Ultrafast Ratiometric Fluorescent Probe and Deep Learning-Assisted On-Site Detection Platform for BAs and Meat Freshness Based on Molecular Engineering.
Journal:
ACS sensors
Published Date:
Apr 25, 2025
Abstract
As metabolic byproducts and representative indicators of food spoilage, the monitoring and detection for biogenic amines (BAs) are crucial but challenging for food quality assessment. Here, a strategy is proposed by combining fluorescent probe molecular engineering with a portable detection platform integrating a smartphone and a deep convolutional neural network (DCNN). Four ratiometric fluorescent probes with tunable intramolecular charge transfer (ICT) properties are designed by introducing different electron-withdrawing substituents (-F, -OCH, -Py, and -CN) to the carbazole. Notably, CNCz exhibits the strongest ICT property and superior sensing performance, with a satisfying detection limit (11 ppb), rapid response (<5 s), and discriminative bathochromic shift (110 nm). Then, a smartphone-based detection platform is fabricated, which enables rapid, visual, and on-site quantitative evaluation of BAs. Furthermore, by integrating DCNN, this platform achieves an impressive 98.5% accuracy in predicting meat freshness. Hereby, this study not only provides a molecular engineering strategy to fine-tune the intrinsic ICT properties to gain high-performance ratiometric fluorescent probes but also presents an intelligent detection platform for BAs and meat freshness with high practical applicability.