Detection technologies and sensing systems for crop pest identification and infestation severity prediction: a review

With the rapid development of precision agriculture technology, agricultural production is gradually shifting from traditional experience-based practices to data-driven decision-making. Pest species identification and scale prediction are crucial technologies in the field of pest detection. Compared with traditional pest monitoring methods, detection based on organic volatile gases released by crops under pest stress provides superior temporal and spatial resolution. The use of gas sensors in crop pest monitoring has great potential for application in future agricultural production. Infrared absorption spectroscopy-based gas sensors have gained widespread attention in crop pest monitoring due to their superior detection sensitivity and extensive scalability. A comprehensive overview of recent advances in intelligent detection methods and equipment for crop pest monitoring is provided. Emphasis is placed on the architecture, operating principles, sensing mechanisms, and fabrication materials of trace gas sensors based on infrared absorption spectroscopy for agricultural pest monitoring. In addition, key technologies involved in their fabrication processes are outlined. Finally, based on the specific characteristics of these sensors, the paper discusses in detail the application strategies of infrared absorption spectroscopy trace gas sensors in crop pest and disease monitoring, including transmission network design, platform integration, and the technical bottlenecks encountered in practical applications. The research will provide scientific foundations and innovative ideas for the development of future crop pest monitoring technologies, addressing the challenges faced by precision agriculture today.

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Publication Details

Journal
Frontiers in Plant Science
Published
2026-02-27
DOI
https://doi.org/10.3389/fpls.2026.1765363
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Detection technologies and sensing systems for crop pest identification and infestation severity prediction: a review

Fu Zhang, Yafei Wang, Jingmin Dang, Changji Wang
Frontiers in Plant Science
Smart Agriculture and AI
article

Detection technologies and sensing systems for crop pest identification and infestation severity prediction: a review

Fu Zhang, Yafei Wang, Jingmin Dang, Changji Wang
article en

Abstract

With the rapid development of precision agriculture technology, agricultural production is gradually shifting from traditional experience-based practices to data-driven decision-making. Pest species identification and scale prediction are crucial technologies in the field of pest detection. Compared with traditional pest monitoring methods, detection based on organic volatile gases released by crops under pest stress provides superior temporal and spatial resolution. The use of gas sensors in crop pest monitoring has great potential for application in future agricultural production. Infrared absorption spectroscopy-based gas sensors have gained widespread attention in crop pest monitoring due to their superior detection sensitivity and extensive scalability. A comprehensive overview of recent advances in intelligent detection methods and equipment for crop pest monitoring is provided. Emphasis is placed on the architecture, operating principles, sensing mechanisms, and fabrication materials of trace gas sensors based on infrared absorption spectroscopy for agricultural pest monitoring. In addition, key technologies involved in their fabrication processes are outlined. Finally, based on the specific characteristics of these sensors, the paper discusses in detail the application strategies of infrared absorption spectroscopy trace gas sensors in crop pest and disease monitoring, including transmission network design, platform integration, and the technical bottlenecks encountered in practical applications. The research will provide scientific foundations and innovative ideas for the development of future crop pest monitoring technologies, addressing the challenges faced by precision agriculture today.

Frontiers in Plant ScienceVol. 17
Jiangsu University (CN), Henan University of Science and Technology (CN), Jilin University (CN), Henan University of Technology (CN), Jilin Agricultural University (CN)
Zero hunger
Openalex Percentile: Top 42%
Smart Agriculture and AI
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