In response to increasingly complex risks and challenges and to safeguard national agricultural product supply security, this study constructs a four-dimensional evaluation index system encompassing “Resistance-Adaptation-Recovery-Innovation”. Utilizing panel data from 30 provincial-level regions in China from 2017 to 2023, and employing a comprehensive methodology including the entropy method, Dagum Gini coefficient, Markov chain, kernel density estimation, and convergence models, this research measures the resilience of China’s agricultural product supply chain and investigates its spatiotemporal evolution patterns. The findings are as follows: Firstly, the resilience level of the national agricultural product supply chain shows overall steady improvement, but regional development is uneven, presenting a pattern of eastern regions leading, central regions maintaining steady progress, and western regions catching up. Secondly, the overall resilience difference is strongly correlated with regional variability, with the most pronounced internal disparity observed in the western region. Thirdly, the evolution of resilience exhibits path dependency characterized by the coexistence of a “low-level trap” and “high-level stability”, and less developed regions demonstrate a significant “catch-up effect” towards their more developed counterparts. Based on these findings, this study proposes countermeasures such as implementing targeted policies for different regions, establishing cross-regional coordination mechanisms, strengthening dynamic monitoring and early warning systems, and promoting innovation-driven development and structural upgrading. These efforts aim not only to enhance China’s capacity to respond to risks in its agricultural product supply chain and ensure national food security, but also to provide valuable insights for other countries facing similar challenges in building resilient agricultural systems in an increasingly uncertain global environment.
Wang et al. (Thu,) studied this question.