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This review highlights how metagenomic tools can enhance Life Cycle Assessment for sustainable textile supply chains, addressing supply chain risks.
The textile sector provides essential goods, yet it remains environmentally and socially intensive, driven by high water use, pesticide dependent monocropping, chemical pollution during processing, and growing waste streams. This review examines credible pathways to sustainability by integrating emerging plant-based fibres from hemp, abaca, stinging nettle, and pineapple leaf fibre. These underutilised crops combine favourable agronomic profiles with competitive mechanical performance and are gaining momentum as the demand for demonstrably sustainable textiles increases. However, conventional fibre identification methods, including microscopy and spectroscopy, often lose reliability after wet processing and in blended fabrics, creating opportunities for mislabelling, greenwashing, and weak certification. We synthesise how advanced molecular approaches, including DNA fingerprinting, species-specific assays, and metagenomic tools, can support the authentication of fibre identity and provenance and enable linkage to Digital Product Passports. We also critically assess environmental Life Cycle Assessment (LCA) and social assessment frameworks, including S-LCA and SO-LCA, as complementary methodologies to quantify climate burden, water use, labour conditions, and supply chain risks. We argue that aligning fibre innovation with molecular traceability and harmonised life cycle evidence is essential to replace generic sustainability claims with verifiable metrics, strengthen policy and certification, and accelerate transparent, circular, and socially responsible textile value chains. Key research priorities include validated marker panels and reference libraries for non-cotton fibres, expanded region-specific LCA inventories and end-of-life scenarios, scalable fibre-to-fibre recycling routes, and practical operationalisation of SO-LCA across diverse enterprises.
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Sousa et al. (2026) studied this question.
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