衰减全反射
血迹
样品(材料)
体液
犯罪现场
漫反射红外傅里叶变换
人类血液
色谱法
傅里叶变换
红外光谱学
分析化学(期刊)
模式识别(心理学)
化学
人工智能
计算机科学
数学
病理
医学
生理学
数学分析
生物化学
有机化学
光催化
催化作用
政治学
法学
作者
Shveta Sharma,Rito Chophi,Jaskirandeep Kaur Jossan,Rajinder Singh
标识
DOI:10.1177/00258024211010926
摘要
The most important task in a criminal investigation is to detect and identify the recovered biological stains beyond reasonable scientific doubt and preserve the sample for further DNA analysis. In the light of this fact, many presumptive and confirmatory tests are routinely employed in the forensic laboratories to determine the type of body fluid. However, the currently used techniques are specific to one type of body fluid and hence it cannot be utilized to differentiate multiple body fluids. Moreover, these tests consume the samples in due process, and thus it becomes a great limitation especially considering the fact that samples are recovered in minute quantity in forensic cases. Therefore, such limitations necessitate the use of non-destructive techniques that can be applied simultaneously to all types of bodily fluids and allow sample preservation for further analysis. In the current work, attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy has been used to circumvent the aforementioned limitations. The important factors which could influence the detection of blood such as the effect of substrates, washing/chemical treatment, ageing, and dilution limits on the analysis of blood have been analysed. In addition, blood discrimination from non-blood substance (biological and non-biological in nature) has also been studied. Chemometric technique that is PCA-LDA has been used to discriminate blood from other body fluids and it resulted in 100% accurate classification. Furthermore, blood and non-blood substances including fake blood have also been classified into separate clusters with a 100% accuracy, sensitivity, and specificity. All-inclusive, this preliminary study substantiates the potential application of ATR-FTIR spectroscopy for the non-destructive identification of blood traces in simulated forensic casework conditions with 0% rate of false classification.
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