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296780

DETECTING MILDEW DISEASES IN CUCUMBER USING IMAGE PROCESSING TECHNIQUE

Article

Last updated: 26 Dec 2024

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Subjects

-

Tags

Biosystems Engineering

Abstract

In Egypt, Cucumber is a crucial cash crop, and its farming could significantly benefit the country's agriculture-based economy. Meanwhile plant disease detection manually is costly and time consuming. This study aims to improve early identification of downy and powdery mildew diseases using machine vision by comparing the effectiveness of several detection methods and developing a real life application. This approach will involve five steps including: image acquisition, pre-processing, feature extraction, post-processing, and classification. In which the experiment was conducted on two greenhouses where 931 images were obtained and used with five key features to train and evaluate the proposed methods. The classification performance of three machine learning algorithms, named discriminant analysis (DA), support vector machine (SVM) and K‑nearest neighbors (KNN), were compared. The results indicated that the fine gaussian SVM achieved the highest classification accuracy rate of 96%, where fine KNN got 95.8%, and quadratic DA obtained the lowest value 92.8%. Additionally, the suggested method has a practical application that enables automatic mildew disease detection via personal computers, eliminating the need for sample collection and laboratory analysis. This method could also be extended to identify other plant diseases and pests and track disease progression as the study moves forward.

DOI

10.21608/mjae.2023.201331.1096

Keywords

Cucumber, downy mildew, powdery mildew, Machine Learning, Image processing

Authors

First Name

A. A.

Last Name

Eldesoky

MiddleName

I.

Affiliation

Agricultural Specialist, General Administration of Plant Quarantine of Port Said and North Sinai, Port Said, Egypt.

Email

alaaattaelsayed@gmail.com

City

-

Orcid

-

First Name

H.

Last Name

Abd El-Nabi

MiddleName

M.

Affiliation

Prof. of Plant Pathology, Plant Pathology Dept., Fac. of Ag., Suez Canal U., Ismailia, Egypt.

Email

oheba2004@yahoo.com

City

-

Orcid

-

First Name

E.

Last Name

Omran

MiddleName

E.

Affiliation

Prof. of Soil and Water, Soil and Water Dept., Fac. of Ag., Suez Canal U., Ismailia, Egypt.

Email

ee.omran@gmail.com

City

-

Orcid

-

Volume

40

Article Issue

3

Related Issue

42190

Issue Date

2023-07-01

Receive Date

2023-03-27

Publish Date

2023-07-01

Page Start

243

Page End

258

Print ISSN

1687-384X

Online ISSN

2636-3062

Article File

MJAE_Volume 40_Issue 3_Pages 243-258.pdf

PDF . 1.9MB

Link

https://mjae.journals.ekb.eg/article_296780.html

Detail API

https://mjae.journals.ekb.eg/service?article_code=296780

Order

7

Type

Original Article

Type Code

1,326

Publication Type

Journal

Publication Title

Misr Journal of Agricultural Engineering

Publication Link

https://mjae.journals.ekb.eg/

MainTitle

DETECTING MILDEW DISEASES IN CUCUMBER USING IMAGE PROCESSING TECHNIQUE

Details

Type

Article

Created At

26 Dec 2024