Convolution Neural Network-Assisted Smart Fluorescent-Tongue Based on Lanthanide Ion-Induced Forming MOF/HOF Composite for Differentiation of Flavor Compounds and Wine Identification.

Abstract

Wine flavor is a vital quality characteristic in wine, influenced by those flavor components with low sensory thresholds. It is crucial to recognize and classify the wine components related to their flavor contribution. The integration of fluorescent sensors and artificial intelligence shows huge potential in flavor recognition by emulation of the gustatory perception system. Meanwhile, achieving information identification of wine based on multiple information barcodes has hopeful applications in anticounterfeiting. In this study, we present a simple method in which organic linkers are weaved into a hydrogen-bonded organic framework (HOF) for the available transformation of a metal-bonded organic framework (MOF) induced by lanthanide ions (Ln3+). The fluorescent Ln-MOF/HOF composite exhibits high sensitivity, rapid response, and good recyclability for detecting seven flavor compounds in wine, including tannic acid, ionone, vanillin, anethole, anisaldehyde, hydroxybenzaldehyde, and 4-hydroxy-2-methylacetophenone. Depending on its satisfactory detectability, a novel strategy is provided in which a fluorescent sensor is able to function as a smart fluorescent-tongue (F-tongue) by the aid of convolutional neural network to differentiate these seven flavor compounds. In addition, the Ln-MOF/HOF composite has been used to prepare multiple information barcodes for wine information identification on the basis of dynamic fluorescence response toward tannic acid. The mimetic gustatory perception system developed in this study may offer a promising strategy for flavor recognition in food and further food anticounterfeiting.