Publication: Forensic examination of textile fibres using Raman imaging and multivariate analysis
| dc.contributor.author | Ortega-Ojeda, Fernando E. | |
| dc.contributor.author | García-Ruiz, Carmen | |
| dc.contributor.author | Zapata Arráez, Félix | |
| dc.contributor.department | Química Analítica | es |
| dc.contributor.other | Facultades,Servicios y Escuelas::Facultades de la UMU::Facultad de Química | es |
| dc.date.accessioned | 2025-09-03T07:18:09Z | |
| dc.date.available | 2025-09-03T07:18:09Z | |
| dc.date.issued | 2021-12-03 | |
| dc.description | © 2021 The Author(s). This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. This document is the Published version of a Published Work that appeared in final form in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. To access the final edited and published work see https://doi.org/10.1016/j.saa.2021.120695 | |
| dc.description.abstract | Vibrational spectroscopic techniques have shown to be highly suitable for the identification and comparison of textile fibres and clothing fabrics. On the other hand, new chemical imaging modes based on these spectroscopic techniques are becoming useful in multiple fields. This is particularly important to, for instance, chemically visualize and screen different samples including forensic evidence (crime scene investigation), chemical and food products (quality control), biological tissues and living beings (medical imaging), among others. This study explores the forensic examination and selective chemical visualization of textile fibres and clothing fabrics using Raman imaging. Four experiments were performed, which were focused on the screening of (i) white different materials made of 100 % cotton (gauze, cotton wool, t-shirt, and swab), (ii) polyester and cotton fabrics evidence of the same colour, (iii) five different coloured cotton fabrics, and (iv) textile fibres of different materials (acrylic, cotton, nylon, polyester, and silk). Several methods of multivariate chemometric analysis including principal component analysis (PCA), multivariate analysis of variance (MANOVA), and multivariate curve resolution (MCR) were applied to enhance the limited visual comparison of the spectra accomplished with the unaided eye. The results evidenced the suitability of Raman imaging to statistically discriminate textile fibres and fabrics due to the chemical composition of both the clothing material and the dyestuff. | es |
| dc.format | application/pdf | es |
| dc.format.extent | 10 | es |
| dc.identifier.citation | Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 268 (2022) 120695 | |
| dc.identifier.doi | https://doi.org/10.1016/j.saa.2021.120695 | |
| dc.identifier.issn | Print: 1386-1425 | |
| dc.identifier.issn | Electronic: 1873-3557 | |
| dc.identifier.uri | http://hdl.handle.net/10201/158061 | |
| dc.language | eng | es |
| dc.publisher | Elsevier B.V. | es |
| dc.relation | Sin financiación externa a la Universidad | es |
| dc.relation.publisherversion | https://doi.org/10.1016/j.saa.2021.120695 | es |
| dc.rights | info:eu-repo/semantics/openAccess | es |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.subject | Raman Imaging | es |
| dc.subject | Chemometrics | es |
| dc.subject | PCA | es |
| dc.subject | MCR | es |
| dc.subject | MANOVA | es |
| dc.subject | Cotton | es |
| dc.subject | Nylon | es |
| dc.subject | Polyester | es |
| dc.subject | Silk | es |
| dc.subject | Acrylic | es |
| dc.subject.other | CDU::5 - Ciencias puras y naturales::54 - Química::543 - Química analítica | es |
| dc.title | Forensic examination of textile fibres using Raman imaging and multivariate analysis | es |
| dc.type | info:eu-repo/semantics/article | es |
| dspace.entity.type | Publication | es |
| relation.isAuthorOfPublication | 353fd926-6063-4cbb-a5ca-ae9860360e17 | |
| relation.isAuthorOfPublication.latestForDiscovery | 353fd926-6063-4cbb-a5ca-ae9860360e17 |
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