Unveiling the Mechanisms of Digital Technology in Driving Farmers' Green Production Transformation: Evidence from China's Watermelon and Muskmelon Sector.

Leveraging the transformative potential of digital technologies to support the farmers' green production transformation (FGPT) is a critical catalyst for facilitating the accelerated green transformation and upgrading of agricultural systems, thereby achieving high-quality agricultural development. Using survey data from major watermelon- and muskmelon-producing regions in Henan, Shandong, and Xinjiang, and employing Ordinary Least Squares (OLS), Propensity Score Matching (PSM), and the Logit model, this study examines the mechanisms through which digital technology influences FGPT. The findings reveal that the adoption of digital technology significantly reduces farmers' use of pesticides and fertilizers, with a particularly pronounced effect on pesticide reduction.

Internal Drive or External Pull: Independent Innovation and Sustainable Growth of Chinese Agricultural Enterprises.

The independent innovation of agricultural enterprises ensures national food security through enhancing food production efficiency and optimizing food nutritional quality. Independent innovation is an important way for the sustainable growth of agricultural enterprises. However, in this process, there are issues such as long cycles and high risks.

Does digital economy keep enterprises out of green innovation trouble? evidence from "double carbon" goal.

The proposal of the "dual carbon" targets has provided direction for promoting China's economic green transformation and green innovation. As enterprises are important entities driving technological innovation in China, enhancing their green innovation capabilities holds significant practical significance for reducing carbon emissions. While the flourishing development of the digital economy currently provides new avenues and impetus for enterprise green innovation, research on the micro-level effects of green innovation driven by digital economy is still lacking.

Threshold effects of green technology application on sustainable grain production: Evidence from China.

Sustainable production is considered as an important approach to solve the dilemma of food insecurity. Green technologies have made contributions to improving food production and reducing environmental pollution. Studying the effects of green technologies on sustainable food production has great significance.

Study on the Spatiotemporal Evolution and Influencing Factors of Agricultural Carbon Emissions in the Counties of Zhejiang Province.

The accurate measurement of agricultural carbon emissions and the analysis of the key influential factors and spatial effects are the premise of the rational formulation of agricultural emission reduction policies and the promotion of the regional coordinated governance of reductions in agricultural carbon emissions. In this paper, a spatial autocorrelation model and spatial Dubin model are used to explore the spatiotemporal characteristics, influential factors and spatial effects of agricultural carbon emissions (ACEs). The results show that (1) From 2014 to 2019, the overall carbon emissions of Zhejiang Province showed a downward trend, while the agricultural carbon emission density showed an upward trend.

Can the Adjustment of China's Grain Purchase and Storage Policy Improve Its Green Productivity?

While the sustainability of grain production has been extensively studied, there have been few studies focusing on the impact of grain policy adjustment on its sustainable production, and the quantitative relationship between these two aspects and the internal mechanism is not completely clear. The main objective of this paper was to explore the impact of grain purchase and storage policy (GPSP) adjustment on its green productivity by expounding the evolution logic and influence mechanism of GPSP. Therefore, taking maize production as an example, this paper constructs the analysis framework of the evolution logic and influence mechanism, and the super-epsilon-based measure model (Super-EBM) is adopted to measure maize green productivity (MGP) in main producing areas from 1997 to 2019, then two groups of difference-in-differences (DID) models are constructed to study the influence of the temporary purchase and storage policy (TPSP) and the producer subsidy policy (PSP) on MGP.