An Explainable EfficientNetB4-Based Deep Learning Framework for Plant Leaf Disease Detection and Carbon Estimation Using RGB Image Analysis

This study presents an integrated deep learning-based framework for mango leaf disease detection and non-destructive carbon estimation using RGB leaf images. The proposed CNN-based disease classification model achieved excellent disease recognition accuracy, while the EfficientNetB4 regression framework demonstrated reliable carbon estimation performance. Compared with traditional laboratory-based and manual agricultural monitoring methods, the proposed system offers a scalable, low-cost, accurate, and environmentally sustainable solution for precision agriculture and smart farming applications. The findings demonstrate the strong potential of deep learning techniques for intelligent agricultural monitoring, crop health assessment, and climate-related environmental analysis.

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