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智能装备与系统

便携式黄曲霉毒素B1检测系统设计与试验

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  • 1.江苏大学 农业工程学院,江苏 镇江 212000
    2.北京市农林科学院智能装备技术研究中心,北京 100097
王鹏飞,硕士研究生,研究方向为智慧农业与农业智能装备与技术。E-mail:18713450897@163.com
李爱学,研究员,研究方向为智慧农业与电化学传感器。E-mail:aixueli_2021@163.com

收稿日期: 2023-03-07

  网络出版日期: 2023-04-23

基金资助

北京市自然科学基金(2222007);国家自然科学基金(21974012)

Design and Test of Portable Aflatoxin B1 Detection System

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  • 1.College of Agricultural Engineering, Jiangsu University, Zhenjiang 212000, China
    2.Research Center of Intelligent Equipment, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
WANG Pengfei, E-mail:18713450897@163.com
LI Aixue, E-mail:aixueli_2021@163.com

Received date: 2023-03-07

  Online published: 2023-04-23

Supported by

Beijing Natural Science Foundation (2222007); National Natural Science Foundation of China (21974012)

摘要

为实现农副产品中黄曲霉毒素B1(AFB1)的现场快速检测,设计了一款基于差分脉冲伏安法(Differential pulse voltammetry,DPV)、以STM32F103ZET6为核心处理器的便携式检测系统。系统主要包括硬件检测设备和手机App两部分,二者通过Wi-Fi通信连接。硬件检测设备主要包括DPV波形生成电路、恒电位电路及微电流检测模块;上位机App在安卓环境下开发,主要完成信号采集、数据存储等任务。应用实验室自制的AFB1传感器,在0.1 fg/ml~100 pg/ml范围内系统可以对 AFB1实现有效检测。标准溶液中的测试结果与电化学工作站CHI760e相比,最大相对误差为7.37%。对加入不同浓度AFB1的花生油样品进行检测,以CHI760e检测结果为标准,回收率为96.8%~106%;对发霉程度不同的花生样品中进行测试,与CHI760e相比,最大相对误差为7.10%。本便携式检测系统在农副产品中AFB1的现场快速检测中具有广阔的应用前景。

本文引用格式

王鹏飞, 高原源, 李爱学 . 便携式黄曲霉毒素B1检测系统设计与试验[J]. 智慧农业, 2023 , 5(1) : 146 -154 . DOI: 10.12133/j.smartag.SA202303004

Abstract

To achieve rapid on-site detection of aflatoxin B1 (AFB1) in agricultural and sideline products, a portable detection system based on differential pulse voltammetry (DPV) and STM32F103ZET6 as the core processor was designed. The system consists of two main parts: hardware detection devices and a mobile App, which are connected through Wi-Fi communication. The hardware detection equipment includes a DPV waveform generation circuit, constant potential circuit, and micro current detection module. The upper computer App was developed in an Android environment and completed tasks such as signal acquisition and data storage. After completing the design, experiments were conducted to verify the accuracy of the constant potential circuit and micro current detection module. The constant potential circuit accurately applied the voltage set by the program to the electrode, with a maximum error of 4 mV. The micro current detection module converts the current into a voltage signal according to the theoretical formula and amplifies it according to the theoretical amplification factor. The laboratory-made AFB1 sensor was used to effectively detect AFB1 in the range of 0.1 fg/ml to 100 pg/ml. The maximum relative error between the test results in the standard solution and the electrochemical workstation CHI760e was 7.37%. Furthermore, peanut oil samples with different concentrations of AFB1 were tested, and the results were compared to the CHI760e detection results as the standard, with a recovery rate of 96.8%~106.0%. Peanut samples with different degrees of mold were also tested and compared with CHI760e, with a maximum relative error of 7.10%.The system's portability allows it to be easily transported to different locations for on-site testing, making it an ideal solution for testing in remote or rural areas where laboratory facilities may be limited. Furthermore, the use of a mobile App for data acquisition and storage makes it easy to track and manage testing results. In summary, this portable detection system has great potential for widespread application in the rapid on-site detection of AFB1 in agricultural and sideline products.

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