Artificial intelligence in plant disease management
DOI:
https://doi.org/10.48165/jefa.2026.21.1.19Keywords:
Artificial intelligence, AI, disease management, detection, agriculture.Abstract
Artificial intelligence (AI) enables the early detection, precise diagnosis and other effective mitigation strategies, which revolutionized the plant disease management practices. Different tools are used in artificial intelligence like learning about machine models and neural networks, which analyse the various datasets from satellite imagery, drone surveillance and other smart phone-based disease recognition, which help in identification of symptoms of plant disease with high accuracy. The two types of techniques are computer vision and predictive analytics. The vision techniques help in the identification of pathogens, however, the predictive analytics help in forecasting disease outbreaks based on environmental and climatic conditions. This AI-powered decision support system assists farmers in choosing the best treatments, minimizing dependence on chemical pesticides, and fostering sustainable agricultural practices. AI also facilitates real-time crop health monitoring by integrating with Internet of Things (IoT) devices and remote sensing technology. There are also some challenges in using AI, such as, scarcity of data, model generalization and accessibility, hinder widespread adoption. There are some aspects of AI, which must be focused in future that include enhancing AI model robustness, improving data collection strategies and also on cost effective techniques to farmers related with AI. It holds potential to transform and revolutionize plant disease management, ultimately improving crop yield, food security, and environmental sustainability.
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