Literature DB >> 24681972

Discrimination of human and animal blood traces via Raman spectroscopy.

Gregory McLaughlin1, Kyle C Doty1, Igor K Lednev2.   

Abstract

The characterization of suspected blood stains is an important aspect of forensic science. In particular, determining the origin of a blood stain is a critical, yet overlooked, step in establishing its relevance to the crime. Currently, assays for determining human origin for blood are time consuming and destructive to the sample. The research presented here demonstrates that Raman spectroscopy can be effectively applied as a non-destructive technique for differentiating human blood from a wide survey of animal blood. A Partial Least Squares-Discriminant Analysis (PLS-DA) model was built from a training set of the near infrared Raman spectra from 11 species. Various performance measures, including a blind test and external validation, confirm the discriminatory performance of the chemometric model. The model demonstrated 100% accuracy in its differentiation between human and nonhuman blood. These findings further demonstrate a great potential of Raman spectroscopy to the field of serology, especially for species identification of a suspected blood stain.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Blood; Chemometrics; Human origin; Raman spectroscopy; Serology

Mesh:

Year:  2014        PMID: 24681972     DOI: 10.1016/j.forsciint.2014.02.027

Source DB:  PubMed          Journal:  Forensic Sci Int        ISSN: 0379-0738            Impact factor:   2.395


  7 in total

1.  Dual-model analysis for improving the discrimination performance of human and nonhuman blood based on Raman spectroscopy.

Authors:  Haiyi Bian; Peng Wang; Ning Wang; Yubing Tian; Pengli Bai; Haowen Jiang; Jing Gao
Journal:  Biomed Opt Express       Date:  2018-07-05       Impact factor: 3.732

2.  Blood identification and discrimination between human and nonhuman blood using portable Raman spectroscopy.

Authors:  J Fujihara; Y Fujita; T Yamamoto; N Nishimoto; K Kimura-Kataoka; S Kurata; Y Takinami; T Yasuda; H Takeshita
Journal:  Int J Legal Med       Date:  2016-06-05       Impact factor: 2.686

3.  Species identification of bloodstains by ATR-FTIR spectroscopy: the effects of bloodstain age and the deposition environment.

Authors:  Hancheng Lin; Yinming Zhang; Qi Wang; Bing Li; Shuanliang Fan; Zhenyuan Wang
Journal:  Int J Legal Med       Date:  2017-08-18       Impact factor: 2.686

4.  Blood species identification based on deep learning analysis of Raman spectra.

Authors:  Shan Huang; Peng Wang; Yubing Tian; Pengli Bai; DaQing Chen; Ce Wang; JianSheng Chen; ZhaoBang Liu; Jian Zheng; WenMing Yao; JianXin Li; Jing Gao
Journal:  Biomed Opt Express       Date:  2019-11-06       Impact factor: 3.732

5.  Direct differentiation of whole blood for forensic serology analysis by thread spray mass spectrometry.

Authors:  Sierra Jackson; Benjamin S Frey; Maia N Bates; Devin J Swiner; Abraham K Badu-Tawiah
Journal:  Analyst       Date:  2020-07-07       Impact factor: 4.616

6.  Classification and discrimination of real and fake blood based on photoacoustic spectroscopy combined with particle swarm optimized wavelet neural networks.

Authors:  Zhong Ren; Tao Liu; Guodong Liu
Journal:  Photoacoustics       Date:  2021-06-01

7.  Surface enhanced Raman spectroscopy as a novel tool for rapid quantification of heroin and metabolites in saliva

Authors:  Ramazan Akçan; Mahmut Şerif Yildirim; Hasan Ilhan; Burcu Güven; Uğur Tamer; Necdet Sağlam
Journal:  Turk J Med Sci       Date:  2020-08-26       Impact factor: 0.973

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.