Smart Crop Recommender System Using Machine Learning

Agriculture is key to any country's economic growth. However, meeting food requirements of the present population due to the ever-rising human population, changing climatic conditions, and limited natural resources becomes a difficult problem. Smart agriculture is an innovative way of supporting farming by recommending the best crops to use and solving the current problems in maintaining farming sustainable. The classification machine learning algorithm is used to build the recommendation model. This paper's concept is a method of choosing appropriate crops that results in several favorable outcomes for agriculture and farmers. Since the crop yield can be increased, it will contribute to boosting our country's economy. Crops recommendation system for agriculture is based on various attributes such as crop type, soil composition, weather condition, soil pH and rainfall. The data have taken from the historic data which was collected from soil and water conservation and district agriculture office Nagaland and use supervised machine learning approaches to apply different ML algorithms. The effected of algorithm are measure on a various scale including Accuracy, Precision, Recall and F1-Score. The random forest outperformed in specifying the suitable crop with an impressive accuracy of 92.59%.