Under the new situation of rapid development of information technology and increasingly diversified demands of farmers, agricultural information service is also faced with many problems, such as the traditional information service system is difficult to quickly and accurately find the information required by users in the mass information, and the universal information service form cannot meet the growing personalized needs of users. In view of the above problems, this paper explores the application of user portrait technology in agriculture. Through in-depth analysis of the purpose of drawing portrait of agricultural users, characteristics of the agricultural industry and actual needs of agricultural information service, it builds a user portrait model in the agricultural field. At the same time, the situational recommendation system of agricultural science and technology resources based on user portraits is constructed by comprehensively considering the influence of multidimensional situational factors such as the time, geographical location, categories of agricultural production and changes in users’ interests on the demand for agricultural information resources. Through practical application, the system realizes the individualized recommendation of agricultural information resources based on situational awareness and user interest adaptation, and satisfies the individualized demand of agricultural users for agricultural information better.

Beijing–Tianjin–Hebei is an important agricultural production area in China, and farmers’ agrochemical input behavior directly affects the risk of agricultural non-point source pollution and the effect of green agricultural development. Based on a questionnaire survey and field interview data, this study investigated the agrochemical input behavior of farmers in Beijing–Tianjin–Hebei, and analyzed its influencing factors. Using the Probit model, we carried out an empirical study on farmers’ willingness to invest in cleaner production of agrochemicals from four aspects: farmers’ characteristics, agricultural input, environmental awareness and technical cognition. The results showed that the kinds of fertilizer were mainly compound fertilizer, urea and organic fertilizer, and the fertilization method was mainly surface spreading, accounting for 50.6% of the total surveys; the number of agrochemicals was determined chiefly by agricultural sellers, accounting for 55.5%. The proportion of the guidance from technical departments in Beijing was higher than that of Tianjin and Hebei. The first influencing factor for farmers’ behavior towards agrochemical input was the pursuit of high yield and high profit, accounting for 24.9%, 22.6% and 26.0%, respectively. The guidance of relevant technical departments still did not fully cover the use of agrochemicals. The study also found that factors such as the price of farming materials, the price of agricultural products, family income, farmland facilities, government propaganda, technical training and subsidies all impacted the agrochemical input behavior. Pre-production technical guidance and farmers’ awareness significantly affected the willingness to adopt cleaner production. Technical training was helpful to improve farmers’ willingness to participate actively, and enhancing the pertinence of training played an important role in the adoption of cleaner production technology. In conclusion, the influencing factors of farmers’ agrochemical input in Beijing, Tianjin and Hebei were complex, and the scientific application level still needs to be improved. This paper finally discusses and puts forward some countermeasures and suggestions for agrochemical reduction and efficiency improvement.

Making clear the exact amount of carbon emissions from the planting industry is of great significance for developing low-carbon agriculture and helping achieve carbon neutrality. The current carbon emissions from the planting industry in Beijing, the capital of China, are still unclear, and there is a lack of quantitative research on the production, economic, and ecological benefits of carbon emissions. This paper used the carbon emissions factor method to study the inter-annual variation characteristics of carbon emissions and carbon benefits in Beijing’s planting industry since 2000. The results show that the carbon emissions from the planting industry in Beijing in 2023 were 256,400 tons, of which the carbon emissions from agricultural inputs, nitrous oxide (N₂O) from farmland, and methane (CH₄) from rice cultivation were 149,300, 105,200, and 2000 tons, respectively. From 2000 to 2023, the total carbon emissions from the planting industry in Beijing have shown a downward trend. Compared with 2000, the carbon emissions from agricultural inputs and N₂O in 2023 decreased by 59.88% and 74.52%, respectively. The carbon emissions of CH₄ from rice cultivation were only 2.38% of those in 2000, and the total carbon emissions from the planting industry in Beijing decreased by 70.43%. The average carbon emissions from agricultural inputs and N₂O accounted for 50.85% and 47.95% of the total level of the planting industry, respectively, and were the main sources of carbon emissions in Beijing. Chemical fertilizer and agricultural film inputs were important sources of carbon emissions from agricultural inputs. Reducing inputs for agriculture and sources of N₂O from farmland is an important way to reduce carbon emissions from agriculture in Beijing. In the end, some suggestions were proposed for reducing carbon emissions from the planting industry.

From the perspective of project and paper datasets, research frontier recognition in the field of agricultural resources and the environment using the Latent Dirichlet Allocation (LDA) topic extraction model was studied. By combining the wisdom of domain experts to judge the similarities and differences of clustering topics between the two data sources, multidimensional indicators, such as the emerging degree, attention degree, innovation degree, and intersection degree, were comprehensively constructed for frontier identification. The methods for hot research frontiers, emerging research frontiers, extinction research frontiers, and potential research frontiers were proposed. The empirical research in the field of agricultural resources and the environment showed that the “interaction mechanism of plant–rhizosphere–microbial diversity” was a hot research frontier in the years 2016–2021. The themes of “wastewater treatment technology and efficient utilization of water resources”, the “value-added utilization of agricultural wastes and sustainable development”, the “soil ecological response mechanism under agronomic management measures”, and the “mechanism of soil landslide, erosion, degradation and prediction evaluation” were judged as potential research frontiers. The theme of “ecosystems management and pollution control of agricultural and animal husbandry” was recognized as an emerging research frontier. The results confirm that the fusion method of extracting topics from project and paper data, combined with expert intelligence and frontier indicators for fine classification of frontiers, is an optional approach. This study provides strong support for accurately identifying the forefront of scientific research, grasping the latest research progress, efficiently allocating scientific and technological resources, and promoting technological innovation.

The development trends and research layout of agricultural resources and the environment (ARE) are the focus of global attention. In this study, we compiled a data set of SCI papers published in the ARE field since the 13th Five-Year Plan. Thereafter, the topic extraction model of Latent Dirichlet Allocation (LDA) was used to mine the text content so as to explore the research layout of global ARE. The results show that, between 2016 and the time of this study, 31,559 articles were published in the ARE field, exhibiting an overall upward trend. During this time, China and the United States were the main forces in paper publishing. The Chinese Academy of Sciences (CAS), Northwest Agriculture and Forestry University, and the US Department of Agriculture were the top three publishing institutions. Research institutes in China, the United States, Russia, Sweden, the Netherlands, Brazil, and Australia cooperated closely, and the CAS was at the center of the cooperation network. The clustering results of text topics based on the LDA model show that three topics—namely, the interaction mechanisms of plants, the rhizosphere, and microorganisms; the mechanisms and predictive evaluation of soil landslides or erosion; and the decomposition and interaction response of organic matter in agroforestry ecosystems—have been the hot research areas in this field since 2016. The management and efficient utilization of farmland nutrients, and the technology and mechanisms of agricultural waste resource utilization have become key research directions since 2019. The research layouts of China and the United States in this field were analyzed, and the similarities and differences were compared. In addition, suggestions for the future development of ARE are proposed. This study is of great significance for the overall development trend of ARE, the timely tracking of scientific research hotspots, outlining key research and development directions, and promoting scientific and technological innovation.