CW Terahertz Spectroscopy of Heavy-Metal-Induced Alterations in Arabidopsis halleri

Soil pollution and the resulting accumulation of heavy metals in plants represent an increasing challenge for food safety and environmental monitoring. Traditional detection techniques are often destructive, labor-intensive, and poorly suited for in-situ or large-scale applications. This study explores whether continuous-wave (CW) THz spectroscopy can detect alterations in Arabidopsis halleri leaves induced by long-term exposure to heavy metals, and how different sample preparation states influence this. Five leaf sets, ranging from well-prepared (dried and pressed) to fresh and unprocessed, were analyzed using CW THz transmission spectroscopy in the frequency range from 0.1 to 0.8 THz. Under controlled sample conditions, differences in the log-linear slope of the normalized transmission spectra were observed between contaminated and control groups. These findings suggest a sensitivity of the THz transmission signal to changes in leaf composition, potentially associated with heavy metal uptake. However, the spectral contrast diminished under less standardized conditions (e.g., fresh or unpressed leaves), likely due to water-induced absorption and structural variability. In some cases, a difference in fit amplitude remained detectable, but the slope-based separation was not preserved. While the physical origin of the observed spectral differences remains to be fully resolved, possible contributing mechanisms include changes in water binding, dielectric properties, or cell wall organization. These results highlight both the promise and the current limitations of CW THz spectroscopy for non-destructive leaf analysis. Future efforts will focus on clarifying underlying mechanisms, improving robustness under variable sample conditions, and exploring the potential of multivariate and machine-learning methods for enhanced signal interpretation. The compact architecture of CW systems may ultimately support their integration into portable diagnostic tools.