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Automated Black Rust Detection in Wheat Using CNNs

Automated Black Rust Detection in Wheat Using CNNs

Rupsha Roy / Saptarshi Mondal

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Editorial:
KS OmniScriptum Publishing
Año de edición:
2025
Materia
Botánica y ciencias de las plantas
ISBN:
9786207843930
65,43 €
IVA incluido
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Sobre IBD

This research introduces a highly accurate CNN-based model (99.9% accuracy) for early detection of black rust in wheat using image analysis. The model was trained on a diverse, region-specific dataset, ensuring robust performance across varying agro-climatic conditions. It enables early-stage disease detection, reducing yield loss, optimizing fungicide use, and promoting sustainable farming practices. The system is lightweight, deployable on smartphones, and integrates with digital farming ecosystems, empowering farmers with accessible AI tools. Its scalability and compatibility with IoT and cloud platforms position it as a vital step toward precision agriculture and national food security.

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