Detection and Classification of Different Leaf Diseases in Solanum torvum using Deep Learning

Authors

  • Gautam Saikia Author
  • Mutum Bidyarani Devi Author
  • Lairenjam Obiroy Singh Author
  • Ranjit Dutta Author

DOI:

https://doi.org/10.64252/z7618425

Keywords:

Convolutional Neural Network (CNN), Deep Learning, Digital Image Processing, Solanam torvum.

Abstract

Fungal disease is a serious threat for plant life. Detection of this fungal disease under laboratory is a time consuming and laborious work. Image processing techniques can be used for early detect of these diseases. This paper discusses the detection of Early Blight and Late Blight diseases in Solanum torvum species. Early Blight is caused by Alterneria Solani and Late Blight is caused by Phythphora Infestens. Both fungal pathogens are identified in the laboratory of department of Botany, Madhabdev University, Assam. After identification of fungal disease image processing is carried out with the help of Convolution Neural Network. In this study, by using the EfficientNetB0 model CNN architecture, initially 98.75% accuracy has been observed and after fine-tuning 100% of classification accuracy has been achieved.

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Published

2025-09-19

Issue

Section

Articles

How to Cite

Detection and Classification of Different Leaf Diseases in Solanum torvum using Deep Learning. (2025). International Journal of Environmental Sciences, 8365-8372. https://doi.org/10.64252/z7618425