Crop Yield Prediction Using Machine Learning Techniques


  • Indumathi V, Kavibala.M, Dr.P.Kavitha


Only when crops are managed effectively will the information they provide be turned into profitable decisions. Data has become a vital component of modern agriculture, assisting producers with critical decision-making, and current advances in data management are propelling Smart Farming forward at a breakneck pace. This type of data-driven farm management relies on data to improve productivity while reducing resource waste and pollution of the environment. We offer an agro-market knowledge suggested system based on cloud computing to contribute specific suggestions for farmers. We suggest putting in place a system that informs farmers about the crops that should be planted in a given season, as well as stakeholders about the product's current market price This type of system makes traditional farming practices more accessible to the younger generation. Bidding is difficult, but our proposed system offers the real market rate before informing the user of the current retail rate, preventing farmers from bidding. Agriculture yield forecasts are useful for farm administration and can assist collaborators in executing crucial agreements in their agricultural operation in today's agriculture. Farmers are able to manage all aspects of their farms. Farmers are able to manage all aspects of their farms while keeping an eye on the current market estimate of production.   As a result, this type of technique is advantageous to the younger generation.




How to Cite

Indumathi V, Kavibala.M, Dr.P.Kavitha. (2020). Crop Yield Prediction Using Machine Learning Techniques. International Journal of Modern Agriculture, 9(3), 1980 - 1990. Retrieved from