Women’s Perfume: The smell of hands can reveal a person’s gender

The profile of a person’s hand scent compounds can be used to predict their gender, according to a new study led by Kenneth Furton of Florida International University, published July 5 in the open access journal PLOS ONE.

In criminal investigations, dogs have long been used to reliably identify and track people based on their scent. But while trials of human scent in the field are well established, researchers have made little progress analyzing human scent profiles in the lab.

In the new study, the researchers used an analytical technique called mass spectrometry to analyze the volatile odorous compounds found on the palms of 60 individuals, half male and half female. After identifying the compounds in each sample, the team performed a statistical analysis to see if they could determine the individual’s gender based on their scent profile. The analysis successfully predicted a person’s gender with an accuracy rate of 96.67%.

Robbery, assault and rape are all crimes that are often carried out with the hands of a perpetrator and therefore have the potential to leave valuable traces at the crime scene. The new study shows that it is possible to predict a person’s gender based on hand scents, and existing research on human odor indicates that scent compounds can also reveal a person’s age and racial or ethnic group. With further validation, the chemical and statistical analyzes presented in this paper could be used to uncover many details about a potential perpetrator solely through their hand scent profiles.

The authors add, “This approach to analyzing hand odor volatiles can be applied when other discriminatory evidence such as DNA is missing and allows for differentiation or class characterization such as gender, race, and age.”

#####

In your coverage, use this URL to provide access to the article available for free at PLOS ONE: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0286452

Citation: Frazier CJG, Gokool VA, Holness HK, Mills DK, Furton KG (2023) Multivariate regression modeling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS. PLoS UNO 18(7): e0286452. https://doi.org/10.1371/journal.pone.0286452

Author Countries: United States of America

Financing: These CF, KF, and DM authors received funding through a sub-award from the Center for Advanced Research in Forensic Science (CARFS), a National Science Foundation (NSF)-funded Industrial University Cooperative Research Center (IUCRC) at FIU (Award No. 1739805). https://iucrc.nsf.gov/centers/center-for-advanced-research-in-forensic-science/. Funders had no role in study design, data collection and analysis, decision to publish, or manuscript preparation.