Introduction: The ongoing decline in staple crop acreage and the accelerating trend of “non-grain” cultivation pose structural risks to China’s food security. Agricultural insurance, beyond its traditional role in risk mitigation, may serve as a structural policy tool to influence farmers’ planting decisions and guide cropping structures toward staple grains. However, empirical evidence on this guiding function remains limited.Methods: Drawing on data from the 2020 China Rural Revitalization Survey (CRRS), this study employs a two-limit Tobit model to examine the impact pathways and moderating mechanisms through which agricultural insurance affects farmers’ cropping structure adjustment. The analysis addresses endogeneity issues and explores heterogeneous effects across different farmer groups.Results: Agricultural insurance significantly increases the proportion of staple crops in total cultivated area, with findings robust to both robustness checks and endogeneity tests. Mechanism analysis shows that digital technology training significantly strengthens the incentive effect by improving farmers’ ability to access and interpret policy information. The marginal effect also rises with greater distance from the administrative center, indicating higher responsiveness in institutionally underserved areas. Heterogeneity analysis reveals stronger effects among highly educated farmers, small-scale operators, residents in pilot regions, those in non-plain terrains, and farmers in eastern provinces.Discussion: These results confirm the effectiveness of agricultural insurance as a policy instrument for guiding cropping structure adjustments. Strengthening policy communication, expanding service coverage—especially in remote areas—and improving coverage levels can further enhance its contribution to national food security strategies and the Sustainable Development Goals (SDGs).

The digital economy is increasingly recognized as a key force behind sustainable agricultural development, transforming farm management and enhancing food security through innovation, resource optimization, and data-driven decision-making. This study examines how participation in the digital economy affects the agricultural management scale of high-quality farmers in Jiangxi Province, China. Based on survey data from 868 farmers collected in 2022, we apply Ordinary Least Squares regression models, instrumental variable approaches, and mediation analysis to identify the mechanisms at work. The findings indicate that digital economy participation significantly expands agricultural management scale by promoting land transfer-in and elevating farmers’ subjective social status. Further heterogeneity analysis shows that the positive impact is more pronounced among older farmers and those not intending to pursue further education. These insights highlight the essential role of digital tools in fostering sustainable and scalable farming practices and offer practical implications for rural digital transformation strategies.

The key to rural revitalization lies in talent revitalization. Cultivating a workforce that understands agriculture, loves rural areas, and cares for farmers, while retaining talent in rural regions, is of greater significance for comprehensively advancing rural revitalization. From the perspective of farm household part-time farming, this study takes the One Village, One University Student program as an example. Using survey data from 2552 farm households across 12 counties (cities and districts) in Jiangxi Province, China, and employing the ESR model, this study empirically analyzes the impact of rural revitalization talent cultivation on farm household part-time farming. It further explores the differentiated effects of various educational levels and learning modes of talent cultivation on the part-time farming. The results show that rural revitalization talent cultivation significantly reduces the degree of part-time farming, with higher-level education and correspondence education having particularly pronounced effects in enhancing agricultural skills and production efficiency. Based on these findings, this paper proposes policy recommendations to intensify rural revitalization talent cultivation, improve the educational levels and content, optimize educational modes, and strengthen the policy advocacy, aiming to further promote rural economic development and increase farmers’ income.

Rural revitalization cannot be achieved without effective governance. Using the Oprobit model, instrumental variables, moderating-effects model and mediating-effects model, this study investigated the impact of participation in rural digital governance on high-quality grassroots political trust and its mechanism using micro-survey data from 899 high-quality farmers in Jiangxi Province. This study demonstrated that participation in rural digital governance significantly enhances grassroots political trust among high-quality farmers, and both robustness and endogeneity tests yielded consistent conclusions. Further analysis revealed that organizational membership and human expenditure play positive and negative moderating roles, respectively, in the impact of participation in rural digital governance on grassroots political trust among high-quality farmers, and that there are differences in the identity of rural elites in the facilitating effect of participation. Mechanism analysis revealed that participation in rural digital governance promotes grassroots political trust among high-quality farmers by enhancing their subjective social status, and its effect accounts for 11.8% of the total effects. Accordingly, policy recommendations should be made to increase the promotion of rural digital governance, strengthen farmers’ participation and supervision, enhance transparency and effectiveness, support the membership of high-quality farmers’ organizations, reduce the burden of favors and promote overall trust.

Using the One Village, One University Student (OVOUS) project as an example and drawing on survey data from 2,552 farmers in 12 counties (county-level cities/districts) in Jiangxi Province, China, this study employs an endogenous switching probit (ESP) model to empirically examine whether participation in rural revitalization talent-training programs enhances farmers’ social capital. The results show that: (1) participation significantly increases farmers’ bonding social capital by 6.8 percentage points (ATT = 0.068, SE = 0.002), suggesting that systematic education not only strengthens individual capabilities but also facilitates the expansion of social networks; (2) correspondence education yields a stronger social-capital-promoting effect than distance education, with estimated effects of 8.1 and 5.8 percentage points, respectively, highlighting the potential role of face-to-face interaction and repeated social engagement in enhancing farmers’ bonding social capital; and (3) older farmers experience slightly larger gains in bonding social capital than younger farmers (10.8 versus 10.5 percentage points), and female farmers experience substantially larger gains than male farmers (12.8 versus 5.1 percentage points), indicating stronger marginal returns among groups with relatively weaker social networks. Overall, the findings reveal that rural talent policies generate important spillover value by fostering social capital accumulation. This implies that future policy design should jointly consider the dual effects on human capital and social capital and, in light of group heterogeneity, improve the matching mechanisms between training modalities and target participants to enhance policy precision and overall effectiveness.