A peak comparison index approach for robust microplastic analysis across environmental matrices: validation using meat products

Microplastic contamination in food products raises significant concerns regarding human health and environmental safety, necessitating accurate detection methodologies for complex organic matrices. This study presents an effective framework for microplastic detection in meat by systematically evaluating four chemical digestion methods: hydrogen peroxide (H₂O₂), hydrochloric acid (HCl), sodium hydroxide (NaOH), and Fenton's reagent. Among these, HCl and NaOH demonstrated the highest organic matter removal efficiencies while preserving polymer integrity across polyethylene (PE), polystyrene (PS), and polyvinyl chloride (PVC) samples. A novel peak comparison index (PCI) quantitatively assesses spectral alterations, identifying NaOH as the least disruptive digestion method. Furthermore, the systematic comparison of digestion-induced polymer modifications enhances the standardization of microplastic analysis, facilitating methodological harmonization across food systems and broader environmental matrices. These findings establish a robust analytical approach for improving microplastic detection accuracy, strengthening risk assessments, and supporting contamination mitigation strategies within food supply chains.