Journal | Vibrational Spectroscopy |
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Date | Accepted/In press - 22 Feb 2017 |
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Date | E-pub ahead of print - 27 Mar 2017 |
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Date | Published (current) - May 2017 |
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Volume | 90 |
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Number of pages | 10 |
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Pages (from-to) | 21-30 |
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Early online date | 27/03/17 |
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Original language | English |
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The use of near infrared (NIR) spectroscopy was evaluated, by using chemometric tools, for the study of the environmental impact on burned bones. Spectra of internal and external parts of burned bones, together with sediment samples, were treated by Principal Component Analysis and cluster classification as exploratory techniques to select burned bone samples, less affected by environmental processes, to properly carry out forensic studies. Partial Least Square Discriminant Analysis was used to build a model to classify bone samples based on their burning conditions, providing an efficient and accurate method to discern calcined and carbonized bone. Additionally, Partial Least Square regression models were built to predict calcium, magnesium and strontium concentration of bone samples from their NIR spectra, being obtained an accurate root mean square error of prediction of 5.2% for calcium. Furthermore a screen methodology, for magnesium and strontium prediction, with a RPD of 0.24 and 1.08 respectively, was developed.
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