ABSTRACT
Food fraud caused by the violation of glyphosate use in tea is frequently exposed, posing a potential health risk to consumers and undermining trust in food safety. In the work, an ionic fluorescent probe "[P66614] [4HQCA]-Cu2+ (PHQCA-Cu2+)" was constructed using Cu2+ and ionic liquids coordination through a competitive coordination strategy to detect glyphosate. This probe exhibited a prominent "turn-on" fluorescence response in glyphosate detection. PHQCA-Cu2+was destroyed by glyphosate with its strong coordination capability, and a new complex re-formed simultaneously between glyphosate and the Cu2+ in it, where Cu2+ served as an "invisible indicator" influencing fluorescence changes. Remarkably, PHQCA-Cu2+formed rapidly within 5 s, demonstrated exceptional sensitivity and selectivity, and satisfactory detection performance on paper strips impregnated withPHQCA-Cu2+.Importantly,PHQCA-Cu2+showed excellent recoveries in various green tea, which offered a viable method for identifying contaminated products from the supply chain quickly to enhance overall food safety surveillance.
Subject(s)
Fluorescent Dyes , Glyphosate , Tea , Fluorescence , Ions , Spectrometry, Fluorescence , CopperABSTRACT
A novel dual-channel sensor array based on the "off" and "off-on" phenomenon of ZnCdSe quantum dots (QDs) - KMnO4 system was established for the effective distinguish of 30 green teas with various species, grades and origins. Starting from optimization of QDs for the construction of the sensing system, their sensitivity and selectivity performances towards 10 representative green teas were tested first and the sensor systems based on ZnCdSe QDs were finally established. An obvious "off" response brought by the interactions between amino acids, quercetin, et al. and ZnCdSe QDs was obtained while an "off-on" phenomenon brought by the interactions between catechins and the ZnCdSe-KMnO4 system had also been verified. Furthermore, based on the differential fluorescence "off-on" response of seven catechins, the qualitative and quantitative analyses of these catechins were successfully carried out with the linear range from 0.5 to 10 µg/mL. Most importantly, through adopting the dual-channel sensor, 30 green teas with different species, origins and grades can be accurately identified with the LDA model according to the spectral signals and the recognition accuracy could achieve 100 %.