A Comprehensive Analysis Comparing Deep Learning's Performance in Plant Leaf Identification and Disease Detection

Agriculture is a significant element of the economy of a country, and the food that makes the nation healthier. Plant diseases should be determined to avoid wastage of resources and ensure the sustainability of the agricultural sector. Bacterial or animal diseases may seriously affect the food production system and the security of the global food supply. The application of deep learning has gained popularity because it has been used to diagnose and classify plant diseases within a very short period of time, on the basis of photos that are used.The study employs a hybrid deep learning model to predict the disease of bottle gourd and pumpkin leaves by the integration of EfficientNet, InceptionNet, and Transfer Learning. Our proposed models performed better in terms of precision and strength over the existing methods, with an accuracy of 83% in predicting the illness of pumpkin leaf and 96% in predicting the illness of bottle gourd leaf on a real picture dataset with augmentation methods.