Universal detection of body fluid traces in situ with Raman hyperspectroscopy for forensic purposes: Evaluation of a new detection algorithm (HAMAND) using semen samples

Abstract

Towards closing the technological gaps in forensic science, Raman spectroscopy has been a boon to the field. One area that this technique shows exceptional promise is in body fluid identification and characterization, but substrate interference remains a major impediment to its practical implementation. Here, we present an approach for the universal detection of body fluids regardless of the substrate. This approach, which is based on Raman hyperspectroscopy and multivariate curve resolution, was applied to datasets representing simulated semen evidence. In every instance, the signal of the fluid was extracted and matched to a reference of semen. This approach has immediate application for body fluid detection and allows for a universal, automatic, nondestructive, on‐field method for confirmatory identification of body fluid traces at a crime scene. This approach is applicable where an analyte is either a minor contributor or spatially distributed on a strongly interfering substrate.

Vesicular Membrane with Structured Interstitial Water

“…Sample solutions were prepared and sealed in containers prior to Raman measurements. HAMAND (hypothetical addition multivariate analysis with numerical differentiation) is a numerical version of the well-known standard addition method. , It combines the principle of the standard addition method with multivariate curve resolution, hence separating out the known target spectrum from a complicated system spectrum. A number of hypothetical model spectra S j are generated numerically by adding to the observed the known pure water spectrum S std multiplied with hypothetical addition coefficients c j : S j = S unkn + c j × S std , here S unkn means the solution spectra.…”

Potential of Spatially Offset Raman Spectroscopy for Detection of Zebra Chip and Potato Virus Y Diseases of Potatoes (Solanum tuberosum)

“…In other cases, the variation between spectra can be subtle shifts in band position and/or intensity, requiring statistical methods, such as multivariate statistical analysis, to differentiate them. The potential of RS coupled with multivariate statistical analysis was previously demonstrated in many fields including forensics, art, and medicine. − Our group has demonstrated the potential of RS coupled with multivariate statistics for the detection of fungal, viral, and bacterial diseases on a broad spectrum of plants. − Specifically, we showed that RS could be used for the detection of Candidatus Liberibacter asiaticus that causes Huanglongbing, or citrus greening, on orange and grapefruit trees. , While Raman is quite powerful in detecting distinct chemical groups on a sample surface, its ability to probe deeper layers is limited.…”

Discrimination between human and animal blood by attenuated total reflection Fourier transform-infrared spectroscopy

“…A similar problem has been tackled while Raman spectroscopy was used for the identification of biological stains on various interfering substrates 34 , 35 . Most recently, a multivariate statistical approach has been developed for detecting trace amounts of semen on strongly interfering substrates using Raman spectroscopy 36 .…”