Last Month's Most Accessed Feature: Fabric sweat testing: Armpit excretions distinguish material and gender

Skip to Navigation

Monthly Highlight

  • Published: May 5, 2017
  • Categories: Base Peak
thumbnail image: Last Month's Most Accessed Feature: Fabric sweat testing: Armpit excretions distinguish material and gender

Fabric-sweat interactions

The sweat volatiles that escape from armpits onto clothing that were analysed by 2D-GC/MS can be used to distinguish between the types of fabric and whether they had been washed, while also revealing the gender of the subjects.

The full complement of chemicals that exist in body fluids has been examined extensively for blood, plasma, serum and urine while studies on the “less popular” fluids such as saliva, semen and sweat have been less forthcoming. Nevertheless, the volatile compounds emitted from sweat have had some attention, various reports showing that they can distinguish between individuals as well as pinpointing their gender. Other reports have described the sweat compounds and human body odour that is retained on textiles after being worn.

A new study has now been released that examines the sweat volatiles that are released from the armpits onto different types of fabric worn as T-shirts. Scientists from the University of Alberta, Edmonton, wanted to see if cotton and polyester could be classified from their absorbed sweat profiles, whether the fabrics had been washed or not.

It is already known that fabrics have distinct odour characteristics, generating and retaining a particular set of compounds, with the resident microbes playing some sort of role. However, the relationship between human odour and fabric type, which is an important aspect of the clothing industry, remains poorly understood. So, James Harynuk and colleagues undertook a metabolomics study to look at the odour characteristics of cotton and polyester, using a mass spectrometry method for profiling the odour compounds.

Sweat testing

Volunteers wore special bisymmetrical T-shirts made up of one half cotton and the other half polyester while they repeatedly exercised to produce axillary sweat. Previous work had revealed that cotton that had been pretreated with an antimicrobial agent showed no variations in odour profiles than untreated cotton, so the two types were treated the same.

After being worn, segments from the armpit area were cut into small pieces and the volatiles sampled by solid-phase microextraction with a triple-mode fibre to trap as many different classes of compounds as possible. These fibres were inserted into the port of a GC/MS system that was fitted with two GC columns in series for enhanced separation of the 2000 or so peaks that were detected.

The compounds were identified from mass spectral library searching and one-dimensional retention indices. However, even those peaks that were not identified were used in the data analysis as they are unique unknowns and retain value for classification purposes when comparing data sets.

The data sets were analysed by principal components analysis but two peak preselection procedures were used. The first was based on the commercial software that came with the GC/MS system that generated a Fisher ratio for each analyte which was used for selection. The second procedure was an in-house algorithm that exploited cluster resolution.

Cotton and polyester have discriminating sweat profiles

The first test attempted to use the odour profiles to distinguish between male and female subjects. With no preselection, the PCA plots could not discriminate between gender but this improved when the Fisher ratio procedure was brought into play. However, the best performance was undoubtedly obtained with the in-house algorithm which gave excellent gender separation. The compounds that were most effective in this distinction were alcohols and aldehydes, which correlated mostly with males, and aromatic compounds, which correlated with females.

The armpit volatile compounds could also distinguish between cotton and polyester but a different subset was responsible this time. Carboxylic esters and acids were correlated with cotton whereas aldehydes and alcohols were correlated with polyester. Once again, the best separation in the PCA plots was achieved with the custom algorithm.

It was also possible to distinguish between washed and unwashed fabrics using PCA, but separation using the preselection algorithm was not as clear as the previous comparisons. Washed versus unwashed cotton, washed versus unwashed polyester and washed cotton versus unwashed polyester could all be distinguished, although the compounds responsible could not be identified from the mass spectral library.

The findings will be of interest to the textile industry by designing greener materials that selectively retain odorous compounds or inhibit their generation in the first place, so that less frequent washing is necessary. In addition, the special algorithm used for data preselection operates better than the commercial software and could be extended into general data mining processes to find the most relevant compounds in a data set.

Related Links

Analytical and Bioanalytical Chemistry 2017, 409, 1905-1913: "Comprehensive two-dimensional gas chromatographic profiling and chemometric interpretation of the volatile profiles of sweat in knit fabrics"

Article by Steve Down

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

Follow us on Twitter!

Social Links

Share This Links

Bookmark and Share


Suppliers Selection
Societies Selection

Banner Ad

Click here to see
all job opportunities

Most Viewed

Copyright Information

Interested in separation science? Visit our sister site

Copyright © 2017 John Wiley & Sons, Inc. All Rights Reserved