Literature DB >> 33137213

Discrimination of vermilion (sindoor) using attenuated total reflectance fourier transform infrared spectroscopy in combination with PCA and PCA-LDA.

Rito Chophi1, Sweety Sharma1, Rajinder Singh1.   

Abstract

Vermilion (sindoor) is considered sacred in the Hindu religion, and it is used routinely throughout the world by married Hindu women along the line of hair parting during marriage ceremonies, religious rituals, and festivals. Owing to its esthetic appeal, it is sometimes illegally used as a food additive; leading to potential health risks. Therefore, due to the aforementioned reasons, vermilion can likely be encountered as trace evidentiary material during crime investigations, particularly in cases of sexual and physical offenses against women. Analysis of such evidence can provide a link between the criminal, the victim, and the crime scene and thereby be utilized as associative evidence in the court of law. In the present study, ATR-FTIR spectroscopy has been used for the examination of 37 different manufacturers of vermilion. Chemometric methods such as principal component analysis (PCA) and PCA-LDA were performed on the obtained spectra for objective interpretation of results. PCA delivered 99.06% discrimination of samples while PCA-LDA employed for classification purpose delivered 95.25% calibration accuracy and 88% validation accuracy. Afterward, the validity of the chemometric methods employed was tested by blind testing of samples. A preliminary study on the effect of selected substrates (cotton cloth, tissue paper, glass, and plastic) on sample analysis indicates that while sample stain on substrates could be linked to its parent source even after a month, linking an aged samples (after 8 months) could be hindered due to evaporation of components present in vermilion. Overall, the current methodology utilized has a potential prospect in future forensic-casework.
© 2020 American Academy of Forensic Sciences.

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Keywords:  attenuated total reflectance Fourier transform infrared spectroscopy; classification; discrimination; linear discriminant analysis; principal component analysis; vermilion

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Year:  2020        PMID: 33137213     DOI: 10.1111/1556-4029.14609

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  1 in total

1.  Applying a deep residual network coupling with transfer learning for recyclable waste sorting.

Authors:  Kunsen Lin; Youcai Zhao; Xiaofeng Gao; Meilan Zhang; Chunlong Zhao; Lu Peng; Qian Zhang; Tao Zhou
Journal:  Environ Sci Pollut Res Int       Date:  2022-07-26       Impact factor: 5.190

  1 in total

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