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AGRICULTURE CROP RECOMMENDATION BASED ON PRODUCTIVITY AND SEASON

Mrs. S. Sharmila1, K. Ameena Begum2, G. Hemalatha3, P. Saran4, K. Sutharsan5

1Assistant Professor, Department of Information Technology, Nandha Engineering College

(Autonomous), Erode, Tamil Nādu, India

2,3,4,5 UG Scholar, Department of Information Technology, Nandha Engineering College (Autonomous), Erode, Tamil Nādu, India

Email id: sharmilas@nandhaengg.org 1 , ameenbegum01@gmail.com 2

ABSTRACT: Ranchers used to enlist informal, but due to climate conditions; they could now not do as such. Horticultural variables and boundaries are utilized to offer realities that might be utilized to study more prominent roughly Agri-realities. Horticultural issues like yield forecast, revolution, water necessity, compost prerequisite and wellbeing might be addressed. Because of the climate's fluctuating climatic elements, a green strategy to sell crop development and help ranchers of their assembling and control is required. As a beach front state, Tamil Nadu faces vulnerability in horticulture which diminishes its creation. Rural variables and boundaries make the information to get bits of knowledge about the Agri-realities.

Development of IT world drives a few features in Horticulture Sciences to assist ranchers with great rural data. AI Strategies fosters a distinct model with the information and assists us with achieving expectations. Agrarian issues like yield forecast, revolution, water necessity, compost prerequisite and insurance can be settled. Because of the variable climatic elements of the climate, there is a need to have an effective method to work with the yield development and to help out the ranchers in their creation and the board. This might assist forthcoming agriculturalists with having a superior horticulture. Arrangement of suggestions can be given to a rancher to assist them in crop development with the assistance of information mining. To carry out such a methodology, crops are suggested in view of its climatic elements and amount. Information Examination clears a method for developing helpful extraction from horticultural data set. Crop Dataset has been dissected and suggestions of yields are done in view of efficiency and season.

Keywords: Climatic conditions, forecasting, Horticulture, Crop prediction.