Kong Cheng, Sun Lin, Li Xiaodan, Yan Yu, Chang Zhiyong, Li Mo, Gou Fuyan, Rong Baojun
College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China.
Beijing Institute of Geohazard Prevention and Control, Beijing 100011, China.
Sensors (Basel). 2025 Jan 10;25(2):380. doi: 10.3390/s25020380.
The rapid detection of petroleum hydrocarbons and organic pesticides is an important prerequisite for precise soil management. It is also a guarantee for soil quality, environmental safety, and human health. However, the current rapid detection methods are prone to sample matrix interference, complex development processes, short lifespan, and low detection accuracy. Moreover, they face difficulties in achieving simultaneous detection of petroleum hydrocarbons and organic pesticides. In this paper, we developed an electronic nose system for the simultaneous detection of petroleum hydrocarbons and organic pesticides in soil based on gas technology, which includes a sampling module and recognition model. The developed sampling module can simultaneously acquire the odor signals of petroleum hydrocarbons and organic pesticides in soil. The established recognition model can quickly distinguish between healthy soil, soil contaminated by petroleum hydrocarbons, and soil contaminated by organic pesticides. It can also achieve specific recognition of pesticide types and petroleum types. The performance of the developed electronic nose system was verified for real soil, petroleum products, and organic pesticides. The experiment shows that the developed electronic nose system has an accuracy of 100% for three tasks: soil conditions identification, pesticide types identification, and petroleum types identification.
快速检测石油烃和有机农药是精准土壤管理的重要前提。它也是土壤质量、环境安全和人类健康的保障。然而，当前的快速检测方法容易受到样品基质干扰、开发过程复杂、使用寿命短以及检测精度低的影响。此外，它们在实现石油烃和有机农药的同时检测方面面临困难。在本文中，我们基于气体技术开发了一种用于同时检测土壤中石油烃和有机农药的电子鼻系统，该系统包括采样模块和识别模型。所开发的采样模块可以同时采集土壤中石油烃和有机农药的气味信号。所建立的识别模型可以快速区分健康土壤、受石油烃污染的土壤和受有机农药污染的土壤。它还可以实现对农药类型和石油类型的特异性识别。所开发的电子鼻系统的性能在真实土壤、石油产品和有机农药上得到了验证。实验表明，所开发的电子鼻系统在土壤状况识别、农药类型识别和石油类型识别这三项任务上的准确率均为100%。
