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Reseach Article

Diagnosis of Bacterial Leaf Blight, Brown Spots, and Leaf Smut Rice Plant Diseases using Light GBM

by G.R.I.L. Jayasooriya, Samantha Mathara Arachchi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 48
Year of Publication: 2022
Authors: G.R.I.L. Jayasooriya, Samantha Mathara Arachchi
10.5120/ijca2022921895

G.R.I.L. Jayasooriya, Samantha Mathara Arachchi . Diagnosis of Bacterial Leaf Blight, Brown Spots, and Leaf Smut Rice Plant Diseases using Light GBM. International Journal of Computer Applications. 183, 48 ( Jan 2022), 53-58. DOI=10.5120/ijca2022921895

@article{ 10.5120/ijca2022921895,
author = { G.R.I.L. Jayasooriya, Samantha Mathara Arachchi },
title = { Diagnosis of Bacterial Leaf Blight, Brown Spots, and Leaf Smut Rice Plant Diseases using Light GBM },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2022 },
volume = { 183 },
number = { 48 },
month = { Jan },
year = { 2022 },
issn = { 0975-8887 },
pages = { 53-58 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number48/32259-2022921895/ },
doi = { 10.5120/ijca2022921895 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:15:19.655977+05:30
%A G.R.I.L. Jayasooriya
%A Samantha Mathara Arachchi
%T Diagnosis of Bacterial Leaf Blight, Brown Spots, and Leaf Smut Rice Plant Diseases using Light GBM
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 48
%P 53-58
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Considering the human population, food is one of the major problems Sri Lanka might face in the near future. Rice is the most widely consumed food product and one of the extensively cultivated crops in Sri Lanka. Therefore, increasing the crop yield is one of the primary needs of the country. When rice crops are infected with diseases, it results in a loss of crops. Therefore, it is essential to identify the disease in the early stage of infection to prevent the damage that can be done. Disease identification could be challenging without a clear understanding. With the advancement of new technologies, researchers are interested in identifying paddy diseases through machine learning and image processing techniques to help farmers identify infectious diseases accurately. It is difficult to observe the paddy leaf with the naked eye to diagnose the infected disease. In this research, an algorithm was developed to check whether the image contains different changes to the paddy leaf by considering the green colour pixels and their variance. OpenCV libraries have been used to develop the algorithm for feature extraction. Those features were used as attributes to the LightGBM algorithm to classify the disease images with over 80% accuracy.

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Index Terms

Computer Science
Information Sciences

Keywords

Decision Tree Diagnosis Diseases Leaves Light GBM Open CV Rice