Development of High-Fidelity DenseNet Framework for Multi-Disease Real-Time Crop Health Surveillance and Farming Recommendation in Maize (Zea Maize) Cultivation in Nigeria
Domaine:
agricultureType de record:
modelpaper
Créateur:
AisAlhHyeSol
Éditeur:
Fed
Hôte:
In Nigeria, maize is the most widely cultivated grain, largely supporting food security for about half of the population. Research has indicated that there is annual production is declaiming to approximately 50% in maize, this is due to crop diseases and pest damage. This research presents a deep learning surveillance system for crop disease prediction and pesticides recommendations based on a DenseNet-121 architecture for continuous video streams. The research was evaluated on a curated field dataset collected from three states in Nigeria; Adamawa, Borno, and Taraba State. The system achieved a mean accuracy of 98.2% and a mean F1-score of 0.982. The results reflect a strong discriminative capacity across the diverse textural maize diseases.
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