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全面探索食品中柠檬黄的检测:荧光纳米材料和电化学传感器的应用:最新进展与未来趋势。

A comprehensive exploration of tartrazine detection in food products: Leveraging fluorescence nanomaterials and electrochemical sensors: Recent progress and future trends.

机构信息

Department of Quality Assurance, H. R. Patel Institute of Pharmaceutical Education and Research Shirpur, Dist. Dhule, Maharashtra 425 405, India.

Department of Pharmaceutical Chemistry, H. R. Patel Institute of Pharmaceutical Education and Research Shirpur, Dist. Dhule, Maharashtra 425 405, India.

出版信息

Food Chem. 2024 Feb 1;433:137425. doi: 10.1016/j.foodchem.2023.137425. Epub 2023 Sep 9.

DOI:10.1016/j.foodchem.2023.137425
PMID:37690141
Abstract

Azo dyes are widely used as food coloring agents because of their affordability and stability. Examples include brilliant blue, carmoisine, sunset yellow, allura red, and tartrazine (Tar), etc. Notably, Tar is often utilized in hazardous food goods. They are frequently flavoured and combined with food items, raising the likelihood and danger of exposure. Therefore, detecting Tar in food is crucial to prevent health risks. Fluorescence nanomaterials and electrochemical sensors, known for their high sensitivity, affordability, simplicity, and speed, have been widely adopted by researchers for Tar detection. This comprehensive paper delves into the detection of Tar in food products. It extensively covers the utilization of advanced carbon-based nanomaterials, including CDs, doped CDs, and functionalized CDs, for sensitive Tar detection. Additionally, the paper explores the application of electrochemical sensors. The paper concludes by addressing current challenges and prospects, emphasizing efforts to enhance sensitivity, and selectivity for improved food safety.

摘要

偶氮染料由于其价格低廉和稳定性而被广泛用作食品着色剂。例如亮蓝、胭脂红、日落黄、诱惑红和柠檬黄(Tar)等。值得注意的是,Tar 经常被用于危险食品中。它们经常与食品混合调味,增加了暴露的可能性和危险。因此,检测食品中的 Tar 对于预防健康风险至关重要。荧光纳米材料和电化学传感器以其高灵敏度、价格低廉、简单易用和快速响应而被研究人员广泛应用于 Tar 的检测。本文全面探讨了食品中 Tar 的检测。它广泛涵盖了先进的碳基纳米材料(包括 CDs、掺杂 CDs 和功能化 CDs)在灵敏 Tar 检测中的应用。此外,本文还探讨了电化学传感器的应用。最后,本文讨论了当前的挑战和前景,强调了提高灵敏度和选择性以改善食品安全的努力。

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