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Microbial Odor Profile of Polyester and Cotton Clothes after a Fitness Session
Author(s) -
Chris Callewaert,
Evelyn De Maeseneire,
FrederiekMaarten Kerckhof,
Arne Verliefde,
Tom Van de Wiele,
Nico Boon
Publication year - 2014
Publication title -
applied and environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.552
H-Index - 324
eISSN - 1070-6291
pISSN - 0099-2240
DOI - 10.1128/aem.01422-14
Subject(s) - odor , polyester , clothing , textile , food science , bacteria , bacterial growth , wool , biology , pulp and paper industry , materials science , composite material , engineering , neuroscience , history , genetics , archaeology
Clothing textiles protect our human body against external factors. These textiles are not sterile and can harbor high bacterial counts as sweat and bacteria are transmitted from the skin. We investigated the microbial growth and odor development in cotton and synthetic clothing fabrics. T-shirts were collected from 26 healthy individuals after an intensive bicycle spinning session and incubated for 28 h before analysis. A trained odor panel determined significant differences between polyester versus cotton fabrics for the hedonic value, the intensity, and five qualitative odor characteristics. The polyester T-shirts smelled significantly less pleasant and more intense, compared to the cotton T-shirts. A dissimilar bacterial growth was found in cotton versus synthetic clothing textiles. Micrococci were isolated in almost all synthetic shirts and were detected almost solely on synthetic shirts by means of denaturing gradient gel electrophoresis fingerprinting. A selective enrichment of micrococci in an in vitro growth experiment confirmed the presence of these species on polyester. Staphylococci were abundant on both cotton and synthetic fabrics. Corynebacteria were not enriched on any textile type. This research found that the composition of clothing fibers promotes differential growth of textile microbes and, as such, determines possible malodor generation.

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