Diseases are a serious threat to the sustainable and healthy production of plant yields and the food security of the world's people, and annually reduce a significant part of their production in terms of quantity and quality. Classical methods of diagnosing plant diseases based on pathogen isolation in the laboratory and visual field monitoring of disease progression and implementation of management methods are very time-consuming, require specialized personnel and expensive. Artificial intelligence-based software uses image analysis, environmental sensors and disease forecasting modeling to quickly diagnose diseases at the farm level, integrate meteorological data, soil and crop parameters to predict the time of disease outbreak, provide appropriate suggestions for disease management based on previously available data and implement management methods quickly and accurately using the Internet of Things, drones and robots. Artificial intelligence-based softwares, help to quickly and accurately diagnose plant diseases before they cause damage, establish predictive systems for diseases, predict the exact time of their occurrence and spread, and implement timely and correct management methods, enabling increased production of healthy plant products, while reducing costs to ensure food security for the world's people.
