Affiliation:
1. Chair of Aroma and Smell Research Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany
2. Machine Learning & Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany
3. Institute for Biomedicine of Aging Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Nuremberg Germany
4. Fraunhofer Institute for Process Engineering and Packaging IVV Freising Germany
Abstract
AbstractIt has been reported that a distinct ‘old person smell’ can develop with advancing age, however, this odour has not yet been sufficiently described in previous research. Sensory evaluation by a trained panel might be useful to describe alterations with age in body odour (BO). To evaluate the alterations and achieve first insights into the ‘old person smell’, this pilot study determined the odour profiles of BO samples from both a younger and an older age group with a trained panel. In addition, we aimed to assess whether the panellists can recognize the age group based on the smell of the BO samples. Eight younger (20–28 years) and eight older (80–83 years) participants sampled their BO by wearing a cotton T‐shirt for one night. The samples were sensorially evaluated by a trained panel, including ratings of total intensity and pleasantness. Additionally, an age labelling task was performed as a forced‐choice decision. Results revealed that the odour profiles of the BO samples were very similar for both age groups. Nevertheless, trained panellists were able to predict the age group with significantly higher accuracy (p = .042) than expected by chance (61% mean accuracy over all panellists). Furthermore, a linear support vector machine (SVM) classifier achieved an average accuracy of 69%. This finding indicates that the age of a person affects the BO, though it is not reflected in significantly distinct odour profiles.
Subject
General Chemistry,Food Science