Open Access
Research Paper
Peer Reviewed

Paper Title

Crop and Fertilizer recommendation system using Machine Learning

Article Identifiers

Registration ID: IJNRD_219465

Published ID: IJNRD2404654

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Keywords

Agriculture, machine learning, graphical visualization, k-means clustering, map reduce, recommendation system.

Abstract

This paper aims at collecting and analysing temperature, rainfall, soil, seed, crop production, humidity and wind speed data (in a few regions), which will help the farmers improve the produce of their crops. Firstly, we pre-process the data in a Python environment and then apply the MapReduce framework, which further analyses and processes the large volume of data. Secondly, k-means clustering is employed on results gained from MapReduce and provides a mean result on the data in terms of accuracy. After that, we use bar graphs and scatter plots to study the relationship between the crop, rainfall, temperature, soil and seed type of two regions (Ahmednagar, Maharashtra and, Andaman and Nicobar Islands). Further, a self-designed recommender system has been used to predict the crops and display them on a Graphic User Interface designed in a Flask environment. The system design is scalable and can be used to nd the recommended crops of other states in a similar manner in the future.

How To Cite (APA)

B. N. Divya, C. Mallika, D. Chaithanya, K. Himal kumar, & Mrs. K. Shandhini (April-2024). Crop and Fertilizer recommendation system using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), g457-g463. https://ijnrd.org/papers/IJNRD2404654.pdf

Issue

Other Publication Details

Paper Reg. ID: IJNRD_219465

Published Paper Id: IJNRD2404654

Downloads: 000122061

Research Area: Computer Science & Technology 

Author Type: Indian Author

Country: Kuppam/chittoor d, Andhrapradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404654.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404654

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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Call For Paper - Volume 10 | Issue 12 | December 2025

IJNRD is a Scholarly Open Access, Peer-Reviewed, Refereed, and UGC CARE Journal Publication with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost, and Transparent Peer Review Journal Publication that adheres to the UGC CARE 2025 Peer-Reviewed Journal Policy and aligns with Scopus Journal Publication standards to ensure the highest level of research quality and credibility.

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Paper Submission Open For: December 2025

Current Issue: Volume 10 | Issue 12 | December 2025

Impact Factor: 8.76

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