Role of Artificial Intelligence in Disease Detection of Various Crops in Agriculture

Global food security depends heavily on agriculture as its fundamental foundation although it encounters major obstacles to maintain crop productivity and sustainability. The use of conventional crop monitoring techniques combined with disease detection methods involves large labor costs and feedback delays which cause substantial yield losses. Real-time analysis of crop conditions now becomes possible through the agricultural application of Artificial Intelligence (AI), which monitors crops, soils, and environmental factors in real time. The research investigates how Artificial Intelligence transforms agriculture through its three key applications, which include disease prediction technology and soil touchpoints management as well as resource optimization systems. AI achieves precision farming through drone operations along with Internet of Things sensors while using machine learning to detect pests and optimize irrigation systems. Research confirms that AI operates as a tool to deliver greater agricultural efficiency and diminished environmental impact and enhanced food security, it establishes sustainable agricultural practices. The artificial intelligencebased tool serves growers as a useful instrument to stop various crops like sugarcane, potato and carrot crop infections that disrupt the harvesting operation.