WORLD SCI-TECH R&D ›› 2025, Vol. 47 ›› Issue (2): 198-214. doi: 10.16507/j.issn.1006-6055.2024.09.006 cstr: 32308.14.1006-6055.2024.09.006

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Research on Core Technology of Crop Biological Breeding Based on Patent Network Analysis

JIA Qian ZHANG Hui CHUAN Limin WANG Ailing QI Shijie ZHAO Jingjuan   

  1. Institute of Data Science and Agricultural Economics, Beijing Academy of Agriculture and Forestry Sciences
  • Published:2025-04-24

Abstract: Clarifying the core technology of crop biological breeding has guiding significance for China to deploy key core technology for crop seed sources, solve the bottleneck problem of seed sources, and accelerate the revitalization of the seed industry. Based on the Derwent Innovation patent database, the article starts from the perspective of core technology features, constructs a core feature measurement model, and selects core patents in the field of crop biological breeding in combination with the recommendations of experts, then social network analysis methods and tools are used to draw the correlation network and clustering network of crop biological breeding technology according to the potential correlation between core patents and core technologies to identify the core technology fields and subgroups. Finally, eight core technologies of crop biological breeding, including CRISPR/Cas genome editing technology, RNA interference genetic transformation system construction, external gene transformation technology system improvement and optimization, herbicide resistant gene mining, identification and multi gene coexpression, comprehensive trait improvement gene mining and genetically modified variety breeding, are obtained through expert analysis. In addition, the article provides prospects and suggestions for the future research and industrialization development of biological breeding technology in China combined with the current development status of core technology of crop biological breeding in China.

Key words: Biological Breeding; Core Patents; Core Technology; Core Feature Measurement Model; Social Network Analysis