Literature DB >> 19670872

Blood species identification for forensic purposes using Raman spectroscopy combined with advanced statistical analysis.

Kelly Virkler1, Igor K Lednev.   

Abstract

Forensic analysis has become one of the most growing areas of analytical chemistry in recent years. The ability to determine the species of origin of a body fluid sample is a very important and crucial part of a forensic investigation. We introduce here a new technique which utilizes a modern analytical method based on the combination of Raman spectroscopy and advanced statistics to analyze the composition of blood traces from different species. Near-infrared Raman spectroscopy (NIR) was used to analyze multiple dry samples of human, canine, and feline blood for the ultimate application to forensic species identification. All of the spectra were combined into a single data matrix, and the number of principle components that described the system was determined using multiple statistical methods such as significant factor analysis (SFA), principle component analysis (PCA), and several cross-validation methods. Of the six principle components that were determined to be present, the first three, which contributed over 90% to the spectral data of the system, were used to form a three-dimensional scores plot that clearly showed significant separation between the three groups of species. Ellipsoids representing a 99% confidence interval surrounding each species group showed no overlap. This technique using Raman spectroscopy is nondestructive and quick and can potentially be performed at the scene of a crime.

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Year:  2009        PMID: 19670872     DOI: 10.1021/ac901350a

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  12 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.  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

3.  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

4.  Assessment of the radiotherapy effect for nasopharyngeal cancer using plasma surface-enhanced Raman spectroscopy technology.

Authors:  Qiong Wu; Sufang Qiu; Yun Yu; Weiwei Chen; Huijing Lin; Duo Lin; Shangyuan Feng; Rong Chen
Journal:  Biomed Opt Express       Date:  2018-06-27       Impact factor: 3.732

5.  Blood identification at the single-cell level based on a combination of laser tweezers Raman spectroscopy and machine learning.

Authors:  Ziqi Wang; Yiming Liu; Weilai Lu; Yu Vincent Fu; Zhehai Zhou
Journal:  Biomed Opt Express       Date:  2021-11-12       Impact factor: 3.732

6.  NIR Raman spectra of whole human blood: effects of laser-induced and in vitro hemoglobin denaturation.

Authors:  P Lemler; W R Premasiri; A DelMonaco; L D Ziegler
Journal:  Anal Bioanal Chem       Date:  2013-10-27       Impact factor: 4.142

7.  Discriminant analysis of Raman spectra for body fluid identification for forensic purposes.

Authors:  Vitali Sikirzhytski; Kelly Virkler; Igor K Lednev
Journal:  Sensors (Basel)       Date:  2010-03-29       Impact factor: 3.576

Review 8.  Cognition of and Demand for Education and Teaching in Medical Statistics in China: A Systematic Review and Meta-Analysis.

Authors:  Yazhou Wu; Liang Zhou; Gaoming Li; Dali Yi; Xiaojiao Wu; Xiaoyu Liu; Yanqi Zhang; Ling Liu; Dong Yi
Journal:  PLoS One       Date:  2015-06-08       Impact factor: 3.240

9.  Ribose-induced Maillard Reaction as an Analytical Method for Detection of Adulteration and Differentiation of Chilled and Frozen-thawed Minced Veal.

Authors:  Masoumeh Akbarabadi; Mohammad Mohsenzadeh; Mohammad-Reza Housaindokht
Journal:  Food Sci Anim Resour       Date:  2020-04-30

Review 10.  Raman spectroscopy enables phenotyping and assessment of nutrition values of plants: a review.

Authors:  William Z Payne; Dmitry Kurouski
Journal:  Plant Methods       Date:  2021-07-15       Impact factor: 4.993

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