The use of crime scene detection dogs to locate semen stains on different types of fabric

A. van Dam, A. Schoon, S.F. Wierda, E. Heeringa, M.C.G. Aaldersa

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)

Abstract

In sexual assault cases, the detection and identification of semen is extremely important as this type of evidence can be used as a source for investigative leads and contributes to case evidence. However, the detection of semen stains is often difficult, even indoors, because of different (environmental) factors, such as substrate type, coloured items and large search areas. In 2015, a project was initiated by the Dutch police to evaluate the feasibility of the use of detection dogs to locate semen stains in forensic practise. Since promising results were obtained, here, a double-blind study was designed to investigate how these detection dogs can optimally be implemented in the current work flow of crime scene investigators and to compare the dog's sensitivity and specificity with current detection methods. The performance of the detection dogs was compared to three commonly used detection methods for semen, (i) forensic light sources (FLS), (ii) the RSID semen field kit and (iii) the enzymatic Acid Phosphatase (AP)-test on semen deposited at different types of fabrics. A 100% sensitivity and specificity for the detection of semen stains using the detection dogs was obtained, compared to an overall sensitivity and specificity of 76.3% and 100% for FLS, 81.6% and 100% for RSID-test, and 92.1% and 100% for AP-test, respectively. Especially, on fabrics with a pattern or interfering fluorescent properties, detection dogs demonstrated to be of additional value to locate the semen stains. We recommend to use the following order of testing, FLS, detection dog, AP-test and RSID test in a forensic workflow.
Original languageEnglish
Article number109907
Number of pages6
JournalForensic Science International
Volume302
Early online date30 Jul 2019
DOIs
Publication statusPublished - Sept 2019

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