EfficientNet B0 CNNs for Orange Huanglongbing and Tomato Pathogens

Citrus greening, also known as Orange Huanglongbing, and various bacterial and fungal pathogens pose a significant threat to the orange and tomato crops in the Nagpur region and its surroundings. These diseases have had adverse effects on production and the socio-economic well-being of the region, emphasizing the need for early detection and intervention. This Research paper presents an approach using Convolutional Neural Networks (CNN) with EfficientNet B0 for the early detection of diseases in oranges and tomatoes, achieving an impressive accuracy of 98% on test data. The EfficientNet B0 model is fine-tuned and evaluated to ensure robust disease detection. These Results indicate that our CNN model achieves remarkable accuracy in identifying early disease symptoms, showcasing its potential for practical implementation. This research demonstrates the efficacy of CNNs in early disease detection in oranges and tomatoes, offering a promising solution for disease management in the Nagpur region. The model’s high accuracy paves the way for practical implementation and highlights the potential to bolster agricultural sustainability and community well-being.