Plant Leaf Disease Detection Using CNN and Fertilizer Predictor

BHARTI NANA DURGADE; Mr. Sangram Dafale; Mr. Shreyash Lunkad; Mr. Aditya Madhave; Mr. Aditya Jadhav

Plant Leaf Disease Detection Using CNN and Fertilizer Predictor

Authors: BHARTI NANA DURGADE, Mr. Sangram Dafale, Mr. Shreyash Lunkad, Mr. Aditya Madhave, Mr. Aditya Jadhav

Unique Paper ID: 169456
Volume: 11
Issue: 6
PageNo: 1053-1055

Keywords: Plant diseases Crop security infection etc

Abstract:
For many different nations, agriculture is the most important and fundamental source of domestic income. Plant diseases brought on by a variety of pathogens, including bacteria, fungi, and viruses, can cost agribusiness companies a significant amount of money worldwide. Crop security in terms of both quantity and quality is essential for tracking plant disease. Therefore, identifying plant diseases is crucial. Different plant components exhibit the symptoms of the plant disease syndrome. However, the infection is typically seen in different plant leaves. Several researchers use computer vision, deep learning, few-shot learning, and soft computing techniques to automatically identify plant diseases from photos of its leaves. These methods also help farmers take prompt and appropriate action to prevent a decline in crop quality and quantity. Through careful feature extraction and selection, the use of these techniques in disease recognition can prevent the disadvantage of origin and increase research efficiency and technological speed. Additionally, specific molecular methods have been developed to stop and lessen the chance of infection.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 6
PageNo: 1053-1055

Plant Leaf Disease Detection Using CNN and Fertilizer Predictor

Available:https://ijirt.org/Article?manuscript=169456

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