Strawberry is a plant with high economic value and promising business prospects. A common problem in strawberry cultivation is that the seeds quickly get a disease. Some diseases like spot leaf, blight leaf, and scorch leaf can be detected from the leaf. Identifying strawberry diseases from its leaf can prevent damage to the fruit. We proposed a CNN Model to identifying strawberry diseases from its leaf. CNN is one of deep learning approaches that has been used in many previous studies to identifying fruit diseases. There are four different strawberry leaf types, healthy, scorch leaf, spot leaf, and leaf blight, in the proposed technique. Using ResNet-50 architecture for the model
with 3600 images, the model achieves a prediction accuracy of
100% for spot leaf, 99% for blight leaf, 99% for scorch leaf, 100% for a healthy leaf. The proposed model provides a simple, reliable technique for identifying strawberry diseases.