基于微球编码信号传导的机器学习驱动的光学免疫传感器,用于快速和多重检测牛奶中的抗生素
Cuiyun Zhou1, Chenxi Huang2, Hongyu Zhang3
1College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
Food chemistry
|October 23, 2023
概括
这项研究介绍了一种新的光学免疫传感器,用于快速同时检测食品中的多种抗生素残留物. 该传感器提供高精度和高效率,以确保公共卫生和食品安全.
科学领域:
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
- 生物传感器是一种生物传感器.
背景情况:
- 抗生素残留物是牛奶和乳制品中普遍存在的污染物,对公众健康构成风险.
- 同时,方便和稳定的检测方法对于监测食品中的这些污染物至关重要.
研究的目的:
- 开发一种光学免疫传感器,同时检测多种抗生素残留物.
- 提高食品矩阵中的抗生素残留分析的准确性,成本效益和简单性.
主要方法:
- 使用易于功能化的聚乙烯纳米粒子与多重信号探测器.
- 基于机器学习的综合转码分析用于数据解释.
- 采用单步信号转换反应进行检测.
主要成果:
- 在30分钟内实现了广泛的线性范围 (pg/mL到ng/mL) 内多重检测抗生素.
- 显示总体准确度超过99%.
- 在准确性,成本和程序简单性方面表现优于传统的化学发光免疫试验.
结论:
- 开发的光学免疫传感器适用于准确,同时量化牛奶中的多种抗生素.
- 这种技术为食品安全监测提供了显著的优势,特别是在检测多种危险物质时.
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