Bacterial Disease Detection of Cherry Plant Using Deep Features

Emrah Dönmez; Yavuz Ünal; Hatice Kayhan

doi:10.35377/saucis...1359146

EN

Bacterial Disease Detection of Cherry Plant Using Deep Features

Abstract

Although the cherry plant is widely grown in the world and Turkey, it is a fruit tree that is difficult to grow and maintain. It can be exposed to various pesticide diseases, especially during fruiting. Today, approaches based on expert reviews and analyses are used for the identification of these diseases. In addition, cherry producers are trying to detect diseases with their knowledge based on experience. Computer-aided agricultural analysis systems are also being developed depending on the rapid developments in technology. These systems help to monitor all processes from planting, cultivation, and harvesting of agricultural products and to make decisions to grow the products healthily. One of the most important issues to be detected and monitored with these systems is plant diseases. The features of the cherry plant disease will be determined by using a pre-trained convolutional neural network (CNN) model which is DarkNet-19, within the scope of this study. These machine learning-based features have been used for the detection of bacteria-based diseases commonly seen on the leaves of cherry plants. The acquired features are classified with Linear Discriminant Analysis, K-Nearest Neighbor, and Support Vector Machine classifiers to solve the multi-class problem including diseased (less and very) and healthy plants. The experimental results show that a success rate of 88.1% was obtained in the detection of the disease.

Keywords

Thanks

We thank Amasya University and Bandırma Onyedi Eylül University for providing the opportunity to use computer laboratories in the realization of this study.

References

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Details

Primary Language

English

Subjects

Computer Software

Journal Section

Research Article

Authors

Emrah Dönmez
0000-0003-3345-8344
Türkiye

Yavuz Ünal ^*
0000-0002-3007-679X
Türkiye

Hatice Kayhan
0000-0003-4679-7142
Türkiye

Early Pub Date

April 27, 2024

Publication Date

April 30, 2024

Submission Date

September 12, 2023

Acceptance Date

January 10, 2024

Published in Issue

Year 2024 Volume: 7 Number: 1

DOI

https://doi.org/10.35377/saucis...1359146

IZ

https://izlik.org/JA95HG73LR

Cite

RIS / Bibtex

APA

Dönmez, E., Ünal, Y., & Kayhan, H. (2024). Bacterial Disease Detection of Cherry Plant Using Deep Features. Sakarya University Journal of Computer and Information Sciences, 7(1), 1-10. https://doi.org/10.35377/saucis...1359146

AMA

1.Dönmez E, Ünal Y, Kayhan H. Bacterial Disease Detection of Cherry Plant Using Deep Features. SAUCIS. 2024;7(1):1-10. doi:10.35377/saucis.1359146

Chicago

Dönmez, Emrah, Yavuz Ünal, and Hatice Kayhan. 2024. “Bacterial Disease Detection of Cherry Plant Using Deep Features”. Sakarya University Journal of Computer and Information Sciences 7 (1): 1-10. https://doi.org/10.35377/saucis. 1359146.

EndNote

Dönmez E, Ünal Y, Kayhan H (April 1, 2024) Bacterial Disease Detection of Cherry Plant Using Deep Features. Sakarya University Journal of Computer and Information Sciences 7 1 1–10.

IEEE

[1]E. Dönmez, Y. Ünal, and H. Kayhan, “Bacterial Disease Detection of Cherry Plant Using Deep Features”, SAUCIS, vol. 7, no. 1, pp. 1–10, Apr. 2024, doi: 10.35377/saucis...1359146.

ISNAD

Dönmez, Emrah - Ünal, Yavuz - Kayhan, Hatice. “Bacterial Disease Detection of Cherry Plant Using Deep Features”. Sakarya University Journal of Computer and Information Sciences 7/1 (April 1, 2024): 1-10. https://doi.org/10.35377/saucis. 1359146.

JAMA

1.Dönmez E, Ünal Y, Kayhan H. Bacterial Disease Detection of Cherry Plant Using Deep Features. SAUCIS. 2024;7:1–10.

MLA

Dönmez, Emrah, et al. “Bacterial Disease Detection of Cherry Plant Using Deep Features”. Sakarya University Journal of Computer and Information Sciences, vol. 7, no. 1, Apr. 2024, pp. 1-10, doi:10.35377/saucis. 1359146.

Vancouver

1.Emrah Dönmez, Yavuz Ünal, Hatice Kayhan. Bacterial Disease Detection of Cherry Plant Using Deep Features. SAUCIS. 2024 Apr. 1;7(1):1-10. doi:10.35377/saucis. 1359146

Bacterial Disease Detection of Cherry Plant Using Deep Features

Abstract

Keywords

Öz

Thanks

References

Details

Primary Language

Subjects

Journal Section

Authors

Early Pub Date

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite