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Pepper bell leaf disease detection and classification using optimized convolutional neural network

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Abstract

Agriculture production plays a significant role in the country’s economy. Diseases are quite natural and common among plants. Identification of diseases in plants is necessary for averting losses in the yield of agricultural products. Manual monitoring of plants requires expertise, immense effort, and excessive time. Automatic detection will not only help in reducing time and effort but will also help in detecting disease at an early stage, as soon as it will start appearing on plant leaves. Recently, image processing in agriculture has attained a surge of interest by researchers. This study presents a five-layered CNN model for automatic detection of plant disease utilizing leaf images. In order to better train a CNN model, 20,000 augmented images are generated. Experimental results demonstrate that proposed optimized-CNN model can predict pepper bell plant leaf as healthy or bacterial with 99.99% accuracy. Robust results make the proposed optimized-CNN model a preliminary warning tool that can be applied as a disease identification system in a real cultivation environment.

Representation the methodology of classification of bacterial and healthy leafs.

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Data Availability

The datasets generated during and/or analysed during the current study is publicly available. The dataset is available from the corresponding author on reasonable request.

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Acknowledgements

This research was supported by Department of Computer Engineering under Khwaja Fareed University of Engineering and Information Technology(KFUEIT), Punjab, Rahim Yar Khan, Pakistan.

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Authors and Affiliations

  1. Department of Computer Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan

    Hassan Mustafa, Umair Hafeez, Ahmad Hameed, Ahmed Sohaib & Hamza Ahmad Madni

  2. Department of Computer Science, The Islamia University of Bahawalpur, Bahawalpur, Pakistan

    Muhammad Umer

  3. Department of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan

    Saleem Ullah

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  1. Hassan Mustafa
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  2. Muhammad Umer
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  3. Umair Hafeez
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  6. Saleem Ullah
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Correspondence to Muhammad Umer.

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Mustafa, H., Umer, M., Hafeez, U. et al. Pepper bell leaf disease detection and classification using optimized convolutional neural network. Multimed Tools Appl 82, 12065–12080 (2023). https://doi.org/10.1007/s11042-022-13737-8

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