Nimi Chongtham, Chophi Rito, Singh Rajinder
Department of Forensic Science, Punjabi University, Patiala, Punjab, India.
J Forensic Sci. 2022 May;67(3):911-926. doi: 10.1111/1556-4029.14998. Epub 2022 Feb 1.
Electrical tapes are recovered during criminal investigations as physical evidence in cases of rape, kidnapping, and explosion incidents. The analysis of such evidence can provide an evidentiary link between the suspect, the victim, object, or the crime scene. In the present study, 25 brands of electrical tapes have been analyzed using ATR-FTIR (attenuated total reflectance Fourier transform infrared) spectroscopy. Samples (1 cm ) were analyzed in the mid IR (Infrared) region from 4000-600 cm , and the functional groups of various components have been profiled. Chemometric methods-PCA (principal component analysis) and PCA-LDA (linear discriminant analysis) have been employed to interpret the data and classify the samples into its respective classes. Preliminary assessment of sample clustering due to similar chemical composition was visualized using PCA. PCA-LDA applied for classification purpose yielded classification accuracy (calibration) of 92.98% for the adhesive side and 88% for the backing side. The validation results showed classification accuracy of 89.47% for the adhesive side and 84% for the backing side. Blind validation study was carried out using 5 samples, and classification accuracy of 100% and 80% was obtained for the adhesive and the backing side, respectively. In the current study, a preliminary substrate study was carried out, and the results showed that the backing samples could be more accurately matched to their correct source of origin than the adhesive side.
在强奸、绑架和爆炸事件等刑事案件调查中,电工胶带作为实物证据被找回。对此类证据的分析可以在嫌疑人、受害者、物体或犯罪现场之间建立证据联系。在本研究中,使用衰减全反射傅里叶变换红外光谱(ATR-FTIR)对25个品牌的电工胶带进行了分析。对1厘米的样品在4000 - 600厘米的中红外区域进行分析,并对各种成分的官能团进行了剖析。采用化学计量学方法——主成分分析(PCA)和主成分线性判别分析(PCA-LDA)来解释数据并将样品分类到各自的类别中。使用PCA可视化了由于化学成分相似导致的样品聚类的初步评估。用于分类目的的PCA-LDA对胶带粘性面的分类准确率(校准)为92.98%,对胶带背面的分类准确率为88%。验证结果表明,粘性面的分类准确率为89.47%,背面的分类准确率为84%。使用5个样品进行了盲法验证研究,粘性面和背面的分类准确率分别为100%和80%。在当前研究中,进行了一项初步的基材研究,结果表明,与粘性面相比,胶带背面的样品能够更准确地与其正确的来源相匹配。