AGRIMENTOR: An Intelligent Crop, Fertilizer & Disease Recommendation System Using Machine Learning | IJCT Volume 13 – Issue 2 | IJCT-V13I2P101

Agriculture remains a key pillar of the Indian economy, and while some farmers are shifting to new technology to decide which crops to plant, when to apply fertilizers and how to manage diseases, many farmers are still relying on traditional techniques. These outdated methods often result in low yields and economic drawbacks. To overcome these issues, this paper introduces Agri Mentor, which is an intelligent Web-based platform that supports farmers in making informative and data-driven agricultural decisions. The system is based on three key components: crop recommendation, fertilizer recommendation, and plant disease detection, which is based on a customized trained Convolutional Neural Network (CNN). The front end is developed with React.js while the backend is powered with Node.js and Express. Authentication and data storage is handled by Firebase. Agri Mentor enables the farmer to upload the image of crop or leaves, get instant recommendations and interact with a simple and accessible interface on any device. Experimental results have shown that the system gives highly accurate recommendations concerning crop and fertilizer usage and also reliably identifies common plant diseases. Overall, this is a work of promoting sustainable and technology-oriented farming through the combination of artificial intelligence and new web development tools.