Raman Spectroscopy as a Tool for Early Identification of Tan Spot Disease and Assessment of Fungicide Response in Wheat

Tan spot disease, caused by Pyrenophora tritici-repentis, poses a significant threat to wheat production worldwide. Early detection and precise fungicide application are essential for effective disease management. This study explores the potential of Raman spectroscopy—specifically surface-enhanced Raman spectroscopy (SERS) and coherent anti-Stokes Raman scattering (CARS)—as non-invasive tools for identifying fungal infection and assessing wheat’s biochemical response to propiconazole treatment. The methodology is entirely theoretical; no laboratory experiments were conducted. Instead, all spectral graphs and figures were generated through a collaborative process between the author and Microsoft Copilot, which served as a rendering tool. These AI-assisted visualizations simulate Raman responses based on known molecular interactions and literature data. The results demonstrate the conceptual feasibility of Raman-based diagnostics for precision agriculture, offering a sustainable approach to disease monitoring and fungicide management.