Tomato Plant Leaf Malady Detection Using Machine Intelligence

Abstract

Tomato crops are progressively mainstream, as a result of their high nutrition power which is available such as beta-carotene and Vitamin C, E. Lack of care for such crops results in causing serious ailments on plants and it is very important for identifying disease in plants for an efficient crop yield. Maladies on the plant causes depletion in both the quantity and quality of the crop. This paper possesses a real-time, precise, and efficient approach based on machine learning to recognize maladies existing in a tomato plant by revealing from its leaves. The model for disease detection was trained on plant leaves which were taken from PlantVillage Dataset and a convolution neural network-based algorithm was used for the identification of maladies in tomato plant leaf. The outcome shows that the presented approach is effective in detecting disease of tomato plant leaves as well as it could be globalized.