Authors:
Ballela Avinash Reddy, M. S. Bennet Praba, Rachaputi Yeswanth Vardhan, Charan Deepesh Kristam

Addresses:
Department of Computer Science Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamil Nadu, India.

Abstract:

A crop management system for precision agriculture utilizing machine learning aims to develop a farmer-friendly web application that incorporates ensemble learning algorithms. This web application features a crop recommendation system, a fertilizer recommendation system, a yield prediction system, and a crop possibility prediction system, all designed to assist farmers in making informed decisions based on reliable information. The crop and fertilizer recommendation system utilizes fundamental natural and soil properties of various minerals, as well as other factors, to recommend the most suitable crops for a particular region and the type of fertilizer required for that soil. The yield and crop possibility prediction system utilizes authentic data and current conditions, such as region, Season, crop type, and area, to help farmers maximize production and identify possible crops for that Season. The paper compares classification algorithms and chooses the best algorithm based on an analysis of the accuracy using ensemble learning. Based on the accuracy, the best algorithm is identified, and the model is trained accordingly. This improves efficiency, agricultural productivity, asset utilization, and food security. The crop management system serves as a fundamental asset for modern agriculture, enabling more effective strategies and driving economic progress.

Keywords: Crop Recommendation System; Fertilizer Recommendation System; Yield Prediction System; Crop Prediction System; Ensemble Learning; Authentic Data; Crop Possibility Prediction.

Received on: 03/07/2024, Revised on: 05/09/2024, Accepted on: 27/09/2024, Published on: 09/03/2025

DOI: 10.69888/FTSESS.2025.000370

FMDB Transactions on Sustainable Environmental Sciences, 2025 Vol. 2 No. 1, Pages: 1-14

• Views : 72
• Downloads : 12

Download PDF