A Comprehensive Review on Soil Nutrient Management Using Machine Learning Tools

Soil fertility management is a key part of sustainable farming. Traditional methods to check soil properties and decide on fertilizer use take a lot of time and effort. Machine learning (ML) tools offer modern solutions to these problems. ML can handle large amounts of data, predict soil nutrient needs, and improve fertilizer use. Using techniques like regression and classification, ML models can boost crop production and lower harm to the environment. ML can also use real-time data from IoT devices or remote sensing to make better decisions with fewer mistakes. This review focuses on how ML can help in managing soil fertility. These methods can be used in many ways, offering different techniques and benefits. It also discusses challenges like data availability and accuracy of models. The results show that ML tools can help in sustainable farming by using resources wisely and managing soil health better.