Electronics Department, National Institute of Astrophysics, Optics and Electronics, Sta. Ma. Tonantzintla, Puebla 72840, Mexico.
Computational Sciences Department, National Institute of Astrophysics, Optics and Electronics, Sta. Ma. Tonantzintla, Puebla 72840, Mexico.
Sensors (Basel). 2024 Sep 30;24(19):6348. doi: 10.3390/s24196348.
Effective pest population monitoring is crucial in precision agriculture, which integrates various technologies and data analysis techniques for enhanced decision-making. This study introduces a novel approach for monitoring lures in traps targeting the Mediterranean fruit fly, utilizing air quality sensors to detect total volatile organic compounds (TVOC) and equivalent carbon dioxide (eCO). Our results indicate that air quality sensors, specifically the SGP30 and ENS160 models, can reliably detect the presence of lures, reducing the need for frequent physical trap inspections and associated maintenance costs. The ENS160 sensor demonstrated superior performance, with stable detection capabilities at a predefined distance from the lure, suggesting its potential for integration into smart trap designs. This is the first study to apply TVOC and eCO sensors in this context, paving the way for more efficient and cost-effective pest monitoring solutions in smart agriculture environments.
有效的害虫种群监测在精准农业中至关重要，精准农业整合了各种技术和数据分析技术，以增强决策能力。本研究介绍了一种针对地中海实蝇诱捕器的新型监测方法，利用空气质量传感器来检测总挥发性有机化合物（TVOC）和等效二氧化碳（eCO）。我们的研究结果表明，空气质量传感器，特别是 SGP30 和 ENS160 型号，可以可靠地检测到诱捕器的存在，减少了频繁进行物理诱捕器检查和相关维护成本的需求。ENS160 传感器表现出卓越的性能，在预定义的距离内对诱捕器具有稳定的检测能力，这表明它有可能集成到智能诱捕器设计中。这是首次在该领域应用 TVOC 和 eCO 传感器的研究，为智能农业环境中更高效、更具成本效益的害虫监测解决方案铺平了道路。
