化学
荧光
氢
化学传感器
纳米技术
环境化学
有机化学
物理化学
物理
材料科学
电极
量子力学
作者
Xin Li,Kai Zhu,Bing Yan
标识
DOI:10.1021/acs.inorgchem.5c01956
摘要
As crucial biomarkers of food spoilage, portable and real-time monitoring of the biogenic amines (BAs) is essential to ensuring food safety. In light of this, a ratiometric fluorescent probe (Tb@HOF-BPTC) is developed, which exhibits distinct fluorescence response upon exposure to BAs. It demonstrates exceptional analytical performance with a low limit of detection ranging from 3.1 to 14.3 μM and remarkably rapid response times (<7.02 s). Notably, the differential responses of three BAs to the Tb@HOF-BPTC construct individualized "portrait" that enhance identification accuracy. Moreover, a machine learning-intelligent sensing platform is constructed by integrating back-propagation neural networks (BPNN) with smartphone-based RGB recognition. This platform utilizes a smartphone camera to capture fluorescence images, which are then processed by a BPNN model to classify the concentrations and the species of the BAs. Furthermore, for the purpose of overcoming the inconvenience of detecting BAs vapors in conventional fluorescence sensing, poly(vinyl alcohol) (PVA) hydrogel microneedles combined with Tb@HOF-BPTC are designed for real-time detection of BAs. Overall, our work shows the potential of real-time food freshness assessment by constructing an intelligent sensing platform based on PVA hydrogel microneedles.
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