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April 28, 2026Open Access

An Intelligent Leaf Image–Based Plant Disease Detection and Pesticide Recommendation System Using Deep Learning

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Authors

MPMr. D. Retheesh, Jagadeesan S, Gokul Raj V, Kumaresan V, Manikandan V Department of Computer Science & Engineering Velammal Institute of Technology, PanchettiDTDEPARTMENT OF ARTIFICIAL INTELLIGENCE AND DATA SCIENCE R.M.K. College of Engineering and TechnologyMPMISSILE MAN SCIENTIFIC AND RESEARCH PUBLICATIONS

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Overview

Randomized trial demonstrates enhanced crop health through disease detection and pesticide suggestion.

Key Points

  • The aim is to develop a system that detects plant diseases early and suggests appropriate pesticide treatments.
  • Utilized deep learning algorithms, specifically Convolutional Neural Networks, for image analysis.
  • Analyzed leaf images to classify plants as healthy or diseased, identifying specific diseases.
  • Recommended suitable pesticides and calculated required dosages based on user input.
  • Improved accuracy of disease detection compared to traditional methods.
  • Enhanced decision-making for farmers by providing tailored pesticide recommendations.
  • Reduction in unnecessary pesticide usage leading to more sustainable agricultural practices.

Cite This Study

Panchetti et al. (2026) studied this question.

synapsesocial.com/papers/69f04eb8727298f751e72b57https://doi.org/10.5281/zenodo.19782814
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