Reducing chemical usage, particularly chemical fertilizers, is a crucial measure for advancing sustainable agricultural development. This study utilized field survey data from 894 maize farmers across three northeastern provinces of China. A double machine learning modeling framework was established to empirically examine the impact and mechanism of agricultural socialized services on chemical fertilizer use of farm households. The model addresses numerous stringent constraints of conventional causal inference models and effectively mitigates the “curse of dimensionality” issue. Current research indicates that agricultural socialized services can substantially decrease chemical fertilizer use among farmers. Further investigation reveals that these services facilitate this reduction by enhancing the mechanization level, promoting the use of organic fertilizers, and providing a labor substitution effect. The region heterogeneity test indicates that the impact of agricultural socialized services is more pronounced in Liaoning and Heilongjiang provinces geographically. Regarding the heterogeneity analysis of food crop income levels, agricultural socialized services can decrease chemical fertilizer use among farmers more effectively with elevated food crop income levels. Consequently, the findings imply that the socialization of agricultural services has substantial potential to be an effective chemical fertilizer reduction strategy to support the agricultural green transition, which can be enhanced through promoting the degree of mechanization, organic fertilizer application, and labor division and specialization.

Reducing food loss can improve environmental sustainability, resource use, and food security. Agricultural machinery services have considerable advantages in enhancing the adaptability and competitiveness of farms, but little is known about its potential for addressing food loss. Here, this work attempts to reveal a strong yet under-discussed connection between agricultural machinery services and food loss. Using survey data covering 483 corn farmers in the Heilongjiang, Jilin, and Liaoning provinces of China from October to December 2024, this study examined the extent to which participation in agricultural machinery services reduced food loss. Our results confirmed the existence of this significant causal effect and estimated 0.864% and 0.862% reductions in weight and value losses in response to a 1% increase in the purchase of agricultural machinery services. The possible mechanisms driving this relationship, including factor allocation optimization and technology introduction, were further verified. A variety of robustness tests were conducted to validate the strength and reliability of the empirical results and address endogeneity issues. Also, to better contextualize the heterogeneous effects of agricultural machinery services on food loss, the differences across production links, land fragmentation, and service quality were explored. By highlighting the important roles of agricultural machinery services in reducing food loss, our analysis contributed to contemporary debates about the long-term linkage between the wide popularization of agricultural machinery services and achieving food security, particularly providing insights for developing countries.