article·2014-07-24

Axillary odour build-up in knit fabrics following multiple use cycles

Rachel H. McQueen, James J. Harynuk, Wendy V. Wismer, M. Keelan, Yin Xu, A. Paulina de la Mata

Publisher page

Abstract

Purpose – Fibre content can influence the intensity of odour that develops within clothing fabrics. However, little is known about how effective laundering is at removing malodours in clothing which differ by fibre type. The purpose of this paper is to investigate whether a selected cotton fabric differed in odour intensity following multiple wear and wash cycles compared to a polyester fabric. Design/methodology/approach – Eight (male and female) participants wore bisymmetrical cotton/polyester t-shirts during 20 exercise sessions over a ten-week trial period. Odour was evaluated via a sensory panel, bacterial populations were counted and selected odorous volatile organic compounds were measured with comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry detection. Analysis occurred both before and after the final (20th) wash cycle. Findings – Findings showed that laundering was effective in reducing overall odour intensity ( p 0.001) and bacterial populations ( p 0.001) in both cotton and polyester fabrics. Odour was most intense on polyester fabrics following wear, not just before, but also after washing ( p 0.001); although, no differences in bacterial counts were found between fibre types ( p >0.05). Chemical analysis found C4-C8 chained carboxylic acids on both types of unwashed fabrics, although they were more prevalent on polyester. Originality/value – The findings suggest that the build-up of odour in polyester fabrics may be cumulative as important odorants such as the carboxylic acids were not as effectively removed from polyester compared to cotton.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Textile materials and evaluations · Olfactory and Sensory Function Studies · Color perception and design

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References

Reference metadata was not supplied for this record.