Non-destructive food authentication by vapor-assisted desorption chemical ionization mass spectrometry paired with machine learning.

ABSTRACT: The in-situ, rapid and non-destructive identification of complex food samples is a long-standing core technical challenge in food chemistry. Herein, vapor assisted desorption chemical ionization mass spectrometry (VADCI-MS) device was independently constructed, which facilitates rapid and non-destructive analysis of complex foods with diverse morphologies. Additionally, an integrated strategy that combines MS fingerprinting, feature selection, and machine learning classification models was established and is particularly effective for complex foods that are challenging to differentiate using conventional methods. As a paradigm, VADCI-MS was employed to rapidly (<1.0 min/sample) and non-destructively obtain the MS fingerprints of 101 batches of Zanthoxylum bungeanum (ZB) samples and 415 fea

SUBMITTER: Wang Y 

PROVIDER: S-EPMC12722350 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature