Detection and Classification of Different Leaf Diseases in Solanum torvum using Deep Learning
Year: 2025
Type: article
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.
DOI: 10.64252/z7618425
Authors: Gautam Saikia, Mutum Bidyarani Devi, Lairenjam Obiroy Singh, Ranjit Dutta
Institution: Manipur International University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
OpenAlex ID: W4414986947
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