Agriculture Crop Recommendation System Using Machine learning
Sangeetha Allam, Bollimuntha Manjusha, Asha Vuyyuru, P. Veeranjaneyulu, K. Pushpa Rani, Sushruta Mishra
Abstract
India's socioeconomic system is mostly dependent on agriculture. Farmers used to rely on word-of-mouth, but the current climate prevents them from doing so. The IT industry has grown in order to provide farmers with precise agricultural information, which has resulted in several advancements in the field of agriculture sciences. In the current climate, having access to contemporary technologies for agriculture is desirable. [1] Using machine learning methods, it is feasible to make predictions and create a precise model from the data. There are solutions for agricultural problems such crop rotation, crop forecasts, water and fertilizer needs, and crop protection. Due to the environment's unpredictable climatic elements, an effective method is required to expedite crop cultivation and support farmers in their production and management. It's possible that aspiring farmers can now engage in improved agriculture. [2] A farmer can receive a number of recommendations to aid with crop yield. Based on the properties of the soil, the timing of the sowing, and the location, farmers occasionally choose the incorrect crops. [3]Many as a result commit suicide, stop farming, and go to cities in search of employment. By taking into account all relevant aspects, including the planting season, soil, and geographic location, this research effort has developed a method to assist farmers in choosing crops. Following a careful review of crop data gathering, crop recommendations were given.