In Situ Identification of Semen Stains on Common Substrates via Raman Spectroscopy,,

The spectroscopic identification of body fluids in situ is a major objective in forensic science. This approach offers the confirmatory, nondestructive, rapid, and on‐scene identification of various body fluids. Although Raman spectroscopy has shown tremendous promise toward this goal in prior proof‐of‐concept experiments, a significant challenge which still remains is substrate interference. Here, an approach for detecting semen stains in situ on various substrates using Raman spectroscopy is explored. Simulated semen evidence was prepared on skin, glass, and various fabrics. Raman data were accumulated from stains without any pretreatment using a common confocal mapping spectrometer using 785 nm laser excitation. The results demonstrate that the spectroscopic interferences encountered by substrates can be reduced and eliminated using a combination of existing subtraction techniques and chemometric models. Heterogeneous substrates proved most challenging, however, automatic subtraction treatment, and location of fluid hotspots was able to elucidate a clear spectroscopic signature of semen in every instance.     

Raman spectroscopy offers great potential for the nondestructive confirmatory identification of body fluids

Raman spectroscopy was used to compare body fluids commonly found at crime scenes in a nondestructive manner. The dry traces of semen, vaginal fluid, sweat, saliva, and blood were analyzed using confocal Raman microscopy with a 785-nm excitation. The results show that the five fluids can be differentiated from one another by visual comparison of their Raman spectra, and that the laser radiation does not damage the sample. The Raman signature of each body fluid is specific and correlates with the known composition of the fluid. Dry traces of human and canine semen exhibited distinctly different Raman signatures. Overall, this preliminary study demonstrates the great potential of Raman spectroscopy for nondestructive, confirmatory identification of body fluids for forensic purposes.     

Advanced statistical analysis of Raman spectroscopic data for the identification of body fluid traces: Semen and blood mixtures

Conventional confirmatory biochemical tests used in the forensic analysis of body fluid traces found at a crime scene are destructive and not universal. Recently, we reported on the application of near-infrared (NIR) Raman microspectroscopy for non-destructive confirmatory identification of pure blood, saliva, semen, vaginal fluid and sweat. Here we expand the method to include dry mixtures of semen and blood. A classification algorithm was developed for differentiating pure body fluids and their mixtures. The classification methodology is based on an effective combination of Support Vector Machine (SVM) regression (data selection) and SVM Discriminant Analysis of preprocessed experimental Raman spectra collected using an automatic mapping of the sample. This extensive cross-validation of the obtained results demonstrated that the detection limit of the minor contributor is as low as a few percent. The developed methodology can be further expanded to any binary mixture of complex solutions, including but not limited to mixtures of other body fluids.     

Forensic Identification of Blood in the Presence of Contaminations Using Raman Microspectroscopy Coupled with Advanced Statistics: Effect of Sand,Dust, and Soil

Body fluid traces recovered at crime scenes are among the most common and important types of forensic evidence. However, the ability to characterize a biological stain at a crime scene nondestructively has not yet been demonstrated. Here, we expand the Raman spectroscopic approach for the identification of dry traces of pure body fluids to address the problem of heterogeneous contamination, which can impair the performance of conventional methods. The concept of multidimensional Raman signatures was utilized for the identification of blood in dry traces contaminated with sand, dust, and soil. Multiple Raman spectra were acquired from the samples via automatic scanning, and the contribution of blood was evaluated through the fitting quality using spectroscopic signature components. The spatial mapping technique allowed for detection of “hot spots” dominated by blood contribution. The proposed method has great potential for blood identification in highly contaminated samples.