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Semen is most frequently encountered body fluid in forensic cases apart from blood especially in sexual assault cases. The presence and absence of semen can help in conviction or exoneration of a suspect by either confirming or refuting the claims put forward by the suspect and the victim. However, in the wake of limited studies on non-destructive and rapid analysis of semen, it is fairly difficult. Therefore, it is an increasing demand to pioneer the application of available analytical methods in such manner that non-destructive, automated, rapid, and reliable identification and discrimination of body fluids can be established. In the present study, such a methodological application of attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy has been put forward as one of the initial steps towards the identification and discrimination/classification of seminal fluid from vaginal fluid and other human biological as well as non-biological look-alike semen substances using chemometric tools which are principal component analysis (PCA), partial least square regression (PLSR), and linear discriminant analysis (LDA). Effect of other simulated factors such as substrate interference, mixing with other body fluids, dilutions, and washing and chemical treatments to the samples has been studied. PCA resulted in 98.8% of accuracy for the discrimination of seminal fluid from vaginal fluid whilst 100% accuracy was obtained using LDA method. One hundred percent discrimination was achieved to discriminate semen from other biological fluids using PLSR and LDA, and from non-biological substances using PCA-LDA models. Furthermore, results of the effect of substrates, chemical treatment, mixing with vaginal secretions, and dilution have also been described.

Body fluids are one of the most important pieces of evidence encountered in forensic cases especially in cases of sexual assault. Analysis of such evidence can help to establish a link between the perpetrator, the victim, and the crime scene and thereby assist in crime reconstruction. However, one of the biggest challenges faced by the investigators in sexual assault cases is that of ascertaining the issue of consent of the victim. In this matter, differentiation of menstrual blood (either in dried or stained form) from traumatic peripheral blood can give a potential solution on this particular aspect. A number of studies have been attempted to differentiate these two body fluids using various biochemical and serological methods. However, the methods employed are limited by factors such as sample destructivity and non-specificity, and the methods are susceptible to false positive results. In the present study, the scope of attenuated total reflectance (ATR)-Fourier transform infrared (FT-IR) spectroscopy in discriminating samples of menstrual blood and peripheral blood has been investigated, in combination with chemometric tools such as principal component analysis (PCA), partial least square regression (PLSR), and linear discriminant analysis (LDA). PCA resulted in 93.3% accuracy, whereas PLSR and LDA resulted in 100% accuracy for the discrimination of peripheral blood from menstrual blood. Application of PCA for the discrimination of menstrual blood from vaginal fluid and seminal fluid delivered 100% classification. Similarly, 100% classification was achieved while differentiating between menstrual blood and blood look-alike substances. Furthermore, in the current study, the effect of substrates on the analysis of menstrual blood has also been studied and described.

The analysis of body fluids is of utmost importance in forensic casework since many biological fluids contain DNA. The ATR FT-IR spectroscopy is an emerging approach for the confirmatory, rapid, facile, non-destructive, and on-site identification and differentiation of body fluid stains. Notwithstanding the ATR FT-IR spectroscopy is showing a colossal promise towards the identification of body fluids, and further forensic enquiry related to substrate’s interference is still in its infancy stage. Therefore, in the present proof-of-concept study, the ATR FT-IR spectroscopy has been utilized for the detection of vaginal fluid stains and to investigate the effect of different substrates on sample analysis. Simulated vaginal fluid samples were prepared on some selected substrates such as glass, plastic, floor tiles, polished wood, paper, and on various cloth substrates and analyzed without any prior sample preparation. Results suggested that vaginal fluid can be successfully detected on non-porous substrates, but it turned out to be a challenging task on porous substrates. However, on the basis of certain peaks, successful identification of vaginal fluid can be done directly on various case-related substrates. The best approach for the detection of vaginal fluid depends upon the nature of substrates and type of interference encountered. In addition, 10 non-vaginal fluid substances which look similar to vaginal fluid and which may lead to misclassification of vaginal fluid or can deliver false-positive results were also analyzed. The spectra of look-alike substances were classified using the chemometric tools such as PCA and PCA-LDA. The developed PCA model successfully classified all vaginal fluid samples from non-vaginal fluid substances with 100% accuracy, specificity, and sensitivity rate. In addition, the effects of other factors such as aging and mixing with other body fluids have also been studied and the results have been described.

Shoe polish smears or stains are encountered as evidentiary material on a variety of substrates, particularly in cases related to sexual and physical assault, murder, theft, and robbery. This trace evidence can be used as proof of contact to narrow down the search in a criminal investigation. The identification and differentiation of samples with similar composition and the same hue can be a difficult task for the investigator. In the present work, the scope of Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy for discriminating shoe polish samples of 15 different brands is investigated in combination with chemometric tools that is principal component analysis. The discriminating power of visual analysis is 99.04 %, while in principal component analysis it is 98.09 %, which is highly significant. The blind test is carried out with unknown samples to the analyst, to predict their respective sample source. Intra-brand variation, homogeneity and the effect of. different substrates on sample analysis are also studied. The reported method provides considerable results for the identification and differentiation of shoe polish samples of different brands. The stains on substrates could be identified and linked to their parent source as well.

During the past few decades, Raman spectroscopy has progressed and captivated added attention in the field of science. However, the application of Raman spectroscopy is not limited to the field of forensic science and analytical chemistry; it is one of the emerging spectroscopic techniques, utilized in the field of forensic science which in turn could be a supporting tool in the law and justice system. The advantage of Raman spectroscopy over the other conventional techniques is that it is rapid, reliable, and non-destructive in nature with minimal or no sample preparation. The quantitative and qualitative analysis of evidence from biological and non-biological origins could easily be performed by using Raman spectroscopy. The forensic domain is highly complex with multidisciplinary branches, and therefore a plethora of techniques are utilized for the detection, identification, and differentiation of innumerable pieces of evidence for the purpose of law and justice. Herein, a systematic review is carried out on the application of Raman spectroscopy in the realm of forensic biology and serology considering its usefulness in practical perspectives. This review paper highlights the significance of modern techniques, including micro-Raman spectroscopy, confocal Raman spectroscopy, surface-enhanced Raman spectroscopy, and paper-based surface-enhanced Raman spectroscopy, in the field of Raman spectroscopy. These techniques have demonstrated notable advancements in terms of their applications and capabilities. Furthermore, to comprehensively capture the progress in the development of Raman spectroscopy, all the published papers which could be retrieved from the available databases from the year 2007 to 2022 were incorporated.

Blood is often encountered on different types of substrates in criminal investigations. Among such substrates, blood stained fabrics are one of the most commonly encountered evidence. Analysis of bloodstains on fabrics is restricted due to interference of fabric dyes, color of fabric which hampers visual identification, and limited sample quantity. Over the years, a plethora of research has been conducted to analyze recovered blood traces, however, the methods employed are limited by factors such as sample destructibility, chronophagus processing, and vulnerability to false positive results. To circumvent the aforementioned limitations, use of ATR FT-IR spectroscopy has surged as a non-destructive and reliable tool for the detection of traces of blood and other body fluids on fibers. In the present study, an attempt has been made to detect traces of blood in fibers of different types and colors using ATR FT-IR spectroscopy. The obtained results unequivocally concluded that by using ATR FT-IR spectroscopy blood can be successfully detected even on a single fiber through characteristic peaks positioned at 1650 cm-1 and 1543 cm-1 corresponding to amide I and amide II. On the basis of the IR marked protein region (1700-1500 cm-1) bloodstains could easily be discriminated from the blank fibers (except human hair, which overlapped with the peaks of bloodstained fibers) by using PCA chemometric tool. Although, further investigations are needed to be conducted, this proof-of-concept study establishes the potential use of ATR FT-IR spectroscopy for the non-destructive, rapid, eco-friendly, and reliable identification of blood traces from a single fiber due to its inherent surface sensitivity and smaller penetration depth.

Raman spectroscopy, complemented by advanced techniques such as surface-enhanced Raman spectroscopy (SERS) and micro-Raman spectroscopy, is increasingly expanding its forensic applications in analysing trace materials. Forensic practitioners are adopting it more widely due to its simplicity, speed, non-destructive nature, and minimal or no sample preparation required. Despite certain limitations, such as relatively low sensitivity and significant fluorescence interference, Raman spectroscopy has been greatly enhanced by advanced techniques like SERS and Resonance Raman Spectroscopy, which effectively mitigate these issues and help unlock the full potential of Raman analysis. This review compiles extensive data from three major databases—Web of Science, Scopus, and Google Scholar—to demonstrate the utility of Raman spectroscopic techniques in the forensic analysis of trace samples, particularly in the examination of inks, dyes, gunshot residues, paints, and related substances. The study shows that Raman spectroscopy has significantly simplified the analysis of forensic traces, offering a promising approach for the on-site examination of a wide range of traces with improved efficiency and accuracy. [Display omitted] •Raman Spectroscopy offers rapid, non-destructive analysis with minimal sample preparation.•Advanced methods like Resonance Raman Spectroscopy and Surface-Enhanced Raman Spectroscopy enhance sensitivity and mitigate interference.•Raman advances help detect trace materials like inks, dyes, gunshot residue, paints, and soils.•Its versatility and robustness enable reliable and efficient trace analysis.•It offers a promising method for on-site analysis of various forensic trace materials

Examination of hair with its intact root is commonly used for DNA profiling of the donor. However, its use for gathering other types of information is less explored. Using attenuated total reflectance-Fourier transform infrared spectroscopy, the present study aims to explore other relevant aspects in a non-destructive manner for forensics. Determining the sex and blood group of human hair samples were the major goals of the study. Sex determination was accomplished by analyzing the differential vibrational intensities and stretching of various chemical groups associated with hair and its proteins. Statistical inference of spectral data was performed using chemometric algorithms such as PCA and PLS-DA. The PLS-DA model determined sex with 100% accuracy and blood grouping with an average accuracy of 95%. The present study is the first of its kind to determine sex and blood grouping from human scalp hair shafts, as far as the author knows. By acting as a preliminary screening test, this study could have significant implications for forensic analysis of crime scene samples. Human and synthetic hair were used in validation studies, resulting in 100% accuracy, specificity, and sensitivity, with 0% false positives and false negatives. The technique ATR FTIR spectroscopy could complement the currently used methods of hair analysis such as physical examination and mitochondrial or genomic DNA analysis.

Grass evidence often encountered at the crime scene, helps in establishing the primary as well as secondary crime scenes. Due to the limited quantity and intricate nature of samples, there is a need for fast, sensitive and reliable techniques for the effective analysis of this vital evidence. In the current study, an attempt is made to study the feasibility of ATR FT-IR in combination with chemo¬metric tools for chemical characterization and species dif¬ferentiation of grass stains. Ten different grass species belonging to three sub¬families, Panicoideae, Chlorodoidae, and Bambusoideae, were collected and analyzed by using the ATR FT-IR spectroscopy combined with the PLSR chemometric tool. Results showed a clear difference between samples of Panicoideae, Chlorodoidae, and Bambusoideae subfami¬lies, and between species of each subfamily. To analyse the performance of the classification model, a set of 10 unknown/blind samples (unknown to the analyst) were randomly selected from the training dataset and all un¬known/blind samples were accurately assigned in their corresponding group. ATR FT-IR spectroscopy requires minimal sample preparation and can be successfully used as an eco-friend¬ly, non-destructive, and reliable alternative to other exist¬ing methods.