机器学习增强的电化学传感平台,用于在食品样本中同时检测多种抗生素
Ting Zhang1, Yuan Sun1, Xin Zhang1
1Center of Pharmaceutical Engineering and Technology, Harbin University of Commerce, Harbin 150076, China.
Food chemistry
|December 17, 2025
概括
一个新的人工神经网络 (ANN) 增强的电化学传感器可以检测食品中的多种抗生素残留物. 这种先进的传感器提供了高灵敏度和准确性,以改善食品安全监测.
科学领域:
- 分析化学 分析化学
- 材料科学 材料科学 材料科学
- 生物技术是生物技术.
背景情况:
- 食品中的抗生素残留物对公众健康构成重大风险.
- 准确而敏感的检测方法对于食品安全至关重要.
研究的目的:
- 开发一种新型的人工神经网络 (ANN) 增强的电化学传感器,用于同时检测氨基醇 (CAP),化 (NFZ) 和化 (MNZ).
- 通过机器学习评估传感器在复杂的食品矩阵中的性能,并提高检测准确度.
主要方法:
- 一个ZIF-8/MnMoO4/MWCNTs修改的玻璃碳电极 (GCE) 的制造.
- 抗生素残留物的电化学检测.
- 使用反向传播人工神经网络 (BP-ANN) 的优化和信号解释.
主要成果:
- 传感器表现出高灵敏度,对CAP,NFZ和MNZ的超低检测极限.
- 在牛奶和蜂蜜样本中观察到出色的选择性和微不足道的干扰 (90.0%-110.0%的恢复率,RSD<4.07%).
- 该BP-ANN实现了超过93%的预测准确性,显著减少回归误差.
结论:
- 开发的智能电化学传感器在分析真实食品样本方面表现出强大的性能.
- 这种传感器平台具有很大的潜力,可以在食品安全监测中进行实用的多残留抗生素检测.
相关概念视频
Microbial Biosensors
91
Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...
91
Automated Microbial Diagnostics
83
Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...
83


