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Abstract Reusing and recycling End-Of-Life (EoL) textiles is a successful approach to develop sustainable and circular strategies in the apparel industry. Textile reuse and recycling can help to reduce the environmental impact of the fashion and textile industry by preserving natural resources and reducing waste. Textile fibers recognition and sorting, according to material composition, are of primary importance for the implementation of efficient and sustainable recycling strategies. In this work, Short-Wave InfraRed (SWIR: 1000–2500 nm) spectroscopy was applied to extract information regarding the fabric composition of different EoL textiles in order to set up a hierarchical classification procedure able to recognize different type of textile. In more detail, Partial Least Squares-Discriminant Analysis (PLS-DA) pattern recognition technique was used and classifications were performed in two steps: (1) recognition of the fiber origin i.e. plant-derived, animal-derived, artificial textiles such as synthetic and/or Man-Made Cellulosic Fibers (MMCFs) and, (2) discrimination of fabrics according to the material classes (i.e. silk, cotton, wool, viscose, linen, jute, polyester and blends). The proposed chemometric technique successfully classified textiles based on their spectral properties. The acquired results are highly promising and provide important insight into the EoL textile recycling business. These analytical techniques have the potential to be utilized to successfully automate the recycling process, either in addition to or as a replacement for manual processes, hence improving sorting procedures. Graphical Abstract
Bonifazi et al. (Thu,) studied this question.