Title: A machine learning-based nonlinear system for optimising crop selection and ensuring agricultural prosperity

Authors: Mamata Garanayak; Swagatika Tripathy; Subrat Kumar Parida; Monalisa Panda; Bijay Kumar Paikaray; Fatimun Nisha

Addresses: Department of Computer Science, Kalinga Institute of Social Sciences (Deemed to be) University, Odisha, India ' Department of Computer Science and Engineering, Centre for Data Science, Siksha 'O' Anusandhan (Deemed to be) University, Odisha, India ' Department of Computer Science and Engineering, Centurion University of Technology and Management, Vizianagaram, Andhra Pradesh, India ' Department of Computer Science and Engineering, Siksha O Anusandhan (Deemed to be) University, Odisha, India ' Department of Computer Science and Engineering, Centre for Data Science, Siksha 'O' Anusandhan (Deemed to be) University, Odisha, India ' Department of Computer Science and Engineering, Centurion University of Technology and Management, Odisha, India

Abstract: Our nation's economic prosperity is significantly influenced by agriculture. Investments in agricultural research and extension have consistently demonstrated excellent rates of return in Asia and the Pacific. In light of the impending difficulties in politics, the environment, and the economy, the cultivation of particular crops at specific times remains the primary issue that needs to be resolved. In this work, we create a prototype for recommendations that will first speculate on the kind of crop a farmer can cultivate based on the type of soil and environmental conditions (temperature, moisture, and rainstorm). The recommendation system will suggest five additional crops that are comparable to the predicted crop following the prediction. Prototypes relied on machine learning that have been shown to be effectual for predicting the best harvest can be utilised to accomplish this. The crops are predicted and recommended by the prototype with an accuracy of about 99.09%.

Keywords: cultivation; crop counsel prototype; precision agriculture; recommendation prototype.

DOI: 10.1504/IJANS.2025.148930

International Journal of Applied Nonlinear Science, 2025 Vol.5 No.1, pp.1 - 21

Received: 21 Jun 2024
Accepted: 28 Aug 2024
Published online: 04 Oct 2025 *

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