The slowdown in income not only hinders the sustainable development of farmers but also exacerbates ecological and environmental problems. Likewise, the digital economy model represented by e-commerce has become a key path for growing farmers’ income. This article is based on 2020 China Rural Revitalization Survey data and uses the OLS and mediation effect models to examine the impact and mechanism of e-commerce operations on farmers’ income. The research results indicate that e-commerce operations can significantly improve the income level of farmers. After robustness and endogeneity tests, this conclusion still holds. The mechanism analysis results indicate that e-commerce operations promote farmers’ income growth by enhancing information acquisition, reducing operating costs, and enhancing financial support. The results of the heterogeneity analysis indicate that the impact of e-commerce on farmers’ income is heterogeneous in terms of income structure, education level, and regional distribution. Specifically, e-commerce significantly increases farmers’ agricultural operating income, non-agricultural operating income, and transfer income but significantly reduces their wage income. At the same time, e-commerce has a more significant income-increasing effect on highly educated and central and western farmers. Therefore, in promoting the development of a rural digital economy, it is necessary to improve the supporting facilities of e-commerce in rural areas; strengthen the supply of information, technology, capital, talent, and other elements; continue to improve the inclusiveness of rural e-commerce; and promote the sustainable growth of farmers’ income. The above findings not only provide new channels and ideas for farmers to increase income through e-commerce operations, but also help relevant decision-making departments to formulate new policies to promote farmers’ income growth and the development of e-commerce in China.

Introduction: The increasing frequency of extreme weather events has posed significant challenges to global food security. While it is well established that such events can reduce food production, the specific effects of different types of extreme weather on food security, as well as the heterogeneous mitigation strategies available, remain inadequately understood.Methods: This paper systematically analyzes the impacts of extreme high and low temperature events on maize yields using panel data from major maize-producing regions in China from 2000 to 2023, highlighting the potential threats climate extremes pose to food security.Results and discussion: The findings reveal that: (1) extreme high temperatures significantly suppress maize yields, with the number of extreme heat days showing a consistent negative effect nationwide and across regional and growth-stage subsamples, particularly pronounced in northern summer maize-producing areas, indicating heat stress as a key constraint on stable grain production and supply; (2) the effects of extreme low temperatures exhibit clear regional heterogeneity, with southern spring-sown maize more vulnerable to late frosts during seedling and nodulation stages, resulting in greater yield losses, whereas in northern regions, low temperatures mostly occur before sowing and have a limited impact; (3) the adverse effects of extreme temperatures have intensified over time, with extreme heat impacts worsening in recent years—reflecting cumulative climate risks and agricultural system vulnerability—while the negative impacts of low temperatures have somewhat diminished since 2010, indicating improved farmer adaptation; (4) agricultural insurance and protected agriculture have significantly mitigated the impacts of extreme low temperatures on maize yields, demonstrating their effectiveness in cold climates, but have yet to provide significant buffering against yield losses from extreme heat, suggesting opportunities to optimize existing insurance mechanisms and protective agricultural technologies. These findings contribute to a deeper understanding of climate adaptation strategies and support the achievement of SDGs 2 (Zero Hunger) and 13 (Climate Action) through enhancing resilience in the agri-food system.

Sustainable development is crucial for alleviating poverty among farmers. In this study, we examined the impact, and the mechanism underlying this impact, of the adoption of agricultural machinery services by farmers on their relative poverty from a multidimensional poverty perspective by employing the logit and ordered logit models and the Karlson-Holm-Breen (KHB) method. These results indicate that adopting agricultural machinery services can significantly reduce the probability of relative poverty among farmers, thereby expediting the sustainability of rural development. However, this poverty-reduction effect varies based on age and sex. The adoption of agricultural machinery services mainly reduces poverty by increasing farmers' human capital. Training in employment skills and non-agricultural work experience are the main transmission mechanisms. Therefore, the socialization of agricultural machinery services can be used as an effective policy tool to reduce relative poverty in developing countries, promote sustained improvements in farmers' incomes, and achieve sustainability in rural development.

Introduction: The impact of farm machinery outsourcing services (FMOS) on grain production has been extensively studied in the literature. However, whether FMOS would adjust cropping structures and ensure food security is little known. To address this research gap, we analyzed the impact of FMOS on the cropping structure adjustment and grain production of farmers.Methods: We estimate the impact of FMOS on grain production by using data collected from a survey of 3,863 wheat farmers in China. We employ the Extended Regression Model (ERM) to address selectivity bias.Results and discussion: The empirical results show that FMOS can adjust the cropping structure and increase the proportion of household food cultivation. Among all segments of FMOS, fertilizer application services drive the increase in grain acreage more significantly. We also find that large-scale households prefer to self-purchase farm machinery rather than FMOS, leading to an insignificant impact of FMOS on cropping structure. Therefore, in the process of promoting the development of FMOS, we should focus on the coordinated development of various types of FMOS, strengthen the popularization and application of fertilization services, and formulate a differentiated subsidy policy for heterogeneous farmers in terms of scale to better play the role of agricultural machinery in promoting grain production.

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.

Introduction: Farmers’ own risk attitudes are important for e-commerce operations and digital transformation of rural economy. Methods: Based on the 3,670 farmers data of China Rural Revitalization Survey, using binary logit model and mediation effect model, this paper discusses the impact of risk preference on farmers’ e-commerce operations and its mechanism, and examines the heterogeneous impact of road condition, network outlet construction and regional distribution. Building on this analysis, it further discusses differences in the impact across operation scales, operation models, technology utilizations and product types. Results and discussion: The results indicate that risk preference significantly increases the likelihood of farmers’ participation in e-commerce operations, and this finding remains robust after both robustness and endogeneity tests. Mechanism analysis reveals that risk preference promotes e-commerce operations through both formal and informal lending channels. Heterogeneity analysis shows that the effect is stronger for farmers with favorable road condition, well-developed network outlet, and in the central and western regions. Further analysis demonstrates that the promoting effect of risk preference is particularly pronounced for large-scale e-commerce, social e-commerce, and live-streaming e-commerce, and is especially strong in transactions involving primary processed products. The findings suggest the need to establish a hierarchical support mechanism that accommodates differences in farmers’ risk preference, while simultaneously advancing innovations in rural financial services and strengthening the development of e-commerce infrastructure. In addition, differentiated guidance should be provided to foster innovative e-commerce models and to optimize the overall e-commerce ecosystem, thereby unlocking the full development potential of rural e-commerce and contributing to sustainable rural revitalization.