M2.3.4 - 3D-Printed µ-GC Integrated with an E-Nose System for Enhanced Plant Health Prediction
- Event
- EUROSENSORS XXXVII
2025-09-07 - 2025-09-10
Wroclaw - Band
- Lectures
- Chapter
- M2.3 - 3D Printed Microfluidics
- Author(s)
- U. Yaqoob, D. Limbani, S. Esfahani, M. Cole, J. W. Gardner - University of Warwick, Coventry (United Kingdom)
- Pages
- 80 - 81
- DOI
- 10.5162/EUROSENSORS2025/M2.3.4
- ISBN
- 978-3-910600-07-2
- Price
- free
Abstract
This work integrates a low-cost 3D-printed µ-GC with an e-nose system for improved plant health prediction. Metal oxide sensors are placed before and after the µ-GC column and show that ethanol elutes first, followed by trans-2-hexenal with a 1 s and linalool with a 2.5 s delays; demonstrating the column’s ability to separate out these pest plant biomarkers. Features are extracted from the sensor time-dependent responses and analysed using partial least squares (PLS) method. They accurately predict the VOC type and concentration. This simple e-nose system may offer a cost-effective solution for real-time plant health monitoring with enhanced prediction capabilities of harmful pests.