Towards recycling of textiles: fast detection of contaminated waste fabric by near-infrared spectroscopy

Since the implementation of EU Waste Framework Directive, which mandates the separate collection of textile waste from 2025 onwards, there has been an increasing need for effective systems for textile waste collection, sorting, and recycling, together with reliable approaches to assess the chemical safety of textile products. The present study explores near-infrared (NIR) spectroscopy, combined with chemometric tools, proposed as a non-destructive rapid approach to identify the presence of contaminants on textile samples. Representative contaminants were applied to pre-consumer virgin polyester, virgin cotton and post-consumer polyester fabrics. This combined strategy succeeded in distinguishing contaminated textiles from uncontaminated ones, supported by statistical analysis with principal components (PCA), enhanced with feature selection by Minimum Redundancy Maximum Relevance (mRMR) and supervised classification using k-Nearest Neighbors (kNN). This NIR-based integrated method, implemented on a miniaturized NIR spectrometer (MicroNIR), is a promising solution to fast screen contaminated textile waste and produce safe secondary raw materials, reducing analysis time and costs of textile recycling workflows.

Authors

Institutions

Publication Details

Journal
Waste Management
Published
2026-08-14
DOI
https://doi.org/10.1016/j.wasman.2026.115777
Primary Topic
Microplastics and Plastic Pollution
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards recycling of textiles: fast detection of contaminated waste fabric by near-infrared spectroscopy

Andrea Fiorati, Luigi De Nardo, Arianna Rossetti, Roberto Casalini et al.
Waste Management
Microplastics and Plastic Pollution
article

Towards recycling of textiles: fast detection of contaminated waste fabric by near-infrared spectroscopy

Andrea Fiorati, Luigi De Nardo, Arianna Rossetti, Roberto Casalini, Chiara Cressoni, Giorgia Zanchin, C. Brugnoni
article en

Abstract

Since the implementation of EU Waste Framework Directive, which mandates the separate collection of textile waste from 2025 onwards, there has been an increasing need for effective systems for textile waste collection, sorting, and recycling, together with reliable approaches to assess the chemical safety of textile products. The present study explores near-infrared (NIR) spectroscopy, combined with chemometric tools, proposed as a non-destructive rapid approach to identify the presence of contaminants on textile samples. Representative contaminants were applied to pre-consumer virgin polyester, virgin cotton and post-consumer polyester fabrics. This combined strategy succeeded in distinguishing contaminated textiles from uncontaminated ones, supported by statistical analysis with principal components (PCA), enhanced with feature selection by Minimum Redundancy Maximum Relevance (mRMR) and supervised classification using k-Nearest Neighbors (kNN). This NIR-based integrated method, implemented on a miniaturized NIR spectrometer (MicroNIR), is a promising solution to fast screen contaminated textile waste and produce safe secondary raw materials, reducing analysis time and costs of textile recycling workflows.

Waste ManagementVol. 226
Ospedale di Circolo di Busto Arsizio (IT), Politecnico di Milano (IT)
Openalex Percentile: Top 19%
Microplastics and Plastic Pollution
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Towards recycling of textiles: fast detection of contaminated waste fabric by near-infrared spectroscopy — Andrea Fiorati, Luigi De Nardo, et al. · Waste Management (2026) | TGRS Research Map | TGRS