Revolutionizing Plant Disease Detection: A Comprehensive Review

Year : 2024 | Volume :01 | Issue : 02 | Page : 44-55
By

Shruthi T.V.,

Suresh M.B.,

  1. Research Scholar Department of CSE, East West Institute of Technology, VTU, Belagavi, Karnataka India
  2. Professor & HOD Department of ISE, East West Institute of Technology, VTU, Belagavi Karnataka India

Abstract

Rise in population demands more food production but the diseases in plants contribute to loss. The advancement in agricultural field has a remarkable effect in detecting plant diseases. These diseases will have a major impact on the quality of plant and yield and hence can destroy the entire plant if they are not controlled on time. To reduce disease-related losses, it is necessary to identify different types of diseases and control the diseases in the early stages. Subjective audit by farmers or agricultural experts across vast plant fields consumes much time and is impractical thus minimize crop production. Therefore, many agricultural procedures and practices are adapted to control plant diseases. Existing systems have adapted various image processing techniques, computer vision, machine learning techniques, deep learning techniques and deep transfer learning technique for diseases detection. Artificial Intelligence (AI) plays a crucial role in addressing many challenges faced. It is integrated with other technologies for efficient farming. This review helps the researcher to know the existing methods applied for the detection of plant diseases and also the research gaps and future exploration in the field of deep learning to improve the model accuracy for better detection.

Keywords: Machine Learning models, Precision Agriculture, Deep Learning models, Deep Transfer Learning models, Pretrained models, Quantitative Metrics

[This article belongs to International Journal of Advance in Molecular Engineering(ijame)]

How to cite this article: Shruthi T.V., Suresh M.B.. Revolutionizing Plant Disease Detection: A Comprehensive Review. International Journal of Advance in Molecular Engineering. 2024; 01(02):44-55.
How to cite this URL: Shruthi T.V., Suresh M.B.. Revolutionizing Plant Disease Detection: A Comprehensive Review. International Journal of Advance in Molecular Engineering. 2024; 01(02):44-55. Available from: https://journals.stmjournals.com/ijame/article=2024/view=169560

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Regular Issue Subscription Review Article
Volume 01
Issue 02
Received May 8, 2024
Accepted May 15, 2024
Published August 29, 2024
Views: 5

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