Full-Wave Optical Modeling of Leaf Internal Light Scattering Dynamics with Potential Applications for Early Detection of Foliar Fungal Disease
Da-Young Lee, Dong-Yeop Na

TL;DR
This study develops a GPU-accelerated full-wave electromagnetic simulation framework to model leaf internal light scattering, enabling early detection of fungal infections through changes in optical properties before visible symptoms appear.
Contribution
It introduces a novel FDTD-based modeling approach that captures diffraction and multiple scattering in leaves, improving upon previous ray-tracing and radiative transfer models.
Findings
Accurately reproduces healthy leaf reflectance and transmittance.
Detects early fungal infection by changes in green and near-infrared reflectance.
Shows potential for pre-symptomatic disease detection using optical properties.
Abstract
Light interacting with plant leaves undergoes reflection, transmission, scattering, and absorption, which together determine leaf optical properties. Changes in leaf architecture disrupt internal light scattering dynamics and consequently affect photosynthetic performance. Previous studies on internal leaf light scattering have primarily relied on ray-tracing approaches (e.g., Raytran) or radiative-transfer models (e.g., PROSPECT). However, these high-frequency approximations cannot capture diffraction and coherent multiple scattering in wavelength-scale leaf tissues, unlike full-wave electromagnetic simulations. Here, we employ GPU-accelerated Finite-Difference Time-Domain (FDTD) simulations to model internal light scattering dynamics using segmented cross-section image geometries of representative dicot and monocot leaves with wavelength-dependent complex refractive indices. The…
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Taxonomy
TopicsGreenhouse Technology and Climate Control · Remote Sensing in Agriculture · Light effects on plants
