The digital development in rural areas has become an important driving force for promoting green production in agriculture. But the lack of digital skills among farmers remains a problem. The main reason why farmers cannot master digital skills well is their lack of digital literacy, which leads to market information asymmetry and the inability to truly distinguish the difference between green production and traditional production. Based on this, this article uses field research methods to collect data from 1,116 farmers in China, calculates agricultural green production efficiency using the SBM model, and empirically tests the relationship between farmers’ digital literacy and green production efficiency in agriculture. The results showed that digital literacy has a significant promoting effect on agricultural green production efficiency. Secondly, it was found that digital literacy can effectively enhance farmers’ cognition of green agricultural products and green production technology adoption. Among them, the effect of cognition of green agricultural products is reflected in farmers’ self-cognition and market cognition. The green production technology adoption is reflected in the breadth and depth of technology adoption. Third, we discuss the effect of different dimensions of digital literacy on agricultural green production efficiency. The effect of the digital literacy on the production efficiency of the five typical green technologies used by farmers is further discussed. Although there are certain differences, overall, they all have a significant promoting effect. It is necessary to comprehensively improve farmers’ digital literacy, bridge the digital divide and promote the green transformation of agricultural production.

The development of rural digitalization has become a key driving force for promoting green agricultural production. However, in practical operations, due to the insufficient digital skills and lack of necessary digital human capital among farmers, they struggle to distinguish between green production methods and traditional practices, which in turn reduces their willingness to adopt green production. This study employed empirical research methods to collect data from 854 farmers in China’s largest grain-producing region and used the Probit model to analyze the impact of digital human capital on farmers’ willingness to engage in green production. The results indicate that an increase in digital human capital can significantly enhance farmers’ willingness to engage in green production. Additionally, it was found that online learning can enhance farmers’ willingness towards green production, with informal online learning proving more effective. Further analysis revealed that social networks play a mediating role between digital human capital and farmers’ willingness to engage in green production. The study also explored the heterogeneous impact of digital human capital on different groups of farmers, highlighting that increases in digital human capital have a more pronounced effect on the willingness of small-scale farmers and middle-aged farmers to engage in green production. Therefore, continuously enhancing digital human capital, emphasizing diverse learning channels, and leveraging ’acquaintance networks’ to encourage farmers to improve their awareness of green production through digital platforms are critical for promoting sustainable green agriculture in developing countries.

The pivotal measure for reducing pollution and facilitating green and sustainable agriculture lies in the application of biopesticides to replace chemical pesticides. The argument still rests on whether the use of the Internet can assist farmers in selecting biopesticides or not. In light of 532 microscopic research datapoints from the largest rice-producing province in China, the Probit model was applied in this article to probe the influencing factors regarding the use of the Internet on their selection of the biopesticides by farmers, and the TAM-PR model was also adopted to explore its intrinsic mechanisms. According to the research findings, the use of the Internet directly contributed to the application of biopesticides, which can affect farmers’ decisions regarding biopesticides by means of perceived usefulness and perceived ease of use in an indirect manner, and the mediating effect was 19.74% and 20.98%, respectively. The result regarding perceived risk was not significant. The use of the Internet has a remarkable effect on farmers with high incomes and large-scale operations, while it has an insignificant effect on farmers with low incomes and individual operations. It has a remarkable positive effect on farmers with high academic qualifications compared with those with low academic qualifications. Furthermore, personal, household-based production and village and green cognitive characteristics also have a significant influence on the application of biopesticides. Hence, it is of great significance to continuously facilitate the application of rural Internet usage, encourage environmentally friendly modes of production, and reduce agricultural pollution.

Fertilizers play a crucial role in increasing grain yields and ensuring agricultural supply. However, heavy reliance on fertilizers has brought growing pressure on food security and environmental sustainability. Soil improvement technologies provide an effective way to reduce fertilizer use while maintaining agricultural productivity. This paper uses survey data from 808 farmers in China’s major grain-producing regions. It examines the effects of single and combined soil improvement technologies on fertilizer application intensity. Based on farmers’ capabilities, cognition, and production behaviors, this study further explores the moderating roles of digital literacy, psychological expectation, and continuous technology adoption. The results show that technology combinations have a stronger inhibitory effect on fertilizer reduction than a single technology. Digital literacy and continuous technology adoption strengthen this mitigation effect, while psychological expectations weaken it. The fertilizer-reduction effect is more evident in larger farms, non-transferred land, and farms with higher levels of mechanization. Future agricultural policies should place more emphasis on the popularization of technology combinations, such as through targeted subsidies and special supporting funds. At the same time, differentiated support measures should be formulated in light of local conditions to curb excessive fertilizer application and promote the sustainable development of agriculture.