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Chemometric tools to highlight NIAS in PET

AI-generated Abstract

Food packaging materials, particularly PET, can interact with food, raising concerns about non-intentionally added substances (NIAS) and food safety. This study aimed to analyze NIAS during the production of PET bottles using GC-MS fingerprints and chemometric tools. By comparing pellets, preforms, and bottles from the same batch, significant distinctions were made, revealing key volatile and less volatile compounds responsible for the separation of these materials. The findings demonstrated the effectiveness of combining GC-MS data with chemometrics in identifying and assessing NIAS, thus enhancing food safety evaluations.