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Machine Learning-Based Crop Recommendation System Using K-Means Clustering for Precision Agriculture

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Machine Learning-Based Crop Recommendation System Using K-Means Clustering for Precision Agriculture


Yash Kushwaha | Damini Thakare | Prof. Anupam Chaube



Yash Kushwaha | Damini Thakare | Prof. Anupam Chaube "Machine Learning-Based Crop Recommendation System Using K-Means Clustering for Precision Agriculture" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Emerging Trends and Innovations in Web-Based Applications and Technologies, January 2025, pp.17-20, URL: https://www.ijtsrd.com/papers/ijtsrd74900.pdf

Utilizing Machine Learning and Clustering Techniques for Crop Recommendation Food security worldwide heavily depends on agriculture; however, farmers often face challenges in selecting the most appropriate crops for their fields due to diverse soil characteristics, weather conditions, and precipitation levels. This research introduces a Crop Recommendation System based on Machine Learning, employing K-Means Clustering, an unsupervised learning method, to categorize areas according to temperature, rainfall, soil pH, and soil type. The system analyzed historical farming data to group similar regions and propose ideal crops for cultivation. The model was developed using a dataset comprising soil and climate information from various geographic locations. Users can access a web-based interface to input their local parameters and receive dynamic predictions for optimal crops. The findings demonstrated that clustering offers a robust solution for precision farming, enabling data-driven crop selection. This system is designed to assist farmers in making well-informed decisions, potentially leading to enhanced agricultural output and long-term sustainability.

Machine Learning, Crop Recommendation, K-Means Clustering, Precision Agriculture, Soil Analysis


IJTSRD74900
Special Issue | Emerging Trends and Innovations in Web-Based Applications and Technologies, January 2025
17-20
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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