Crop & Fertilizer Recommendation Using Machine Learning

Registration ID: IJNRD_217001

Published ID: IJNRD2404212

DOI: Click Here to Get

Pushparaj Naik , Somnath Melasagare , Sanket Pandit , Soham Gawade , Prathmesh Narvekar

Crop Recommendation

The incorporation of machine learning into systems for recommending crops and fertilizers is a revolutionary development in precision agriculture. The way the system works is by gathering and analyzing several factors, like crop kind, weather, and soil quality. The system creates correlations and patterns in the data by using machine learning models and algorithms. By using less extra fertilizer, this method not only improves crop quality and yield but also tackles sustainability issues. Furthermore, system adjusts to changing environmental conditions, providing real-time information. while farmers gain from higher efficiency and lower costs. Implementation of machine learning-driven crop and fertilizer recommendation systems represents a key step toward a more sustainable and productive agricultural future.

Published Paper   E-Certificate

Pushparaj Naik, Somnath Melasagare, Sanket Pandit, Soham Gawade, & Prathmesh Narvekar (April-2024). Crop & Fertilizer Recommendation Using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), b915-b921. https://ijnrd.org/papers/IJNRD2404212.pdf

Volume 9 Issue 4, April-2024

Pages : b915-b921

Paper Reg. ID: IJNRD_217001

Published Paper Id: IJNRD2404212

Downloads: 000122013

Research Area: Computer Engineering 

Country: Sindhudurg, MAHARASHTRA, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404212.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404212

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

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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