Haibo Jiang, Quanzhen Huang, Changdeng Yang, Yan Liang
), is one of the most devastating diseases threatening global rice production. In recent decades, a range of disease resistance genes have been identified in rice. These genes are involved in complex molecular mechanisms, such as the activation of immune receptors and defense signaling pathways, which trigger the plant's immune response to combat pathogen invasion. Some of these genes have been successfully applied in molecular breeding to develop new disease-resistant varieties. However, traditional breeding methods, which rely heavily on the experience and intuition of breeders, often face limitations in speed and efficiency. With the emergence of artificial intelligence (AI) technologies, there is growing interest in using them to accelerate the breeding of disease-resistant cultivars. This review summarizes the current understanding of the molecular mechanisms underlying BLB resistance, focusing on key resistance genes and their roles in defense responses. It also explores breeding strategies aimed at enhancing resistance and evaluates the opportunities and challenges of AI tools into rice disease resistance breeding.