Abstract
Key common agricultural technologies are the core driving force for upgrading the agricultural industrial chain. This paper takes the development of biological breeding technology for wheat leaf rust resistance as a scenario, constructs a tripartite evolutionary game model involving the government, wheat breeding enterprises, and agricultural and forestry universities, and introduces factors such as the success probability of technology, technology spillover coefficient, and revenue distribution ratio. Through replicator dynamic equations and numerical simulation, it analyzes the evolutionary stable strategies of the collaborative innovation system and their influencing mechanisms. The research results show that: (1) The government’s social benefits and support costs are the key threshold factors affecting the government’s strategy choice; the government’s active support strategy is sustainable and effectively transmitted to wheat breeding enterprises and agricultural and forestry universities. (2) The participation willingness of wheat breeding enterprises is significantly constrained by the research and development costs of biological breeding technology for wheat leaf rust resistance and the losses from technological failure. (3) The willingness of agricultural and forestry universities to deeply cooperate is comprehensively influenced by multiple factors such as financial support for biological breeding technology for wheat leaf rust resistance, revenue from achievements, academic reputation, and the collaborative demands of wheat breeding enterprises. (4) The revenue distribution mechanism has a significant regulatory effect on the system’s evolution. The revenue distribution ratio for wheat breeding enterprises has a positive incentive effect on their participation willingness, while the regulatory role of the revenue distribution ratio for agricultural and forestry universities needs to be coordinated with government investment and the participation of wheat breeding enterprises in collaboration. The findings clarify how public value, technical risk, spillovers, and benefit allocation jointly shape collaborative breeding and provide a basis for staged support, risk-sharing, and benefit-allocation mechanisms.
Funding
This research was funded by The Key Talents of Hebei Yanzhao Golden Platform Gathering Program grant number [HJYB202527].
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Competing interests
The authors declare no conflict of interest.
Ethics
Ethical review and approval were waived for this study by the Institutional Review Board of Hebei Agricultural University.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Reprints and permissions
About this article
Cite this article
Zhao, Z., Ren, X., Wang, H. et al. Collaborative innovation in biological breeding for wheat leaf rust resistance: a tripartite evolutionary game analysis.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-67906-y
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-67906-y
Keywords
- Key common technologies in agriculture
- Wheat resistance to leaf rust
- Biological breeding
- Tripartite evolutionary game
Source: Ecology - nature.com

