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Stream/Area:
-
Subject:
-
Paper ID:
IJSREMWP9024
Volume:
9 |
3 |
Mar 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The Crop Suggestion System (CSS) is an innovative tool designed to assist farmers in selecting suitable crops based on soil characteristics. Utilizing machine learning algorithms, the system analyzes soil data, including nitrogen (N), phosphorus (P), potassium (K), and pH values, to provide personalized crop recommendations. This paper discusses the development, implementation, and evaluation of the CSS, highlighting its potential to enhance agricultural productivity and sustainability. The findings indicate that the CSS can significantly improve decision-making processes for farmers, leading to optimized crop yields and resource utilization
KEYWORDS
Publication Date
3/24/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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