What question did this study set out to answer?

This research aims to develop and assess SMR sensors for identifying plant-emitted VOCs associated with pest detection.

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March 10, 2026Open Access

Single and Dual Mode SMR Sensors for Pest Detection in Plant Health Monitoring

Key Points

This research aims to develop and assess SMR sensors for identifying plant-emitted VOCs associated with pest detection.
Developed surface functionalized SMR sensors at the University of Warwick and utilized commercial sensors.
Tested sensors with specific VOCs (linalool, trans-2-hexenal, D-limonene) at various concentrations.
Conducted assessments under different humidity conditions (30% RH ±3%).
Established a Python-based signal-processing workflow to analyze sensor data.
Successfully detected specific VOCs linked to pest activity.
Demonstrated effective frequency response filtering and feature extraction.
Identified key metrics such as baseline and saturation points.

Abstract

This study presents the development and evaluation of surface functionalized solidly mounted resonators (SMRs), including custom developed at the University of Warwick (UWAR) devices and commercial Sorex sensors, for the detection and classification of plant-emitted volatile organic compounds (VOCs). The sensors were tested against linalool, trans-2-hexenal (T2H), and D-limonene at different concentrations under both dry and humid conditions (30% ±3% RH). A Python-based (v3.13.5) signal-processing workflow was established to filter frequency responses and extract key features, such as baseline, saturation point, and frequency shift (

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