A Survey on Crop Recommendation Using Data Mining Methods

Abstract

Data mining is the process of analyzing and extracting useful information from large amounts of data. Data mining is used in a variety of industries, including banking, retail, medical, and agriculture. In agriculture, data mining is utilized to analyze numerous biotic parameters. Agriculture is a major source of income and employment in India. The most prevalent difficulty faced by Indian farmers is that they do not select the appropriate crop for their land. They will experience a significant drop in production as a result of this. Precision agriculture has been used to solve the farmers' issue. Precision agriculture is a modern farming method that utilizes research data on soil characteristics, soil types, and crop yield data to recommend the best crop to farmers depending on site-specific parameters such as temperature, rainfall, and the farm's latitude, longitude, altitude, and distance from sea. This decreases the number of times a crop is chosen incorrectly and increases production. Nevertheless, RS-based systems need the processing of massive volumes of remotely sensed data from many platforms, thus automated ways to provide reliable recommendations are presently receiving more attention. This is owing to automation-based systems' capacity to manage a high number of inputs and non-linear activities. The article provides a survey of the various methodologies followed with the view of developing an automated system for the recommendation of crop in agriculture system.