With the rapid development of China’s rural economy, rural collective economic organizations have played a significant role in increasing farmers’ income and promoting rural revitalization. This study aims to explore the impact of farmers’ participation in skills training organized by rural collective economic organizations on their livelihood capital and the underlying mechanisms. Using tracking survey data from rural households in Chongzhou City, Sichuan Province, in 2023, the paper employs empirical analysis methods, including OLS and mediation effect analysis. The results show that participation in skills training organized by rural collective economic organizations enhances farmers’ livelihood capital. The effectiveness of public service delivery by village committees, the network role of farmers’ cooperatives, and the linkage effect of leading agricultural enterprises in driving rural development act as mediating factors. Additionally, the impact of skills training on farmers’ livelihood capital varies according to household characteristics and the attributes of the rural collective economic organizations involved. Therefore, this paper proposes the following policy recommendations: (1) Further strengthen the public service and resource allocation functions of the village committees. (2) Support and optimize the operating entities such as farmer cooperatives and leading agricultural industrialization enterprises. (3) Address the training needs of different groups and enhance the focus and support of grassroots governments for skills training in collective economic organizations.

Amid global population growth and the pressures of climate change, traditional factors in driving grain production are increasingly inadequate. In this context, this study utilizes panel data from 31 provinces in China (2001–2022) to examine the impact of digitalization (DG), technological innovation (TI), and financial innovation (FI) on grain production (GP). Specifically, the study constructs a comprehensive evaluation framework where DG is measured by mobile communication penetration, TI by agricultural R&D expenditure, and FI by the loan-to-GDP ratio of financial institutions. Employing a fixed effects model, the empirical results demonstrate that DG, TI, and FI yield significant positive returns on GP, with elasticity coefficients of 0.262, 10.675 and 6.589, respectively. Furthermore, synergistic effects are observed, where the interaction between DG and TI (coefficient 0.0402 × 10⁻³) and between DG and FI (coefficient 0.221 × 10⁻²) significantly amplify production capacity. Channel analysis reveals that DG and TI promote GP by fostering agricultural industrial agglomeration, TI and FI by advancing agricultural mechanization, and DG and FI by expanding the agricultural insurance scale. Heterogeneity analysis indicates that these factors significantly boost GP in major grain-producing regions but are insignificant in grain production–marketing balanced regions. In major grain-consuming regions, DG has an adverse effect, TI has no significant impact, and FI has a positive effect. Additionally, in non-humid regions, the positive impacts of DG, TI, and FI on GP are greater.