This study proposes a novel curriculum framework for Smart Breeding 4.0 to address the interdisciplinary talent gap in sustainable agriculture. Responding to the limitations of traditional agricultural education, the curriculum was developed through an analysis of emerging technological trends and industry needs. It is structured around four integrated modules: (1) Foundational Theory, tracing the evolution to data-driven breeding; (2) Technology Integration, combining AI and blockchain for precision breeding; (3) Practical Innovation, using real-world platforms for simulation projects; (4) Ethics and Policy, cultivating responsibility through case studies. Teaching emphasizes project-based learning with open-source tools, while assessment combines exams, data analysis, and innovation proposals. Explicitly aligned with key UN Sustainable Development Goals (SDGs), this conceptual framework provides a foundational model for agricultural universities worldwide. The primary contribution of this paper lies in its systematic design; future research will focus on empirical validation through pilot implementation.
Zhizhong Zhang (Tue,) studied this question.
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