基于人工神经网络的田水中的兽医药物检测传感器的设计和预测建模
Junshi Huang1, Bolin Huang1, Shuanggen Huang1
1Key Laboratory of Modern Agricultural Equipment of Jiangxi, Jiangxi Agricultural University, Nanchang, 330045, China.
Scientific reports
|February 13, 2026
概括
一个新的传感器系统能够快速实时检测田水中的兽药残留物. 这项技术精确监测硫甲,奥洛素,多西环素化物和四环素化物,这对农业安全至关重要.
科学领域:
- 农业科学 农业科学
- 分析化学 分析化学
- 传感器技术 传感器技术
背景情况:
- 田水中的兽药残留物对生态系统和人类健康构成风险.
- 目前的检测方法通常很慢,不适合实时监控.
- 有效的监测对于确保食品安全和环境保护至关重要.
研究的目的:
- 开发一种新型传感器系统,快速实时检测在田水中的特定兽药残留物.
- 建立一个准确的预测模型来量化兽药度.
- 为了能够有效地监测农业水系统中关键的兽药.
主要方法:
- 开发一个使用互数字电极和STM32F405RGT6微控制器的传感器系统.
- 集成多个硬件模块用于信号生成,检测,处理和无线通信 (LoRa/4G).
- 竞争性适应性重权取样 (CARS) 的应用用于特征选择和人工神经网络建模用于度预测.
主要成果:
- 传感器系统成功获取了广泛频谱 (200 Hz 100 MHz) 的测量数据 (振幅比,相差).
- 作为模型输入的相差数据产生了优异的预测性能,R2值从0.7831到0.8713和RMSEP从22.0759到28.1526 mg/L.
- 该系统在水样中有效检测到了硫甲,奥洛素,多西环素化物和四环素化物.
结论:
- 开发的传感器系统为快速实时监测田水中的兽药残留物提供了可行的解决方案.
- 该系统的准确性和效率支持其在农业水质管理中的应用.
- 这项技术有助于加强农业食品安全和环境监测.
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