Background/Objectives: Body fluid identification is essential in sexual assault investigations because it supports crime scene reconstruction and guides DNA analysis. However, biological traces are often limited, so it is necessary to maximize information from a single sample while minimizing consumption. Evaluation of body fluids by methods of different nature could enhance this detection without losing evidence. This study assessed the analytical compatibility of an integrated forensic workflow combining stain localization, body fluid identification, and DNA profiling to detect semen and saliva on different substrates. Methods: Semen, saliva, and semen–saliva mixtures were deposited on non-porous substrates (plastic, glass, and leaves) and porous substrates (cotton, denim, and leather). Semen stains were located using STK Spray® Sperm Tracker™ or STK Lab® Sperm Tracker™, while saliva was mapped using AmylasePaper. Samples were subsequently tested with the SERATEC® PAM test for simultaneous detection of prostate-specific antigen (PSA) and α-amylase. DNA was extracted and quantified, followed by short tandem repeat (STR) profiling. Results: Sperm Tracker successfully located semen stains on all tested substrates, including stains aged for five days, while AmylasePaper detected saliva stains without observable interference from semen under the tested conditions. Neither mapping procedure interfered with the other or with subsequent PAM testing. PAM test correctly identified semen and saliva individually and in mixtures after all mapping steps. DNA was successfully recovered following the complete workflow, and full STR profiles were obtained from all non-porous samples and from porous samples with sufficient DNA quantities. Conclusions: The proposed workflow enables sequential localization, protein-based identification, and genetic characterization of semen and saliva while preserving evidentiary value. These findings support its application in sexual assault investigations to maximize biological information recovery while reducing sample consumption.
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Hassan et al. (2026) studied this question.
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