抄録
Under the multiple challenges of global food security, climate change, and sustainable agricultural development, biotechnology-driven intelligent agriculture is emerging as a core direction for future agricultural innovation. Among these advancements, the deep integration of artificial intelligence (AI) and gene editing technologies provides a novel scientific pathway for precise breeding of high-yield, high-quality, and pest- and disease-resistant crops. This paper systematically reviews the application progress and synergistic effects of AI and gene editing in modern crop breeding. AI, through big data analytics, machine learning, and phenotypic prediction models, has significantly improved the efficiency of target selection and genetic improvement, while gene editing technologies—especially the CRISPR-Cas system—have accelerated the discovery and targeted modification of beneficial trait genes owing to their efficiency, specificity, and controllability. The synergistic application of these technologies has established an intelligent breeding framework that enables precise regulation and optimization of complex agronomic traits from the gene to the population level. Representative cases are analyzed to illustrate the crucial roles of AI and gene editing in enhancing agricultural productivity, improving crop quality, and strengthening stress resistance. Furthermore, this study discusses the current challenges in algorithm reliability, editing precision, ethical governance, and policy regulation, and proposes future research directions. Overall, the integration of AI and gene editing is expected to continuously drive agriculture toward greater intelligence, sustainability, and efficiency, providing important technological insights for ensuring global food security and advancing ecological agriculture.
