Journal of Advanced Computational Intelligence and Intelligent Informatics
Online ISSN : 1883-8014
Print ISSN : 1343-0130
ISSN-L : 1883-8014
Regular Papers
Non-Invasive Plant Root Tomography Through Optimized Sonar Array Transducer Antenna Design Using Genetic Swarm Metaheuristic
Jonnel D. Alejandrino Ronnie S. Concepcion IIArgel A. BandalaEdwin SybingcoRyan Rhay P. VicerraElmer P. Dadios
Author information
JOURNAL OPEN ACCESS

2024 Volume 28 Issue 1 Pages 59-66

Details
Abstract

Plant root imaging is crucial for progress in various domains such as plant breeding and crop optimization. Traditionally, root tomography involves invasive methods that disrupt plant systems and yield non-reproducible results. As a result, non-invasive techniques, particularly electrical tomography, have gained significant attention. Despite the advantages, these techniques have limitations in terms of radiation efficiency and directivity due to suboptimal antenna design. This paper presents a comprehensive simulation on antenna design optimization focusing on dimensions, spacing, and integration of advanced algorithms. A micropatch transducer antenna was engineered for an existing in-silico plant root setup operating within a 3–5 MHz frequency range. The optimized dimensions of the antenna are 109.32 mm × 140.67 mm × 2.55 mm, and it resonates effectively within a frequency range of 3.1–5.68 MHz. Using scalar minimization techniques, patch transducers were interconnected into an antenna array with an optimized 3 mm spacing. Utilizing multi-objective optimization algorithm based on sperm fertilization procedure and shuffled frog leaping algorithm, optimal frequencies were obtained at 3,989,796.88 Hz and 3,989,951.83 Hz, respectively. Validated using CADFEKO software, the proposed antenna design demonstrated distinctive voltage distribution, superior directivity of 9.24 dBi, gain of 9.15 dBi, and 98.6% radiation efficiency when compared to the existing silicon-based root tomography antenna setups.

Content from these authors

This article cannot obtain the latest cited-by information.

© 2024 Fuji Technology Press Ltd.

This article is licensed under a Creative Commons [Attribution-NoDerivatives 4.0 International] license (https://creativecommons.org/licenses/by-nd/4.0/).
The journal is fully Open Access under Creative Commons licenses and all articles are free to access at JACIII official website.
https://www.fujipress.jp/jaciii/jc-about/#https://creativecommons.org/licenses/by-nd
Previous article Next article
feedback
Top