Preliminary Evaluation of Gunshot Residue (GSR) Using 3-Aminophenol as a Substitute in Modified Griess Test

Abstract

In forensic ballistics, gunshot residue (GSR) particles can be detected using screening or presumptive tests which are mainly focused on the chromophoric reaction. Most tests serve as an initial indication for a forensic investigator at the crime scene before instrumental analysis for definitive identification. The screening methods are known to be convenient, have fast analysis, and minimal preparation. In GSR analysis, the well-known method of detecting GSR known as the Modified Griess Test (MGT) requires acid and heat for the reaction. Therefore, this study demonstrated a new and rapid screening test named the Rapid Griess Test (RGT) for the detection of GSR. This study intends to improve the functionality of previous screening reagents in determining nitrite (NO2–), the composition present after shooting activity. To do this, chemical reagents with an amino group, 3-aminophenol, were substituted with alpha-naphthol. The experiment showed that the reactions were positive color changes using standard NO2– and real GSR samples. The diazotization reactions involving sulfanilic acid and 3-aminophenol produced azo dyes that changed the solution from colorless to orange in the presence of NO2–. The RGT reagent will make it possible to avoid using heat and the addition of acetic acids in a sample to form chromophoric reactions. Moreover, the colorimetric method using Video Spectral Comparator (VSC) showed that RGT had higher intensity of the orange color when compared to MGT.

Teaching Old Presumptive Tests New Digital Tricks with Computer Vision for Forensic Applications

“…Applications span handwriting recognition, 12 face detection, 13 security screening, 13 blood stain characterisation, [14][15][16] identification of chemical warfare agents, 17 quantifying explosives, 18 and ballistics. 19 More specifically within presumptive testing, smart phoneenabled single imaging approaches have been applied to, for example, recreational drug detection in drinks, 20 risk-mitigating false positives in cocaine detection, 21 bodily fluid identification, 15 digitalising amphetamine spot tests, 22 and micro-device fabrication for more objective spot testing. 23…”

Teaching old presumptive tests new digital tricks with computer vision for forensic applications

“…Applications span handwriting recognition, 12 face detection, 13 security screening, 13 blood stain characterisation, 14–16 identification of chemical warfare agents, 17 quantifying explosives, 18 and ballistics. 19…”