Proceedings of the International e-Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2023)

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An Automatic Rice Grain Classification for Agricultural Products Marketing

Authors
Manjula Sri Rayudu1, *, Lakshmi Kala Pampana1, Shalini Myneni1, Sruthi Kalavari1, Raghupathy Reddy Madapa2
1VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, TS, 500090, India
2Wells Fargo International Solutions Pvt. Ltd, Hyderabad, TS, 500032, India
*Corresponding author. Email: manjulasree_r@vnrvjiet.in
Corresponding Author
Manjula Sri Rayudu
Available Online 21 December 2023.
DOI
10.2991/978-94-6463-314-6_21How to use a DOI?
Keywords
Agriculture Marketing; Machine Learning; Rice varieties
Abstract

Use of Technology in agriculture and marketing of agricultural products is essential in sustainable and quality production. Some of the usage areas of these technologies are quality control and classification of grains. To optimize the rice production and processing industry, ensuring best product quality and meeting consumer demands effectively, different varieties of rice grain need to be classified accurately and consistently. Manual classification of rice is laborious, time consuming, inconsistent, and inefficient. Our main objective is developing an Artificial Intelligence (AI) based automated model that can analyze and classify rice grains with high accuracy, allowing for higher throughput and increased productivity. In such, we proposed a Machine Learning (ML) based approach to classify five classes of rice varieties. Investigated the results of five classifiers namely, Logistic Regression (LR), K-Nearest Neighbors (KNN), Naive Bayes (NB), Decision Tree (DT) and Random Forest (RF). The RF classifier has given 99.40% accuracy in classifying the five varieties of rice grains.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International e-Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
21 December 2023
ISBN
10.2991/978-94-6463-314-6_21
ISSN
2589-4900
DOI
10.2991/978-94-6463-314-6_21How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Manjula Sri Rayudu
AU  - Lakshmi Kala Pampana
AU  - Shalini Myneni
AU  - Sruthi Kalavari
AU  - Raghupathy Reddy Madapa
PY  - 2023
DA  - 2023/12/21
TI  - An Automatic Rice Grain Classification for Agricultural Products Marketing
BT  - Proceedings of the International e-Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2023)
PB  - Atlantis Press
SP  - 209
EP  - 218
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-314-6_21
DO  - 10.2991/978-94-6463-314-6_21
ID  - Rayudu2023
ER  -