Abstract

Textiles are extremely important materials for everyday life with a broad range of applications and properties. Due to the large variations in quality on the one hand and the increasing quality awareness and price consciousness of customers on the other hand, the availability of a simple tool for a rapid test of the correct identity of the purchased textile article would be a significant progress in customer protection. Miniaturization of near infrared spectrometers has advanced to the point where handheld instruments could provide reliable and affordable means to serve this purpose. One objective of the present communication was to scrutinize the identification and discrimination performance for textile materials for four real-handheld (<200 g) near infrared spectrometers based on different monochromator principles. The second focus was to show that in the near future these handheld instruments can be used by a non-expert user community to protect themselves against fraud in textile purchase situations. For this purpose, diffuse reflection spectra of 72 textile samples of synthetic and natural origin were measured. While in simple situations, test samples can readily be authenticated by visual inspection of their near infrared spectra only, for a more comprehensive identification of unknown samples principal component analysis in combination with soft independent modeling of class analogies was applied. In the present work, this approach provided a suitable analytical tool for the correct assignment of the investigated different types of textile materials. Moreover, the evaluation of the mean Euclidian distances in the principal component analysis score plots derived from the near infrared spectra of the textile classes under investigation allowed to compare the identification performance and discrimination capability of the different handheld instruments.

© 2018 The Author(s)

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