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Plant Disease Detection Using Deep Learning Techniques

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Key Digital Trends Shaping the Future of Information and Management Science (ISMS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 671))

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Abstract

Loss in food production due to various viruses or bacteria in the crops is one of the prevailing issues in global agriculture. In order to improve the production, reduce the loss and improve the agricultural sustainability, early plant disease detection is essential. Manual monitoring of plants for disease detection is difficult and needs expertise. Deep Learning (DL)/ Machine Learning (ML) has contributed to detect the crop with disease utilizing the leaf condition. This paper proposes VGG19 based model to predict nine types of disease in plants before the symptoms develop. The publicly available dataset namely PlantVillage is used for experimental study. It involves image pre-processing, feature extraction and classification. The proposed model shows accuracy in prediction of 99.5%. From the experimental study and comparative analysis with the state-of-the-art methods, it can be concluded that the proposed model has significance to detect the diseases in plants effectively.

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Authors and Affiliations

  1. GITA Autonomous College, Bhubaneshwar, India

    Ambuja Behera

  2. Manipal University Jaipur, Jaipur, 303007, Rajasthan, India

    Somya Goyal

Authors
  1. Ambuja Behera
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  2. Somya Goyal
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Corresponding author

Correspondence to Somya Goyal .

Editor information

Editors and Affiliations

  1. Faculty of Information and Communication Technology, University of Malta, Msida, Malta

    Lalit Garg

  2. Department of Computer Science and Engineering, National Institute of Technology Raipur, Chhatisgarh, India

    Dilip Singh Sisodia

  3. Central University of Rajasthan, Tehsil Kishangarh, Rajasthan, India

    Nishtha Kesswani

  4. CIS Department, University of Malta, Msida, Malta

    Joseph G. Vella

  5. EMLYON Business School, Écully, France

    Imene Brigui

  6. Department of Applied Data Science, Institute of Energy Technology, Halden, Norway

    Sanjay Misra

  7. Computer Science and Engineering, National Institute of Technology, Chhattisgarh, India

    Deepak Singh

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Behera, A., Goyal, S. (2023). Plant Disease Detection Using Deep Learning Techniques. In: Garg, L., et al. Key Digital Trends Shaping the Future of Information and Management Science. ISMS 2022. Lecture Notes in Networks and Systems, vol 671. Springer, Cham. https://doi.org/10.1007/978-3-031-31153-6_35

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