As a crucial pillar for rural revitalization and carbon neutrality strategies, the role of digital technology (DT) in agricultural low-carbon transition (ALCT) has become increasingly prominent. Based on panel data from 30 Chinese provinces spanning 2010–2024, this study constructs an ALCT evaluation framework from dual perspectives of carbon sequestration and carbon emissions, employs two-way fixed effects models and double machine learning (DML) methods to systematically assess the impact of DT on ALCT, and explores the underlying mechanisms through two dimensions: land transfer (LT) and industrial integration (II). The results show that: (1) DT significantly promotes ALCT, and this conclusion remains stable across multiple robustness tests including alternative calculation methods, variable substitutions, policy interference exclusion, and instrumental variable approaches. (2) Mechanism analysis reveals that DT indirectly drives ALCT through two pathways-facilitating LT and promoting II-verifying the partial mediating roles of both mechanisms. (3) Heterogeneity analysis demonstrates that DT significantly promotes ALCT in both major grain-producing areas and non-major grain-producing areas, with the promotional effect being notably stronger in non-major grain-producing regions. These findings provide empirical evidence for DT empowerment in agricultural green development and offer important references for formulating differentiated low-carbon agricultural policies.
Li et al. (Tue,) studied this question.