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

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 <i>Sorex</i> 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 (Δf). Adsorption behaviour was modelled using the Freundlich isotherm, showing good agreement with experimental data and suggesting heterogeneous, multilayer adsorption on CH<sub>3</sub>-terminated EC surfaces. A 2D polar classification framework combining vector-normalized Δf values from <i>UWAR</i> and <i>Sorex</i> sensors enabled a clear separation of the VOCs. The results highlight the complementary performance of the two types of SMR sensors and demonstrate that feature-engineered resonant devices, combined with computational classification, offer strong potential for future use in plant health monitoring systems.

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Journal
Sensors
Published
2026-03-08
DOI
https://doi.org/10.3390/s26051708
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
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article

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

Marina Cole, Barbara Urasińska-Wójcik, Usman Yaqoob, Siavash Esfahani et al.
Sensors
Advanced Chemical Sensor Technologies
article

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

Marina Cole, Barbara Urasińska-Wójcik, Usman Yaqoob, Siavash Esfahani, Julian W. Gardner
article en

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 <i>Sorex</i> 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 (Δf). Adsorption behaviour was modelled using the Freundlich isotherm, showing good agreement with experimental data and suggesting heterogeneous, multilayer adsorption on CH<sub>3</sub>-terminated EC surfaces. A 2D polar classification framework combining vector-normalized Δf values from <i>UWAR</i> and <i>Sorex</i> sensors enabled a clear separation of the VOCs. The results highlight the complementary performance of the two types of SMR sensors and demonstrate that feature-engineered resonant devices, combined with computational classification, offer strong potential for future use in plant health monitoring systems.

SensorsVol. 26(5)
Melbourn Science Park (GB), University of Warwick (GB)
Zero hunger
Openalex Percentile: Top 31%
Advanced Chemical Sensor Technologies
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Single and Dual Mode SMR Sensors for Pest Detection in Plant Health Monitoring — Marina Cole, Barbara Urasińska-Wójcik, et al. · Sensors (2026) | TGRS Research Map | TGRS