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. Heterogeneity analysis indicates that the impact of digital technology on reducing pesticide and fertilizer usage varies across regions: while its adoption leads to significant reductions in Henan and Shandong, the positive effects in Xinjiang remain statistically insignificant. Mechanism analysis shows that digital technology enhances FGPT by reducing information asymmetry, improving market access, and enhancing precision management practices. Based on these findings, this study recommends expanding awareness campaigns to accelerate the adoption of digital technology, enhancing digital infrastructure to bridge the urban–rural digital divide, and optimizing digital technology promotion systems. These actions can be taken alongside the implementation of economic incentives and compensation mechanisms. The insights and policy recommendations from this research provide valuable guidance for China and other countries seeking to leverage digital technology for sustainable agricultural development.

Digital inclusive finance (DIF) is regarded as a key instrument in poverty alleviation efforts. However, existing research reveals significant gaps in understanding its poverty-reduction impact: the debate on its inclusivity remains unresolved, its mechanisms of action are unclear, and the psychological empowerment dimension has been largely overlooked. Using micro-level data from seven waves of the China Family Panel Studies (CFPS) from 2010 to 2022, this study employs fixed-effect models, quantile regression models, and mechanism analysis to explore the differentiated impact of digital inclusive finance on rural multidimensional relative poverty and the mechanisms at play. The empirical findings reveal that DIF significantly mitigates multidimensional relative poverty, with more pronounced marginal effects among the poorest households, confirming its pro-poor characteristics. Heterogeneity analysis reveals that, at the regional level, DIF has greater impacts in western regions and remote rural areas farther from county centers; at the individual level, it is particularly effective for women, those with lower education, and individuals with limited digital literacy. Mechanism analysis shows that DIF operates through three channels: promoting employment, encouraging entrepreneurship, and enhancing financial accessibility. Moreover, extended analysis demonstrates that DIF also fosters the endogenous motivation of rural households to escape poverty, as reflected in heightened confidence about the future, increased belief in social mobility and returns of work, and reduced perceived barriers to employment. These findings provide new micro-level evidence to unpack the poverty-alleviation potential of DIF.