Design of Pentagon-Shaped THz Photonic Crystal Fiber Biosensor for Early Detection of Crop Pathogens Using Decision Cascaded 3D Return Dilated Secretary-Bird Aligned Convolutional Transformer Network

Crop pathogens threaten global agriculture by causing severe yield and economic losses. Conventional detection methods are often slow and inaccurate, limiting timely intervention. This study introduces a pentagon-shaped terahertz photonic crystal fiber (THz PCF) biosensor, optimized with the decision cascaded 3D return dilated secretary-bird aligned convolutional transformer network (DC3D-SBA-CTN). The biosensor is designed to detect a broad spectrum of pathogens, including fungi (e.g., Fusarium spp.) and bacteria (e.g., Xanthomonas spp.), by identifying their unique refractive index signatures. Integrating advanced neural networks and optimization algorithms, the biosensor achieves a detection accuracy of 99.87%, precision of 99.65%, sensitivity of 99.77%, and specificity of 99.83%, as validated by a 5-fold cross-validation protocol. It offers high sensitivity (up to 7340 RIU−1), low signal loss, and robust performance against morphological variations, making it adaptable for diverse agricultural settings. This innovation enables rapid, precise monitoring of crop pathogens, revolutionizing plant disease management.