Dielectric Characterization of Plant Tissues Using a Resonant Fractal Sensor in the VHF–UHF Range

Cayo-Cabrera G.H.; Chique-Chino D.G.; Tapia-Cayo E.E.; Meza-Marocho G.; Meza-Duman R.A. · Smart Innovation, Systems and Technologies (2026) · DOI: 10.1007/978-3-032-24262-4_40

Resumen

The growing demand for real-time and non-invasive monitoring in agriculture has highlighted the limitations of conventional techniques for evaluating the dielectric properties of plant tissues, which are often invasive, bulky, or insufficiently sensitive at low radio frequencies. In this context, compact resonant sensors capable of detecting subtle dielectric variations in living tissues remain an open challenge. This study presents the development and experimental validation of a resonant radio-frequency sensor based on a Hilbert fractal geometry for the dielectric characterization of plant tissues in the VHF–UHF range. The proposed sensor was fabricated on an FR4 substrate and characterized using a vector network analyzer over the 70–600 MHz frequency range. Fresh geranium (Pelargonium spp.) leaves were used as dielectric samples and placed directly on the active region of the fractal structure. The sensor response was evaluated through changes in the transmission parameter (S21) under different dielectric loading conditions. Experimental results reveal clear and repeatable resonance shifts toward lower frequencies as the amount of plant material increases. In particular, a stable resonant mode near 350 MHz exhibited a monotonic frequency shift from 351.03 MHz (unloaded sensor) to 279.03 MHz and 243.04 MHz when one and two leaves were applied, respectively, accompanied by increased transmission attenuation. These results confirm the high sensitivity of the Hilbert fractal resonator to dielectric variations in plant tissues. The findings demonstrate that fractal-based resonant sensors offer an effective and low-cost solution for non-invasive dielectric sensing in agricultural and environmental applications, with potential extension to plant health monitoring and bioelectromagnetic energy studies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Instituciones: Universidad Nacional del Altiplano; Universidad Tecnológica del Perú