International Journal of Emerging Research in Engineering, Science, and Management
Vol. 4, Issue 1, pp. 54-61, Jan-Mar 2025.
https://doi.org/10.58482/ijeresm.v4i1.8

This work is licensed under a Creative Commons Attribution 4.0 International License.

Exploring the Diversity of Rice Grain Variegation: A Review

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M. Niranjana, F. Kurus Malai Selvi

Research Scholar, Research Department of Computer Science, Government College for Women (Autonomous), Kumbakonam, (Affiliated to Bharathidasan University, Tiruchirappalli) Tamil Nadu, India. drniranjanasampath@gmail.com

Associate Professor & Head, Research Department of Computer Science, Government College for Women (Autonomous), Kumbakonam, (Affiliated to Bharathidasan University, Tiruchirappalli) Tamil Nadu, India.

Abstract: Challenges persist in developing a suitable method to distinguish high-quality cultivated rice seeds, which can be estimated based on their characteristics. To prevent rice grain varieties from being incorrectly labeled, the quality and type of rice grains must be accurately identified. In this paper, the classification of rice grains is analyzed, and a study is conducted on various algorithms used at each stage. Generally, visual observations are made by specialists using specialized devices that measure various properties. The resultant data are processed through different stages using multiple algorithms, which are discussed in detail. This study reviews machine learning techniques for differentiating rice seeds based on various algorithms. Each stage is analyzed with distinct objectives, and necessary conclusions are drawn to inform the next stage of research.

Keywords: Classification, Deep Learning, Ensemble Model, Machine Learning, Rice Grain.

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