Soybeans play a crucial role in global food security and international agricultural trade. As the world’s largest consumer and trader of soybeans, China faces significant external dependence on supply and concentration of import sources. In light of increasing uncertainties in the international political and economic landscape, risks within China’s soybean supply chain have become increasingly prominent, highlighting the need to explore the global soybean supply potential and optimize import strategies. In response to national food security strategic requirements and anticipated changes in global production capacity, the Global Agro-Ecological Zone (GAEZ) model and the multi-objective nonlinear programming model are used in this paper to estimate the potential of soybean yield increase globally. From dual perspectives of risk minimization and cost minimization, diversified soybean import schemes for China are proposed across three scopes: neighboring countries, countries along the Belt and Road Initiative (BRI), and globally. The results indicate that in the long term, the center of gravity for global soybean production capacity remains in the Americas; these areas, along with Europe and Africa, are key regions for China to expand its soybean import sources in the future. If all countries’ soybean production potentials are fully explored, China can achieve sufficient soybean supply by relying on neighboring countries as well as those countries participating in the BRI. Specifically, it is estimated that during the 2020s (2011–2040), the potential soybean production in the United States, Brazil, and Argentina could reach more than 290 million tons, 140 million tons, and 130 million tons, respectively, under scenarios of both yield increase and cultivated land expansion. Neighboring countries such as India and Russia also show significant potential, with India’s production potentially increasing by 42.8 million tons and Russia’s by 10.4 million tons. The results suggest that China can achieve a more balanced and secure import strategy by leveraging the production capabilities of countries in the Americas, Europe, and Africa while also fostering closer economic and agricultural cooperation with neighboring nations and BRI countries. Based on these findings, policy recommendations aimed at stabilizing and ensuring China’s soybean supply are discussed.

Introduction: Escalating climate change has intensified storm surge disasters in China, whose economic repercussions are not confined to coastal areas but cascade nationwide through industrial supply chains. However, existing research overlooks these nationwide implications.Methods: To address this gap, this paper proposes an innovative assessment framework for evaluating the economic footprint of storm surge disasters, quantifies the indirect economic losses inflicted by storm surge disasters in China from 2011 to 2020 and further trace the diffusion of these losses across various industries and regions by developing a disastrously-extended input-output model.Results: The findings reveal that indirect economic losses constituted over 60% of the total economic losses from storm surge disasters during the aforementioned period. Interestingly, regions remote from the direct impact of the storm surge disasters were not immune to their effects. Among these, Henan Province emerged as the inland area most severely impacted by storm surge disasters, while the northwest and southwest regions typically experienced minimal indirect economic losses. Furthermore, the majority of the indirect economic losses originated from the Resource Processing Industry and Service Department of the directly affected regions, and the secondary industry of the potentially affected regions.Discussion: These findings demonstrate the inadequacy of localized disaster policies and underscore the urgent need for a nationwide resilience strategy focused on critical supply chain vulnerabilities.

In modern society with a highly developed Internet, online public opinions on swine epidemic diseases have become one of the important influencing factors for the fluctuation of pork prices. In this paper, the Baidu AI large model, Time-Varying Parameter-Stochastic Volatility-Vector Auto Regression (TVP-VAR) and Latent Dirichlet allocation (LDA) approaches are employed to investigate the dynamic impact of online public opinion regarding live swine epidemic diseases on fluctuations in pork price. The results show that: (1) Online public attention and negative sentiment exert significant time-varying impacts on pork price fluctuations, with these impacts being most pronounced in the short term and gradually diminishing over the medium and long term. (2) During the outbreaks of swine epidemic diseases, the impulse impact of online public attention and negative sentiment on pork price fluctuations exhibits distinct stage-specific characteristics. Initially, the impact is negative and subsequently turns positive before eventually waning. (3) The online discourse surrounding swine epidemic diseases can be categorized into four topics including disease transmission, vaccine technology, industry development, and disease prevention and control. Online public attention towards these four topics associated with negative sentiments generally contributes to variations in pork prices. Based on findings, several policy recommendations are proposed, including the timely release of swine epidemic disease information, the establishment and enhancement of the online public opinion monitoring and early warning system, as well as adherence to routine prevention and control of pig epidemic diseases.

Under tightening resource and environmental constraints, this study evaluates green total factor productivity (GTFP) in China’s apple industry. A balanced panel of eight major apple-producing provincial-level regions from 2006 to 2024 is analyzed using a Global Malmquist-Luenberger index with carbon emissions as an undesirable output. GTFP is decomposed into technical change (TECH) and efficiency change (EFFCH), and cumulative indices are examined using the Gini coefficient, kernel density estimation, σ convergence, and absolute and conditional β-convergence models. From 2007 to 2024, annual GTFP decreased by 0.54% on average, as a 0.20% annual TECH gain was outweighed by a 0.74% decline in EFFCH. Cumulative performance diverged across provinces and production regions: the Bohai Rim improved slightly, whereas the Loess Plateau declined. The national σtrend was insignificant; the Bohai Rim converged, while the Loess Plateau diverged. Negative and significant β coefficients indicate growth compensation following relatively low cumulative index levels, and this relationship strengthened after controlling for regional steady-state conditions. However, β-convergence did not produce sustained nationwide distributional convergence. Policies should therefore link technological progress with persistent efficiency improvements and region-specific diffusion mechanisms.