目的/意义 运用数字技术提升粮食生产韧性对保障粮食安全、构建现代化农业保障体系具有重要意义。本研究旨在探究数字技术对粮食生产韧性的影响效应、内在机制及异质性特征，为数字技术赋能粮食生产韧性提升提供参考。 方法 采用2011—2023年中国30个省份的面板数据，采用熵值法构建粮食生产韧性综合评价指标体系并测算其水平。选取支持向量机作为基学习器的双重机器学习模型识别数字技术对粮食生产韧性的因果影响。运用中介效应模型验证数字技术通过“人-地-服”三条机制路径实现要素重组的驱动作用。通过异质性检验，分析粮食产区、地形起伏度及经济发展水平对该赋能效应的调节差异。 结果和讨论 数字技术显著促进了粮食生产韧性提升，且在不同细化维度呈现结构性差异。数字技术显著增强了调节适应力与转型创新力，但受技术依赖与资本挤占效应影响，对风险抵抗力表现出负向影响。机制分析表明，数字技术通过“人-地-服”三条路径实现要素重组，即促进劳动力非农转移带来的资本回流、降低交易成本推动的土地规模经营，以及发挥技术创新集成作用的农业生产性服务。异质性分析发现，该赋能效应在地形起伏度较高、经济发展水平较低及粮食产销平衡区与主销区更为显著。 结论 应促进数字技术集成以打通全产业链数据链；创新“数字反哺”横向补偿机制以弥补省际数字鸿沟；培育数字化新型农业社会化服务体系，并因地制宜提升自然条件劣势地区的数字化短板，从而多路径提升粮食生产韧性。

Objective Leveraging digital technology to enhance grain production resilience is pivotal for ensuring food security and constructing a modernized agricultural support system. The purposes of this study are: (1) Define the connotation of grain production resilience and construct an evaluation index system across three dimensions—risk resistance, regulatory adaptability, and transformative innovation; (2) Identify the impact and mechanisms of digital technology as a new production factor on grain production resilience; (3) Reveal how digital technology influences resilience through the reorganization of "People-Land-Service" factors; (4) Analyze the heterogeneity of these effects across diverse geographical environments and economic endowments. Methods Based on panel data from 30 Chinese provinces spanning 2011 to 2023, this research conducted a rigorous empirical analysis. First, the entropy method was employed to measure the levels of digital technology and grain production resilience. Second, a dual machine learning model, utilizing Support Vector Machines as base learners with 5-fold cross-validation and double residualization, was constructed for causal inference to address the "curse of dimensionality" and specification biases inherent in traditional linear models. To ensure robustness, an Instrumental Variable approach was applied, using the product of the number of fixed-line telephones in 1984 and the national internet users of the previous year. Third, a mediation effect model was introduced to test three pathways: non-farm labor transfer, large-scale land management, and agricultural productive services. Results and Discussions Mechanism analysis indicated: (1) In the "People" dimension, digital technology promoted non-farm labor transfer by reducing information search costs, thereby inducing capital reflux to alleviate financial constraints; (2) In the "Land" dimension, digital platforms lower transaction costs for land transfer, facilitating contiguous large-scale farming and improving the marginal efficiency of digital equipment; (3) In the "Service" dimension, digital technology empowered agricultural service organizations, enhancing resilience through technology diffusion and professional intervention. Heterogeneity analysis showed that the empowerment effect was more pronounced in grain production-marketing balanced zones, high-relief terrains, and economically underdeveloped regions. This highlighted the "gap-filling" nature of digital technology, where precision tools like drones and remote sensing compensated for the limitations of traditional machinery in complex terrains. Notably, while digital technology significantly drived overall resilience, it primarily bolsterd regulatory adaptability and transformative innovation while exerting a significant negative impact on initial risk resistance. Conclusions Digital technology was not a mere superposition of factors; rather, it catalyzes a fundamental transformation in the dynamics of grain production through the systemic restructuring of elements. To this end, differentiated strategies should be implemented: Major grain-producing areas should prioritize full-chain data integration, whereas production-marketing balanced zones and ecologically disadvantaged regions should focus on overcoming digital infrastructure bottlenecks. Furthermore, a horizontal "digital feedback" compensation mechanism should be innovated, encouraging major consumption areas to shift from "blood transfusion" (passive aid) to "blood-making" (capacity building) through technology licensing and targeted talent support. Finally, a new system of digitalized agricultural social services should be cultivated, leveraging the scale effects of digital platforms to effectively bridge the gap between smallholder farmers and modern agriculture.