Crop selection and yield prediction Using ML Techniques

Abstract

Abstract- “One of the most effective means of reducing severe poverty and promoting shared prosperity is agricultural development. Compared to other sectors, the agriculture sector's growth is 2-4 times more successful at boosting the lowest-income people's incomes. But today, growth that is based on agriculture is under trouble. Crop yields may be even more reduced by accelerating climate change and picking the wrong crop, particularly in areas with the greatest food insecurity, as well as most of the farmers expect their crop with high yield without knowing the land fertility this leads to increase in suicide rate of the farmers. The goal of this project is to create a system for advising on the optimal crop by taking attributes like humidity, Rainfall and soil parameters into consideration and also forecasts agricultural yield by taking land area into account. These functions will be carried out using the best machine learning approaches, which will be chosen after comparing the outcomes of all ML techniques effective rainfall has a great impact on the crop’s growth in agriculture.” Keywords-Precision agriculture, recommendation system, crop yield.