Published Paper Details:

In India agriculture contributes approximately 20% of GDP with employed workforce of 41%. India is the second-largest producer of agriculture crops. The technological contribution may help the farmer to get more yield. The research focuses mainly on South Indian agricultural crops from Karnataka ,Kerala, Tamil Nadu and Andhra Pradesh. In this study we have proposed a system for crop selection and to identify parameters that are responsible for growth of certain crops. There are many machine learning algorithms that can be used for such predictions one among them is Random Forest Regressor. Here we have used Random Forest Regressor algorithm to know the exact crop to be grown based on the parameters entered by the user along with other crops suitable for that region .The data of crop cycle for summer, Kharif, rabi, autumn and whole year is used. The dataset is resourced by gathering data from kaggle and climate-data.org .The experimental parameters considered for study are cultivation area, crop, state, district, season, year , rainfall ,soil pH and temperature. The concept of this paper is to implement crop selection method by identifying the features responsible for growth