International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 2 March-April 2024 Submit your research before last 3 days of April to publish your research paper in the issue of March-April.

Crop Management Using Machine Learning Techniques

Author(s) Shiva Kumar Chakali, Rishitha Erukulla, Harshitha Chinthareddy
Country India
Abstract India is an agricultural nation where crop productivity plays a major role in the country's economy. Thus, it is possible to argue that agriculture will serve as the foundation for every business in our nation. The country's economy is growing mostly due to the agriculture sector. Changes in the climate and other environmental factors are becoming a serious danger to agriculture. The application of machine learning (ML) is a crucial strategy for finding workable and efficient answers to this issue. Crop yield prediction is the process of forecasting crop production using historical data, such as weather, soil, and previous crop output. This focuses on utilizing the Random Forest algorithm to forecast the crop's production based on the available data. The forecast will assist farmers in forecasting yield.
Keywords Random Forest, Machine learning, Crop yield, Historical data.
Field Engineering
Published In Volume 6, Issue 1, January-February 2024
Published On 2024-01-09
Cite This Crop Management Using Machine Learning Techniques - Shiva Kumar Chakali, Rishitha Erukulla, Harshitha Chinthareddy - IJFMR Volume 6, Issue 1, January-February 2024. DOI 10.36948/ijfmr.2024.v06i01.11727
DOI https://doi.org/10.36948/ijfmr.2024.v06i01.11727
Short DOI https://doi.org/gtdr6g

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