As a comprehensive technology with social, economic, and ecological benefits, integrated pest management (IPM) is crucial in fundamentally alleviating the environmental pollution caused by traditional high-input agriculture. Based on the random-sampled data of 981 farmer households in major Indica-rice-producing areas in Anhui Province, this study analyzes the impact of agricultural production knowledge on farmers’ willingness to adopt IPM technology through logit models, considering integrated knowledge and categorized knowledge. The results indicate that integrated agricultural production knowledge significantly increases farmers’ willingness to adopt IPM technology. However, pest-management knowledge was the only one out of four specific disciplines that significantly individually affect farmers’ adoption intention. The more knowledge farmers acquire about pest management, the higher intention they have to adopt IPM. Some demographic and household characteristics also significantly influence their willingness. Based on these results, we suggest that increasing farmers’ agricultural production knowledge, especially knowledge about pest management, is essential in promoting IPM technology. Besides this, IPM technology should be promoted purposely and consciously, combined with farmers’ individual and family characteristics.

Traditional farming practice of rice field co-culture is a time-tested example of sustainable agriculture, which increases food productivity of arable land with few adverse environmental impacts. However, the small-scale farming practice needs to be adjusted for modern agricultural production. Screening of rice field co-culture farming models is important in deciding the suitable model for industry-wide promotion. In this study, we aim to find the optimal rice field co-culture farming models for large-scale application, based on the notion of food productivity. We used experimental data from the Jiangsu Province of China and applied food-equivalent unit and arable-land-equivalent unit methods to examine applicable protocols for large-scale promotion of rice field co-culture farming models. Results indicate that the rice-loach and rice-catfish models achieve the highest food productivity; the rice-duck model increases the rice yield, while the rice-turtle and rice-crayfish models generate extra economic profits. Simultaneously considering economic benefits, staple food security, and regional food output, we recommend the rice-duck, rice-crayfish, and rice-catfish models. Simulating provincial promotion of the above three models, we conclude that food output increases from all three recommended models, as well as the land production capacity. The rice-catfish co-culture model has the most substantial food productivity. None of the three models threatens staple food security, as they do not compete for land resources with rice cultivation.

The rapid development of the internet is affecting rural residents’ well-being profoundly in China. To empirically investigate the impacts of internet use on farmers’ subjective well-being, the latest version of the China Family Panel Studies data is utilized and multiple regression methods are employed. The results of the ordered logit model indicate that internet use positively affects farmers’ subjective well-being. Propensity score matching and endogenous switching regression are used to eliminate possible endogeneity and still reveal robust results. The frequencies of online study, online social interaction, and online entertainment are important channels influencing farmers’ subjective well-being. Furthermore, the impacts of internet use are heterogeneous. Internet users from the central and western regions have higher levels of subjective well-being than their counterparts from the eastern region. Young and middle-aged internet users are happier than the elderly ones. Therefore, the government ought to fully cover rural areas with the internet, eliminate the digital division, especially in Central and Western China, and pay more attention to internet use by the elderly.