Under the context of promoting comprehensive rural revitalization, digital inclusive finance, with its low threshold, wide coverage, and high efficiency, has become a core driving force to break through the spatiotemporal limitations of traditional finance, solve the financial exclusion of farmers, stimulate farmers′ enthusiasm for entrepreneurship and employment, and increase farmers′ income. Based on the provincial panel data of 31 provinces, autonomous regions, and municipalities （directly under the central government）in China（excluding Hong Kong, Macao and Taiwan）from 2014 to 2023, this paper constructed a spatial econometric model and a threshold effect model to empirically test the spatial spillover effect and threshold effect of digital inclusive finance on farmers′ income growth. The results showed that: digital inclusive finance significantly promoted local farmers′ income growth, and this effect was mainly reflected through the dimension of the coverage breadth of digital inclusive finance. However, due to the siphoning effect, it had a negative spatial spillover effect on the income of farmers in neighboring areas. The robustness test, conducted by winsorizing the variables at the 5% level on both sides, also strengthened the above conclusion. Further research revealed a significant nonlinear relationship between digital inclusive finance and farmers′ income growth. By treating digital inclusive finance as the threshold variable and constructing a double-threshold model, it was found that the impact of digital inclusive finance on farmers′ income growth showed a nonlinear trend of increasing marginal effect. Based on the research results, the article proposed suggestions and countermeasures to promote farmers′ income growth from the perspectives of improving digital infrastructure construction, innovating financial products and services suitable for agricultural production scenarios and farmers′ needs, enhancing farmers′ digital financial literacy, and strengthening government supervision and coordination.

Continuously promoting the development of the new quality rural productive forces is an important pathway to enhance grain supply chain resilience. Based on panel data from 31 provinces, autonomous regions, and municipalities （directly under the central government） in China （excluding Hong Kong, Macao, and Taiwan） from 2014 to 2023, this study quantified grain supply chain resilience using the longitudinal and horizontal scatter degree method, analyzed its spatiotemporal differentiation and regional disparities through Kernel density estimation, traditional and spatial Markov chains, and the Dagum Gini coefficient. Compared seven types of machine learning models, the optimal SVR model was selected and integrated with the SHAP interpreter to reveal the driving effects of the new quality rural productive forces on grain supply chain resilience. The results indicated that: China′s grain supply chain resilience increased year by year, consistently maintaining the pattern of main grain production areas > production-marketing balance areas > main grain consumption areas. The spatial distribution showed a trend of "expansion in the middle levels and reduction at both ends". Regional disparities narrowed annually, but multipolarization persisted. The contribution rate of inter-group differences fluctuated upward and became the main source of disparities in grain supply chain resilience. The output value of agriculture, forestry, animal husbandry, and fishery services, urbanization rate, and agricultural carbon emissions exhibited positive driving effects, while the situation of agricultural labor mobility showed a negative inhibitory effect, and the contribution rates of other driving factors were relatively low.Interactions among driving factors also significantly impacted grain supply chain resilience. Accordingly, regional differentiated precision enhancement strategies should be implemented, and a support system for grain supply chain resilience should be constructed to promote overall resilience through the advancement of the new quality rural productive forces.

Agricultural supply-side structural reform is a key measure and inevitable path for promoting the sustainable and healthy development of agriculture in the new era. Based on the panel data of 30 provinces, autonomous regions, and municipalities（directly under the central government）in China（excluding Tibet Autonomous Region, Hong Kong, Macao, and Taiwan regions）from 2010 to 2023, this study adopted the improved CRITIC-entropy weight method, Dagum Gini coefficient decomposition method, and obstacle degree model to quantitatively evaluate the effect of agricultural supply-side structural reform, analyzed the spatial differences and their sources, and identified the main obstacle factors. The results showed that: from 2010 to 2023, the overall effect of China′s agricultural supply-side structural reform presented a fluctuating upward trend, showing a regional growth pattern of "the central and western regions leading the growth while the eastern region lagging behind". The spatial distribution of the reform level was continuously optimized, with the number of provinces at a low level substantially reduced, provinces at a medium level slightly increased, and provinces at a high level remarkably increased; . The overall spatial difference in the reform effect showed a continuous narrowing trend, with the difference mainly derived from super variable density, followed by intra-regional differences, and finally inter-regional differences. The intra-regional differences in the eastern and western regions decreased, while the intra-regional differences in the central region showed an expanding trend, the inter-regional differences between the eastern and western regions decreased significantly, while the inter-regional differences between the eastern and central regions increased. The reform effect faced common constraints across regions, and the coverage depth of agricultural insurance, per capita output of commercial crops, and agricultural credit level were the three core obstacle factors affecting the improvement of the reform effect. Accordingly, it is suggested to continue deepening the agricultural supply side structural reform, strengthen agricultural insurance and credit services, optimize the agricultural production layout, and coordinate the safeguarding of food security and enhance the value of characteristic industries.

After the victory of the poverty alleviation campaign, China has entered a critical period of consolidating poverty alleviation achievements and comprehensively advancing rural revitalization, where consumption-driven poverty alleviation has become an important path to prevent rural poverty recurrence. This study supplemented the micro-behavioral perspective in consumption-driven poverty alleviation research, taking college students as the research object, integrated consumer behavior theory, social responsibility theory, and information-intervention theory to build a multi-dimensional analytical framework. By using a mixed Logit model and latent class analysis, the study systematically measured college students′ attribute preferences, marginal willingness to pay for poverty-alleviation agricultural products（blueberries from Majiang County, Guizhou Province）, and the moderating effects of information intervention. The results showed that: the poverty-alleviation attribute had the highest marginal utility for purchase decisions, and its impact was significantly higher than that of brand attribute and quality attribute, confirming that college students′ decision-making had the dual logic of rational economic demands and social responsibility motivation. Consumers′ preferences showed significant heterogeneity, which could be divided into self-interest-oriented groups and altruism-brand-oriented groups. Information intervention had a significant positive direct impact on college students′ purchase, and enhanced college students′ value recognition of the poverty-alleviation attribute and perceived trust in the quality attribute through the moderating effect, with this effect showing differentiated characteristics among groups of different genders and consumption levels. Accordingly, it is suggested to focus on college students, release their consumption potential through the construction of a university-based consumption-driven poverty alleviation promotion system, differentiated agricultural product designs, and precise information dissemination. Promoting the transformation of consumption-driven poverty alleviation towards an endogenous and voluntary model, so as to provide sustainable impetus for consolidating poverty alleviation achievements and advancing rural revitalization.

Rooted in the context of rural revitalization and common prosperity, agriculture essentially aims to "boost incomes" and "increase grain production", the former needs to solve the problem of income inequality, the latter relies on the fundamental strategy of "storing grain in the land" which implemented through the construction of high-standard farmland. Based on micro-survey data collected from 1 032 farm households across 10 provinces, autonomous regions, and municipalities（directly under the central government）in China, the study empirically analyzed the impact pathways and mechanisms of high-standard farmland construction on income inequality among farm households. The results indicated that: both the implementation of high-standard farmland construction and the expansion of its scale could effectively alleviate income inequality among farmers, and these findings remained significant in robustness tests with alternative dependent variables and these findings remain significant in robustness tests with alternative dependent variables,removal of extreme values ,and employment of alternative estimation models. The mechanism analysis revealed that the high-standard farmland construction significantly narrowed the income gap among farm households by improving the level of agricultural socialized services, while the expansion of high-standard farmland construction alleviated income inequality by accelerating land transfer. The heterogeneity analysis showed that, compared with the clan-elite co-governance type households, the high-standard farmland construction more effectively reduced income inequality among village-governance-dependent and administrative-governance-dependent households. Additionally, compared to part-time farmers, high-standard farmland construction had a more significant mitigating effect on income inequality among full-time farmers. Therefore, it is essential to promote the coordinated development of high-standard farmland construction and the rural common prosperity strategy, improve agricultural socialized services, and guide orderly land transfer to develop appropriately scaled-up agricultural operations. Simultaneously, attention should be paid to the heterogeneity across the dual dimensions of village governance types and household operation types in high-standard farmland construction, thereby ensuring its sustained and steady development and effectively alleviating income inequality among farm households.

Faced with the new round of technological revolution and industrial transformation, developing the new quality rural productive forces is of great significance for realizing comprehensive rural revitalization and building a strong agricultural country. This paper used the entropy weight method, Dagum Gini coefficient and Kernel density estimation method to measure and examine the development level, regional disparity and evolution trend of the new quality rural productive forces in 31 provinces, autonomous regions, and municipalities（directly under the central government）in China（excluding Hong Kong, Macao and Taiwan regions）from 2012 to 2023. The results showed that: during the research period, the overall development level of the new quality rural productive forces in China presented a trend of rising first and then declining, but the overall level remained relatively low, and showed a pattern of Eastern China>Western China>Central China>Northeast China. There were obvious regional disparities in the development level of the new quality rural productive forces, which mainly came from inter-regional disparity, and the inter-regional disparity between Eastern China and Northeast China was the most significant. The results of Kernel density estimation indicated that the kernel density curve of China′s new quality rural productive forces development level showed a uni-modal shape, the peak value presented a trend of first decreasing and then increasing, and the polarization phenomenon had intensified. The kernel density curves of Eastern, Central and Western China showed a trend of weakening divergence, while the kernel density curve of Northeast China showed the characteristics of unstable polarization. Based on this, the paper put forward suggestions such as implementing regional coordinated development strategies and formulating differentiated regional agricultural development plans. Cultivating high-quality agricultural labor force and building a high-quality team of agricultural workers. Promoting agricultural scientific and technological innovation and accelerating the deployment of digital agricultural infrastructure.

Digital transformation is an important path for agricultural enterprises to improve the quality of development, and its also an inevitable choice for advancing agricultural modernization. Based on the data of A-share listed companies from 2007 to 2024, this paper employed the ordinary least squares method and panel fixed-effect model to analyze the impact of digital transformation on the high-quality development of agricultural enterprises, and tested the mechanism of action through the mediating effect model. The results showed that: digital transformation had a significant positive impact on the high-quality development of agricultural enterprises, and R&D investment played a mediating role, that meant digital transformation could drive the high-quality development of agricultural enterprises by increasing R&D investment. Heterogeneity analysis showed that the digital transformation exhibited more significant positive enabling effect for agricultural enterprises with diversified operations, high financing constraints and those located in the eastern region. Accordingly, agricultural enterprises need to increase resource investment to unlock the value of digital technology, financial institutions need to provide diversified financial services to alleviate the financing difficulties of enterprises, government needs to develop digital technology according depend on local conditions to maximize its benefits, in order to provide a reference for agricultural enterprises to enhance their core competitiveness and build a modern agricultural operation system.

Promoting the green development of family farms is a core driver for agricultural modernization, ecological-economic coordination, comprehensive rural revitalization and building a strong agricultural country. Based on micro-survey data of 539 grain-growing family farms in Sichuan Province, this study systematically explored the impact of digital literacy on the adoption of green production technologies and the underlying mechanisms by using Oprobit model, mediating effect model, and moderating effect model. The results showed that: digital literacy had a significant positive impact on the adoption of green production technologies by grain-growing family farms, and this effect exhibited technological heterogeneity with a more prominent promoting role in pesticide and chemical fertilizer reduction, and organic fertilizer and farm manure application. The impact was mediated through three mediating channels: enhancing green value perception, improving agricultural product premium returns, and promoting the use of digital technologies, and social networks played a positive moderating role in the above relationship, and there existed a mediated moderation effect. Heterogeneity analysis indicated that the promoting effect of digital literacy was more significant among family farms with higher-educated and large planting scales. Accordingly, it wis suggested to establish a hierarchical and classified digital literacy training system to implement differentiated training for farm operators of different scales and educational backgrounds, complement it with financial support and green premium acquisition mechanisms to precisely empower the green transformation of grain-growing family farms.