Digital Agriculture for Enhancing Yield, Nutrition, and Biological Stress Resistance

The application of artificial intelligence (AI) has fundamentally altered the agriculture industry by introducing novel approaches that boost crop yields while lowering the cost of production. The monitoring and estimation of preyield requirements, including water and energy for agriculture, disease prediction, and pest and weed control, have been made by the development of methodologies and applications based on AI. In addition, computer vision is a branch of artificial intelligence that focuses on enabling computers to interpret visual information from images or videos. It uses technologies such as object recognition, image segmentation, and motion estimation to identify objects in an image or video frame and track them over time. Computer vision has been used for applications such as imaging analysis of plants and prediction of plant health status. Also, artificial intelligence-based smart irrigation systems are being employed to improve crop yields while reducing water consumption. In addition, artificial intelligence-based crop yield forecasting algorithms have been developed in order to reliably anticipate crop yields. This enables governments to plan crops in an appropriate manner. Additionally, strategies based on AI have been applied to improve transportation demands, purchasing processes, storage facilities, and the agricultural sector’s economy as a whole. It is therefore possible to draw the conclusion that artificial intelligence has completely transformed the agriculture industry by delivering effective solutions that simultaneously raise levels of productivity and cut the expenses of production.