Abstract
Abstract: Farmers have difficulty identifying, detecting, and treating plant diseases and their causes. Fruits are more susceptible to disease depending on the season and environmental conditions in which they grow during cultivation. The traditional method of predicting disease in fruits and plants is extremely difficult. Using the proposed model, a large dataset of different types of fruits and their diseases can be created, with a large number of images stored in different folders for processing the data set. Each data set is labeled with the type of disease and the affected fruit. This system is simple to train and test. Artificial Neural Networks are used to learn and categorize fruits and diseases. The proposed model can detect disease accurately and provide farmers with preventive measures and recommendations. Farmers all over the world will benefit from this system
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