The increasing consumption of textiles leads to an increase of textile fiber production whereby high amounts of natural resources are consumed and hazardous substances released into the environment. Therefore, the recycling of textiles is imperative to reduce the environmental impact. Sensor-based sorting of post-consumer textiles can play an important role in achieving efficient recycling. The aim of this work is to investigate the identification of textile fibers using near infrared (NIR) spectrometry and to describe its potential and barriers. In addition, a database of textile spectra is created on the NIR sorting machine. Previous research studies and EU projects are presented, and their results described. Furthermore, post-consumer textiles were collected, and their material composition studied based on their NIR spectra. The results reveal characteristic spectral regions for pure materials (cotton, polyester, polyacrylic, viscose, silk, linen and wool), which make a distinction possible. Only the spectra of cotton and linen are too similar in order to be distinguished. The evaluation of the blended materials cotton/polyester, cotton/viscose, cotton/polyacrylic and polyester/viscose showed a differentiation if the distance between the composition ratio and pure material is higher than 10¿40 %. Lower contents of a second fiber component could not be identified. This was also shown in the evaluation of blended materials with an elastane content up to 8 %. In general, it can be said that the implementation of NIR spectrometry for post-consumer textile sorting represents a potential due to its advantages over other methods and can contribute to an improvement in the recycling of post-consumer textiles.