Plant Disease Prediction with Fertilizer Recommendation Engine

Agricultural productivity has a critical role in maintaining economies, especially in nations where a significant proportion of the population is engaged in farming. Plant diseases are a serious risk to agricultural productivity because they can result in losses that are both quantitative and qualitative. To identify plant illnesses, this study suggests a complete system that makes use of deep learning and image processing methods, particularly Convolutional Neural Networks (CNNs).mAn artifi-cial neural network with specific capabilities for processing grid-structured data-especially images-is called a convolutional neural network (CNN). CNNs are particularly good at extracting hierarchical features from visual input. They are made up of pooling layers for spatial dimension reduction, activation functions for adding nonlinearity, and convolutional layers that apply filters to extract local patterns.