Sharma Anjali, Chauhan Rohini, Kumar Raj, Mankotia Priyanka, Verma Rajesh, Sharma Vishal
Institute of Forensic Science & Criminology, Panjab University, Chandigarh 160014, India.
Forensic Science Laboratory, Madhuban, Karnal, Haryana 132037, India.
Spectrochim Acta A Mol Biomol Spectrosc. 2021 Sep 5;258:119803. doi: 10.1016/j.saa.2021.119803. Epub 2021 Apr 17.
Facial creams are considered to be essential beauty items and are used by both females and males on an everyday basis. These can be encountered as an evidentiary material in criminal investigations, particularly in cases related to sexual and physical assaults against women. These are found in trace amounts and therefore their analysis is difficult and also, it must be through non-destructive methods. In the present work ATR-FTIR spectroscopy was employed for the discrimination of 57 samples of face creams out of which 31 were non-herbal and 26 were from herbal category. Visual analysis of the obtained Spectra was done for discrimination purposes but the method was prone to human error and laborious too. The spectroscopic results were analyzed with PCA (Principal Component Analysis) and PLS-DA (Partial least square discriminant analysis) methods. A segregation of samples was seen in the PCA plots to some extent. The class separation and prediction of the samples was performed using PLS-DA method. A good classification was achieved between herbal and non-herbal samples using PLS-DA method. Further, validation of the model was also performed by testing 10 unknown samples.
面霜被认为是必不可少的美容用品,无论男女都每天使用。在刑事调查中,尤其是在涉及对女性的性侵犯和身体攻击的案件中,面霜可能会作为证据材料出现。它们的含量很少,因此对其进行分析很困难,而且必须通过无损方法进行。在本研究中,采用衰减全反射傅里叶变换红外光谱(ATR-FTIR)对57种面霜样品进行鉴别,其中31种为非草本面霜,26种为草本面霜。为了鉴别目的,对获得的光谱进行了目视分析,但该方法容易出现人为误差且费力。用主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)方法对光谱结果进行了分析。在PCA图中可以看到样品在一定程度上的分离。使用PLS-DA方法对样品进行类别分离和预测。使用PLS-DA方法在草本和非草本样品之间实现了良好的分类。此外,还通过测试10个未知样品对模型进行了验证。