AI-Driven Plant Disease Diagnosis: A Deep Learning Approach to Precision Agriculture

• Author(s): Mansi Bapu Zanje ; Sneha Balu Shirke ; Ishwari Sanjay Yadav
• Paper ID: 1708210
• Page: 690-693
• Published Date: 13-05-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 8 Issue 11 May-2025

Abstract

Plant diseases have long posed a critical challenge to global agricultural sustainability, leading to significant economic losses and food security concerns. Traditional disease detection methods, which rely on manual inspection and laboratory analysis, are often inefficient, time-consuming, and impractical for large-scale farming operations. The integration of artificial intelligence, particularly deep learning, has emerged as a revolutionary approach to overcoming these limitations. Deep learning models can rapidly and accurately identify plant diseases from images, allowing for early intervention and minimizing the spread of infections. This paper explores the application of deep learning techniques in plant disease diagnosis, delving into various models, training methodologies, datasets, real-world applications, and associated challenges. The study highlights the potential of AI-powered disease detection in improving agricultural productivity and sustainability while addressing the technical barriers that need to be overcome for widespread adoption.

Keywords

Artificial Intelligence, Deep Learning, Plant Disease Diagnosis, Precision Agriculture, Convolutional Neural Networks, Machine Learning, Transfer Learning, Image Processing.

Citations

IRE Journals:
Mansi Bapu Zanje , Sneha Balu Shirke , Ishwari Sanjay Yadav "AI-Driven Plant Disease Diagnosis: A Deep Learning Approach to Precision Agriculture" Iconic Research And Engineering Journals Volume 8 Issue 11 2025 Page 690-693

IEEE:
Mansi Bapu Zanje , Sneha Balu Shirke , Ishwari Sanjay Yadav "AI-Driven Plant Disease Diagnosis: A Deep Learning Approach to Precision Agriculture" Iconic Research And Engineering Journals, 8(11)