AI for Agro-Business in the Identification of Rice Diseases

Rice's quality and resistance to disease are crucial for agribusiness. Crop production must be increased using effective practises and tactics. The introduction of sophisticated artificial intelligence and machine learning methods has been especially beneficial to the area of agricultural innovation. By examining photos of leaves, agricultural fields, or seeds, these techniques have shown astoundingly high levels of success in diagnosing illnesses. In order to increase the production of rice, one of the main crops in the world, this research provides a thorough assessment with a precision agricultural emphasis. The research articles reviewed and analysed in this work use a variety of techniques for identifying crop diseases, evaluating the health of seedlings, and assessing grain quality. They were all published within the last eight years. The Web of Science and Scopus databases were used in experiments to extract data, which allowed for an analysis of research trends in rice disease diagnosis using artificial intelligence. This study includes worldwide trends, annual patterns, and country-specific citation data, offering insightful information to academics working in this area.