Non-destructive characterization of moisture-related relaxation dynamics and compositional changes in mold-infected wheat via fractional-order terahertz dielectric spectroscopy

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Fungal infection during wheat storage triggers complex physicochemical changes, including macromolecular degradation and alterations in moisture-related states, which may remain difficult to detect during early stages. In this study, we proposed a physics-based terahertz (THz) dielectric spectroscopic methodology to characterize mold-associated changes in wheat grains. By integrating the Landau-Lifshitz-Looyenga (LLL) effective medium theory with a generalized fractional-order Cole-Cole model, we extracted the intrinsic dielectric properties of wheat grains. Our results identify two major severity-associated dielectric responses: the relaxation time ( 𝜏 ) reflects changes in water-binding dynamics associated with grain matrix alterations, while the high-frequency permittivity ( 𝜀 ∞ ) is associated with compositional and hydration-related changes, with reducing-substance (DNS) measurements providing complementary biochemical information. By coupling these physically interpretable parameters with a Support Vector Machine (SVM), the proposed framework achieved an internal cross-validation accuracy of 94.2% with a macro-F1 score of 0.950 for mold severity grading. This research provides a physically interpretable THz dielectric framework for grain quality assessment, offering a rapid, non-destructive, and reagent-free approach for evaluating internal moisture-related relaxation dynamics and compositional integrity.

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