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Burned bones forensic investigations employing near infrared spectroscopy

Research output: Contribution to journalArticlepeer-review

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Burned bones forensic investigations employing near infrared spectroscopy. / Cascant, Mari Merce; Rubio, Sonia; Gallello, Gianni; Pastor, Agustin; Garrigues, Salvador; De la Guardia, Miguel.

In: Vibrational Spectroscopy, Vol. 90, 05.2017, p. 21-30.

Research output: Contribution to journalArticlepeer-review

Harvard

Cascant, MM, Rubio, S, Gallello, G, Pastor, A, Garrigues, S & De la Guardia, M 2017, 'Burned bones forensic investigations employing near infrared spectroscopy', Vibrational Spectroscopy, vol. 90, pp. 21-30. https://doi.org/10.1016/j.vibspec.2017.02.005

APA

Cascant, M. M., Rubio, S., Gallello, G., Pastor, A., Garrigues, S., & De la Guardia, M. (2017). Burned bones forensic investigations employing near infrared spectroscopy. Vibrational Spectroscopy, 90, 21-30. https://doi.org/10.1016/j.vibspec.2017.02.005

Vancouver

Cascant MM, Rubio S, Gallello G, Pastor A, Garrigues S, De la Guardia M. Burned bones forensic investigations employing near infrared spectroscopy. Vibrational Spectroscopy. 2017 May;90:21-30. https://doi.org/10.1016/j.vibspec.2017.02.005

Author

Cascant, Mari Merce ; Rubio, Sonia ; Gallello, Gianni ; Pastor, Agustin ; Garrigues, Salvador ; De la Guardia, Miguel. / Burned bones forensic investigations employing near infrared spectroscopy. In: Vibrational Spectroscopy. 2017 ; Vol. 90. pp. 21-30.

Bibtex - Download

@article{b810e5f7a4a843d0aa0a61224a71b648,
title = "Burned bones forensic investigations employing near infrared spectroscopy",
abstract = "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.",
keywords = "Burned bones,, FT-NIR,, Chemical elements,, Statistics, FT-NIR, Burned bones, Chemical elements",
author = "Cascant, {Mari Merce} and Sonia Rubio and Gianni Gallello and Agustin Pastor and Salvador Garrigues and {De la Guardia}, Miguel",
note = "{\textcopyright} 2017 Elsevier B.V. This is an author-produced version of the published paper. Uploaded in accordance with the publisher{\textquoteright}s self-archiving policy.",
year = "2017",
month = may,
doi = "10.1016/j.vibspec.2017.02.005",
language = "English",
volume = "90",
pages = "21--30",
journal = "Vibrational Spectroscopy",
issn = "0924-2031",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Burned bones forensic investigations employing near infrared spectroscopy

AU - Cascant, Mari Merce

AU - Rubio, Sonia

AU - Gallello, Gianni

AU - Pastor, Agustin

AU - Garrigues, Salvador

AU - De la Guardia, Miguel

N1 - © 2017 Elsevier B.V. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.

PY - 2017/5

Y1 - 2017/5

N2 - 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.

AB - 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.

KW - Burned bones,

KW - FT-NIR,

KW - Chemical elements,

KW - Statistics

KW - FT-NIR

KW - Burned bones

KW - Chemical elements

UR - http://www.scopus.com/inward/record.url?scp=85015107810&partnerID=8YFLogxK

U2 - 10.1016/j.vibspec.2017.02.005

DO - 10.1016/j.vibspec.2017.02.005

M3 - Article

VL - 90

SP - 21

EP - 30

JO - Vibrational Spectroscopy

JF - Vibrational Spectroscopy

SN - 0924-2031

ER -