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ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed

Peer Reviewed and Referred Journal || Free Certificate of Publication

Research and review articles are invited for publication in March 2026 (Volume 18, Issue 3) Submit manuscript

Crop recommendation system for growing best suitable crop

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  • Crop recommendation system for growing best suitable crop

Yash Gupta and Garima Srivastava *

Amity School Of Engineering and Technology, Amity University Uttar Pradesh, Lucknow, India.

Review Article
 
International Journal of Science and Research Archive, 2024, 12(01), 2928–2936.
Article DOI: 10.30574/ijsra.2024.12.1.1111
DOI url: https://doi.org/10.30574/ijsra.2024.12.1.1111

Received on 08 May 2024; revised on 15 June 2024; accepted on 18 June 2024

Agriculture is critical to ensuring global food security and financial stability, but faces significant challenges such as climate change, resource scarcity and population growth. To address these issues, crop recommendation systems have proven to be valuable tools to help farmers decide which crops to plant. These systems aim to increase crop yields and make better use of resources. This report offers an in-depth look at these promising crops, covering their importance, opportunities, challenges and future prospects. By analyzing existing research and case studies, we hope to provide a clearer understanding of the current consensus and suggest areas for further study and development.
A crop recommendation system is essentially a decision-making tool for farmers. It helps them select the best crops to grow based on factors such as soil type, climate, available resources and market demand. These systems use data analytics, machine learning and agronomic knowledge to analyze input parameters provided by farmers and then generate personalized recommendations. Using historical data, weather forecasts, soil quality assessments and crop performance models, the system aims to increase agricultural productivity, reduce risk and increase profitability for farmers. By easily integrating into digital platforms and mobile applications, crop recommendation systems enable farmers to make informed decisions and adapt to changing environmental conditions, promoting sustainable agriculture and food security.

Crop Recommendation; Recommendation System; Random Forest Model; Hybrid Model; Classification

https://ijsra.net/sites/default/files/fulltext_pdf/IJSRA-2024-1111.pdf

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Yash Gupta and Garima Srivastava. Crop recommendation system for growing best suitable crop. International Journal of Science and Research Archive, 2024, 12(01), 2928–2936. Article DOI: https://doi.org/10.30574/ijsra.2024.12.1.1111

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

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