Recommendation System for Crop, Fertilizer and Disease Detection

In general, rural farmers lack the knowledge and guidance required to cultivate crops that improve agricultural production. Farmers usually grow crops in the same pattern year after year, using the same fertilizers and crop types, this in turn results in the loss of nutrients and minerals required to create healthy crops. Farmers typically struggle to recognize the crop diseases and lacks knowledge in selecting the suitable to grow based on the local conditions. Government-funded initiatives and efforts have been established recently to teach farmers about crops and assist them to become more technologically aware. This study has developed a novel crop recommendation model to advice farmers about which crops to plant, where and how to prevent crop diseases, and what type of fertilizer to use. The proposed application also allows farmers to update or report crop-related issues for public access, including recommendations for certain disease cures. This application also gives advice on how to cultivate healthy crops, suggest fertilizers, and get assistance with crop disease issues by integrating various Machine Learning (ML) technologies. This study also initiates to create a blog to connect farmers globally and allows them to exchange difficulties and information on various crop diseases by using Flask.