This study is based on the data from co-authored papers, collaborative patents, and jointly authored varieties involving Chinese agricultural enterprises, universities, and research institutions from 2011 to 2023. We construct a three-dimensional dynamic equation system to model the agricultural industry–university–research (I-U-R) collaborative innovation network operation mechanism. Inspired by the Belousov–Zhabotinsky (B-Z) reaction, we model a three-variable oscillator with the state variables (network structure embeddedness, partner heterogeneity, and collaborative innovation output) to represent three primary substances in the chemical oscillators. This study investigates the network’s operational patterns and its determinants. Findings reveal that the patent network operates more efficiently than the paper and variety networks. Dependence on external government support increases with innovation complexity, coordination difficulty, and social value. Although a “structural optimization–resource agglomeration–output explosion” state is theoretically attainable under threshold conditions, the observed reality reflects “marginal structural optimization–continuous resource depletion–zero output growth”. Among the entities, eighteen are active leaders, forty-two constitute a stable but low-dynamism backbone, and ninety are general participants with limited innovation capacity. Significant structural contradictions highlight the need for targeted policy interventions to guide the network toward a more advanced and orderly state.

Purpose: This article aims to identify the structural characteristics of China’s agricultural collaborative innovation network (ACIN) and explore the mechanisms influencing its formation. Design/methodology/approach: Utilizing the data of agricultural science and technology co-authored papers, cooperative patents and jointly authorized varieties from 2012 to 2023, we adopt Social Network Analysis to identify the whole structural characteristics of the ACIN and apply Exponential Random Graph Model to investigate the influence mechanisms of the ACIN formation. Findings: ACIN formation is jointly promoted by agricultural science, technology and innovation (ASTI) capability, openness breadth, geographical province assortativity and geographical neighbor assortativity, albeit with gradually diminishing positive impacts. In contrast, openness depth, ASTI investment foundation, ASTI benefit foundation, organization assortativity, society assortativity and ASTI capability assortativity generally impede ACIN formation, though these negative effects weaken over time. Originality/value: We innovatively explore agricultural science and technology collaborative innovation (ASTCI) enhancement through network optimization. Defining the connotation of the national ACIN, we comprehensively demonstrate and analyze the influence mechanisms of the national ACIN formation from the combined influence of endogenous and exogenous factors.