African Swine Fever (ASF) is a severe viral disease that has significantly impacted the pig farming industry in China. It first broke out in China in 2018 and quickly spread to multiple provinces, significantly affecting the production efficiency of the pig farming industry. This study utilized pig production data from 17 provinces in China from 2010 to 2022 and applied the Malmquist production efficiency index and panel regression methods to assess the impact of the ASF epidemic on the efficiency of the pig farming industry. The results indicated that the outbreak of ASF significantly reduced overall production efficiency, which magnified the vulnerabilities of the production system. Although there was a general decline in technological change and pure technical efficiency, the increase in scale efficiency suggested effective resource optimization by farmers under resource-constrained conditions. In light of these findings, it is recommended to strengthen biosecurity education and epidemic prevention measures in the pig farming industry and to enhance technological innovation and the application of smart technologies to improve production efficiency and disease response capabilities. Additionally, timely adjustments in farming scale and resource optimization will be key to addressing future challenges. Through these strategies, the pig farming industry can maintain stable production efficiency during future epidemics and push towards a more efficient and refined production model.

Climate change has increased the frequency of natural disasters, posing growing challenges to the high-quality development of the grain industry. Using China‘s provincial panel data from 2010 to 2023, this study examines the direct, moderating, and spatial effects of natural disasters on the high-quality development of the grain industry. A multidimensional index of high-quality development is constructed using the CRITIC weighting method. The results show that natural disasters significantly hinder the high-quality development of the grain industry, and this finding remains robust across a series of robustness tests. Further analysis indicates that agricultural irrigation and rural internet penetration mitigate the adverse effects of natural disasters, suggesting that both engineering resilience and digital resilience enhance the adaptive capacity of grain production systems. Heterogeneity analysis reveals that the negative impacts are more pronounced in major grain-producing regions and in the central, western, and northeastern regions of China. In addition, the spatial econometric results reveal significant negative spatial spillover effects, indicating that disaster shocks extend beyond directly affected regions through spatial interactions. This study contributes to the literature by extending disaster-impact research from grain output losses to the high-quality development of the grain industry, integrating engineering and digital resilience resources within a unified analytical framework, and providing new evidence on the spatial spillover effects of natural disasters.

China’s rapid population aging, coupled with the migration of young rural laborers to cities, has made “elderly agriculture” a defining feature of rural life, making agricultural land transition critical for shifting from fragmented smallholder farming toward modern, mechanized agriculture. Using two-period pooled cross-sectional data from the China Social Survey (2015 and 2021), this study uses Logit models together with a battery of robustness checks to examine how household aging shapes farm households’ land transfer-out behavior, and compares the aging–land transfer-out association across the 2015 and 2021 survey waves to examine its temporal heterogeneity. We find that (1) household aging is significantly and positively associated with land transfer-out, and this association is robust across model specifications; (2) the association is stronger among low-income and marginally stronger among low-education households; and (3) the aging–transfer-out association does not differ significantly across the two waves (p = 0.460), although the overall transfer-out rate nearly doubled over this period—a pattern consistent with, though not exclusively attributable to, the maturation of the New Rural Pension Scheme (NRPS).