Implementation and Identification of Crop based on Soil Texture using AI

Soil is the foremost and elementary resource to improve efficiency in agricultural. Many advanced Computing Techniques are arisen and are get executed in different domains of agriculture. The main intent of the work is to develop an application that associates crop names and to expose the basic capabilities of the system. The Aim is to build a machine learning model that recommends the most suitable crop for a given region based on a variety of factors such as soil type, climate, precipitation, and available resources. The model will be trained using NLP techniques to analyze and extract useful information from text data on various crops, including their characteristics, growth conditions, and yield potential. A machine learning model trained using the extracted features and may be capable of predicting the most suitable crop for a given region based on the input data. The proposed model is used as a web service to facilitate faster development.