An Approach Towards Crop Recommendation System Using Random Forest Machine Learning Algorithm - A Review

Abstract

With the use of an intelligent system called Crop Recommender, this project attempts to help Indian farmers choose the best crop to grow based on the qualities of the soil, as well as external parameters like temperature and rainfall. Indian economy is significantly influenced by the agricultural sector. The majority of Indians rely on agriculture for their living, either overtly or covertly. Thus, it can be said with certainty that agriculture is important to the nation. The majority of Indian farmers think that when choosing a crop to plant in a given season, they should rely on their instincts or simply they use their traditional methods which they have been using since old era. Instead of understanding it completely the crop productivity, is contingent on the current weather and soil conditions, they are more at ease merely adhering to established agricultural practices and standards. A single poor choice made by the farmer could result in unintended loss for both himself and the local agricultural sector. As the whole lateral system based on the agricultural industry. The machine learning algorithm can be used to solve this issue. The implementation of a recommendation system uses decision trees. The main objectives of this system are to advise farmers on which crops to plant which is suitable to its soil and seasonal rainfall.