Recently, the Chinese Food Processing and Equipment Innovation Team, Institute of Food Science and Technology (IFST), Chinese Academy of Agricultural Sciences (CAAS) investigated the synchronous fluorescence detection of nitrite in meat products based ondual-emitting dye@MOF and its portable hydrogel test kit. This research was published in the top journal "Journal of Hazardous Materials" (JCR Q1, IF=13.6).

Nitrite (NO₂^–) is a common nitrogen-containing compound in nature and serves as a crucial indicator for monitoring inflammation, food, and water safety. Nitrite is widely employed as a preservative and color fixative in the processing and production of meat products. However, excessive intake of nitrite can pose severe risks to human health, leading to certain chronic diseases and cancer. Therefore, the development of a rapid test kit for nitrite content in food holds significant importance.

In this study, a novel ratiometric fluorescence nanosensor (Rh6G@UIO-66-NH₂) was prepared and utilized in a synchronous fluorescence method for efficient detection of NO₂^– in food. Using commonly available meat products as the testing targets, the interaction between NO₂^– in the samples and the amino groups on the surface of Rh6G@UIO-66-NH₂ resulted in the formation of diazonium salts, causing quenching of the blue fluorescence and reflecting the concentration of NO₂^– in the samples. Experimental results demonstrated a good linear relationship between the added NO₂^– concentration and the fluorescence intensity ratio (I_Rh6G/I_MOF) of Rh6G@UIO-66-NH₂ within the range of 1-100 μM, with a low detection limit of 0.021 μM. The nanosensor exhibited ideal recovery rates in the analysis and detection of NO₂^– concentrations in real meat products, showcasing substantial potential for practical application. Additionally, a portable NO₂^– hydrogel test kit (Gel/Rh6G@UIO-66-NH₂) was constructed for on-site dual-mode detection of NO₂^– in samples. The test kit, combined with a smartphone, enabled simultaneous dual-mode (daylight and ultraviolet light) colorimetric analysis and fluorescence detection of the samples. Using ImageJ software, the smartphone-captured NO₂^– concentration results from the test kit could be converted into numerical information, allowing for visual fluorescence detection within a certain concentration range (0.1-1.5 mM) and further quantitative analysis. This study presents a rapid and efficient method for detecting NO₂^– concentrations in meat products, expanding the prospects for real-time monitoring in the field of food safety assessment. The aim is to provide forward-looking technological support for on-site detection of nitrite in food safety and environmental issues.

Professor Chunhui Zhang from Institute of Food Science and Technology (IFST), Chinese Academy of Agricultural Sciences (CAAS), and Senior Engineer Huan Liu from Beijing Academy of Agriculture and Forestry Sciences, are the co-corresponding authors. The first author is Siyang Deng, a jointly trained Ph.D. student from GSCAAS-ULg Program. The study received support from the National Key Research and Development Program (2021YFD2100103) and the Beijing Science and Technology Plan Project (Approval Number: Z221100007122010).

Link to the paper：https://doi.org/10.1016/j.jhazmat.2023.132898

                                               

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