π-Conjugated Supramolecular Self-Assembled Fluorescent Sensor Array for Biogenic Amines: A Machine Learning Approach

π-Conjugated supramolecular self-assembled fluorescence sensor arrays have been developed for the detection and discrimination of biogenic amines in food samples utilizing machine learning-assisted statistical algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and hierarchical cluster analysis (HCA). The developed sensor array system is applied to the real-time and on-site detection of biogenic amines in food samples. Binary and ternary mixture analyses were successfully achieved.