Advanced Microwave Sensing: Cylinder-Shaped Resonator-Integrated Transmission Line Based Sensor for Mustard oil Quality Estimation
Issued Date
2025-01-01
Resource Type
ISSN
1530437X
eISSN
15581748
Scopus ID
2-s2.0-105018683247
Journal Title
IEEE Sensors Journal
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SCOPUS
Bibliographic Citation
IEEE Sensors Journal (2025)
Suggested Citation
Uddin M.K., Alam T., Islam M.T., Kirawanich P., Baharuddin M.H. Advanced Microwave Sensing: Cylinder-Shaped Resonator-Integrated Transmission Line Based Sensor for Mustard oil Quality Estimation. IEEE Sensors Journal (2025). doi:10.1109/JSEN.2025.3611271 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/112715
Title
Advanced Microwave Sensing: Cylinder-Shaped Resonator-Integrated Transmission Line Based Sensor for Mustard oil Quality Estimation
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Abstract
The quality assessment of edible oils, particularly mustard oil, is a critical aspect of food safety and consumer health. This article presents a design and investigation of a Cylindrical Resonator-Integrated Transmission Line (CRITL) sensor for rapid and precise quality assessment of mustard oil. The proposed CRITL offers a notable advantage over the traditional sensors, responding to the small variations in the quality of mustard oil. The proposed CRITL design achieves exceptional resonance at 2.047 GHz with an S<inf>21</inf> of –78.5 dB. The sensing characteristics of the proposed CRITL are investigated for different mustard oil samples, which achieve an outstanding sensitivity of 40.41, a high Q-factor of 950, and an elevated Figure of Merit (FoM) of 52,002.9. Comprehensive full-wave simulations and experimental validation confirm its ability to detect subtle dielectric variations, where the CRITL sensor demonstrated significant linear variations in transmitted signals ranging from 2.17 GHz to 1 GHz across all oil samples. Results demonstrate that the sensor represents a non-invasive, fast, and highly sensitive means of quality detection for mustard oil, exceeding precision and detection ability compared to conventional methods. The key novelty of this work lies in its advancement of sensing technology through the development of a non-invasive, highly sensitive, and real-time monitoring approach, highlighting its strong potential for industrial food safety applications.