jan 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Chemometrics
- FTIR spectroscopy
- Human bone identification
- PCA
- PLS-DA
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