Evidence map›Paper›PMID 42740113›Full record

ArticleSensors (Basel, Switzerland)2026

Design and Performance Analysis of Split Ring Resonator-Based Sensor for Soil Moisture Content Characterization.

Salman Alduwish, Yongxiang Li, James Scott, Akram Hourani, Nasir Mahmood

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In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Salman AlduwishSchool of Engineering, RMIT University, Melbourne P.O. Box 3000, Australia.ORCID 0009-0002-0714-7622
Yongxiang LiSchool of Engineering, RMIT University, Melbourne P.O. Box 3000, Australia.
James ScottSchool of Engineering, RMIT University, Melbourne P.O. Box 3000, Australia.ORCID 0000-0003-3200-6821
Akram HouraniSchool of Engineering, RMIT University, Melbourne P.O. Box 3000, Australia.
Nasir MahmoodSchool of Science, RMIT University, Melbourne 3001, Australia.ORCID 0000-0002-8340-1058

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper addresses the need for compact, low-cost soil moisture sensors operating at low microwave frequencies that can provide accurate, texture-aware (i.e., sensitive to different soil particle-size distributions such as sand and loam) characterization of soil permittivity and moisture content. Conventional techniques and many existing microwave resonator sensors are constrained by limited penetration depth, relatively large or complex structures, and calibration procedures that do not robustly account for different soil textures and moisture ranges. A dual-port microstrip square split ring resonator (SRR) sensor on Rogers RO3010 (Rmit University, Melbourne, Australia) is designed for operation at 1.3 GHz and analyzed using full-wave 3D electromagnetic simulations. The structure employs a T-shaped feedline and a shunt quarter-wavelength matching section to achieve strong field confinement in the sensing region and effective impedance matching. Soil is modeled as sandy and loamy superstrates over practical agricultural moisture ranges, with their complex permittivities drawn from reference datasets. Empirical calibration models are then developed, including polynomial curve fitting between resonance frequency shift and real permittivity, machine-learning-based calibration using resonance frequency and transmission loss features, and multiple linear regression linking moisture content to both real and imaginary permittivity components. The sensor exhibits a resonance frequency shift of about 115 MHz over 0-30% moisture for sand and 0-40% for loam, with a maximum sensitivity of 3.4%. Calibration models achieve mean absolute error below 1.22%, root mean square error under 1.58%, and coefficients of determination R

Indexed as

complex permittivitymachine learning calibrationsandy and loamy soilssoil moisture sensorssplit ring resonator (SRR)

Identifiers

PMID42740113
PMCPMC13568037

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.