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◆ Journal of Food Composition and Analysis2026-01-31· Livestock

Micro-nanoplastics in livestock and poultry: Emerging components of food matrices

Angela Patricia Abad-López, Omar Solano-Trillos, Carlos David Grande-Tovar

原始摘要(英文原文)· Original abstract
The ubiquitous presence of micro- and nanoplastics (MNPs) in ecosystems has raised increasing concern regarding their transfer through food webs and their occurrence in food animals, particularly cattle and poultry, the most widely consumed animal protein sources worldwide. As emerging, quantifiable components of food matrices, MNPs pose potential risks to food safety and require robust analytical approaches for reliable detection, identification, and quantification in edible tissues. This review compiles and critically evaluates available evidence on the occurrence of MNPs in livestock and poultry meat (n=146, from 2015 to 2025), with particular emphasis on analytical methodologies, reporting units, and compositional relevance. The environmental pathways of MNPs, from sources and animal exposure to tissue translocation, bioaccumulation, and excretion, are synthesized alongside the analytical workflows used to assess their presence. Overall, the available evidence indicates that MNPs bioaccumulation in livestock can reduce growth performance, alter meat quality attributes, and impair reproductive function, with potential implications for human exposure. By integrating compositional evidence and critically assessing analytical performance across studies, this review frames MNPs as emerging constituents of poultry and livestock-derived foods and highlights the need for standardized, validated methodologies to enhance data comparability, enable exposure assessment, and support future monitoring and guideline development. • Micro-nanoplastics (MNPs) are emerging food components detected in meat samples. • MNPs can modify meat composition, affecting texture and sensory-related properties. • MNPs loads can be underestimated due to the limited size sensitivity of the method. • Py-GC/MS enables accurate identification of polymer types in edible tissues. • MNPs detection methods in edible tissues require standardization for comparability.
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