Convolutional Neural Network Based Intelligent Methods for Early Detection of Groundnut Leaf Spot

After China, the United States, and Nigeria, India is the leading producer of groundnuts and oil. On 20,000 acres, Konkan groundnut yields 1,800 kg ha-1. Konkan has an abundance of groundnuts. Leaf spots are the most influential biotic factors on groundnut yield and quality. Depending on the timing and conditions, both leaf marks can result in losses exceeding fifty percent. This disease inhibits photosynthesis by causing leaflet abscission and severe defoliation [2]. Image processing methods based on artificial neural networks, back propagation neural networks, support vector machines, and other methods. Convolutional Neural Network (CNN) and Artificial Neural Network (ANN) models are most frequently used for plant disease diagnosis in agriculture due to their superior computation and precision [3]. Utilizing convolutional neural networks and artificial neural networks, a disease detection model for groundnut early leaf spot caused by Cercospora arachidicola will be developed.