Published on: April 2026
CROP RECOMMENDATION SYSTEM
A.Y.Yaswanth G.Lavanya K.Sai A.Jothish
Dr. Y.H.Prasanna Raju
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Abstract
Agriculture is a primary source of livelihood for the majority of the Indian population and an important component of their economy. As the environmental and economic conditions change, there is a need for a system that can guide farmers in planning their agricultural activities to maximize their return on investment. This project aimed at developing a simple crop recommendation system that utilizes soil and environmental parameters to suggest the most suitable crop to plant. The soil parameters such as nitrogen, phosphorus, potassium content and the soil pH were utilized along with environmental factors such as rainfall, temperature and humidity. The system provides five suitable crop recommendations that are ranked based on their market value. Additionally, current weather conditions are provided to assist the farmer in making the best possible decision. The system offers a simple and effective way to select the best crop to plant based on relevant data.
How to Cite this Paper
A.Y.Yaswanth, , G.Lavanya, , K.Sai, & A.Jothish, (2026). Crop Recommendation System. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.459
A.Y.Yaswanth, , et al.. "Crop Recommendation System." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.459.
A.Y.Yaswanth, , G.Lavanya, K.Sai, and A.Jothish. "Crop Recommendation System." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.459.
References
- 1] A. Bakr, “Evaluation of Learning-Based Models for Crop Recommendation in Smart Agriculture,” International Conference on Advanced Systems and Applications (ASA), pp. 36–43, 2025.
- [2] Sorn-In, “Smart Crop Recommendation for Precision Agriculture: A Comparative Analysis of Ensemble and Deep Learning Models Using Soil and Environmental Data,” 2026.
- [3] Dahiphale, “Smart Farming: Crop Recommendation Using Machine Learning with Challenges and Future Ideas,” 2025.
- [4] Gunasekaran, Physics-Aware Ensemble Learning for Superior Crop Recommendation in Smart Agriculture, 2025.
- [5] S. H. Apu, “IoT-based Crop Recommendation System using Machine Learning via Mobile Application for Precision Agriculture in Bangladesh,” (under review), 2025.
- [6] K. Senapaty, A Decision Support System for Crop Recommendation Using Machine Learning Classification Algorithms, IJCSMC, Vol 13, Issue 6, 2024.
- [7] Vemulapalli. “An Experimental Analysis of Machine Learning Techniques for Crop Recommendation”, 2024. [Online]. Accessed 30 May. 2024.
Ethical Compliance & Review Process
- •All submissions are screened under plagiarism detection.
- •Review follows editorial policy.
- •Authors retain copyright.
- •Peer Review Type: Double-Blind Peer Review
- •Published on: Apr 18 2026
This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. You are free to share and adapt this work for non-commercial purposes with proper attribution.

