Authors : Shivani Ashok Kotkar; Ishika Sachin Narkhede; Renuka Rajendra Shirsath; Dr. R. Naik

Volume/Issue : Volume 9 - 2024, Issue 3 - March

Google Scholar : https://tinyurl.com/3an5c3k7

Scribd : https://tinyurl.com/2246j5sp

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAR2058

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Crop planning for the next season in agriculture is a difficult task for farmers because it is difficult to predict the price of the product in a particular season depending on the weather. Accurate and timely estimation of crop prices is important in making planting, harvesting and marketing decisions. Crop prices cannot be predicted accurately using crop price methods. This problem can be solved with machine learning models that will predict crop prices, show crop analysis patterns and present future situations to farmers. Farmers choose the right crop to produce crops; this includes crop selection, setting crop standards and storage. harvested crops provide sufficient information to estimate the appropriate crop price as a business. It will be used for past, present and future rainfall as well as last year's value. Based on this framework, machine learning algorithms are used to predict crop prices and produce accurate crop price prediction results. It helps farmers and others in agriculture make better decisions about crops. With the help of this survey, researchers will help find the best ideas and methods to predict crop prices using machine learning.

Keywords : Market Analysis, Future Forecasting, Mahine Learning, Crop Pattern.