Chemical fertilizer plays an irreplaceable role in raising vegetable output and improving the livelihood of people in China. Chinese cabbage (Brassica chinensis L.) is one of the most common vegetables with a wide planting area. However, there are problems such as the excessive and blind application of chemical fertilizers, which bring about the increase of planting cost and the risk of environmental pollution. So, it is urgent to improve fertilization methods and improve fertilizer use efficiency, aiming to promote the sustainable development of agriculture. In this study, multi-year and multi-site experiments were retrieved from the published literature and public scientific research institutions to study a sustainable fertilizer recommendation method for Chinese cabbage based on yield response and agronomic efficiency. The results showed that the average indigenous nutrients supply of nitrogen (N), phosphorus (P), and potassium (K) were 112.98, 35.03, and 213.15 kg/ha, respectively. It is suggested that these nutrients should not be neglected in the process of fertilizer recommendation. The average yield responses to N, P₂O₅, and K₂O were 26.6, 13.9, and 16.6 t/ha, the relative yields were 0.70, 0.84, and 0.84; also, it was concluded that the agronomic efficiencies were 114.3, 108.5, and 89.4 kg/kg on average, respectively. From these datasets, the theoretical basis of recommended fertilization was established. It was found that there was a significant negative correlation between N, P, and K indigenous nutrient supply and the yield response to N, P₂O₅, and K₂O, and a significant negative linear correlation between yield response and the relative yield of N, P₂O₅, and K₂O. There was also a significant one-dimensional quadratic function relationship between yield response and agronomic efficiency in Chinese cabbage. Then, two years of field experiments for Chinese cabbage were conducted to verify the fertilizer recommendation. It was concluded that fertilizer recommendation for Chinese cabbage based on yield response and agronomic efficiency was a sustainable way for farmland utilization, not only economically and suitably satisfying its application on fields of different sizes, but also taking into account the indigenous nutrient supply and the interaction between N, P, and K, having shown the advantages of high efficiency, especially when the conditions such as soil testing and plant diagnosis were not sufficient.

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.

Arthropod natural enemies—encompassing predators and parasitoids—form the backbone of sustainable agriculture, delivering irreplaceable ecosystem services via biological pest suppression. Driven by global demand for eco-friendly alternatives to synthetic pesticides, research in this domain has grown sharply over the past decade. Here, we report a systematic bibliometric analysis of 6515 Web of Science Core Collection papers focused on arthropod natural enemies in biological control (2016–2025), with the goal of charting the field’s intellectual structure. Performance metrics confirmed an initial rapid increase from 2016 to 2019 followed by a plateau and a slight rise in 2025, with the US, China, and Brazil dominating output. Keyword co-occurrence networks pinpointed core themes, including conservation biological control, predatory mites, and integrated pest management (IPM). Temporal trends further revealed a pivot toward applied work on invasive pest systems. Co-citation analysis uncovered six foundational research clusters, while bibliographic coupling of 2021–2025 papers uncovered five active emerging subfields: landscape ecology and habitat manipulation, tri-trophic interaction mechanisms, high-impact invasive pest biocontrol, non-target risk assessment for introduced agents, and fall armyworm integrated management. We synthesize cross-cutting implications and outline future priorities—including AI-enabled rearing systems, functional biodiversity boosting, climate adaptation, and multifunctional landscape tuning. By consolidating historical progress and forward-looking directions, this framework empowers researchers, extension practitioners, and policymakers to scale sustainable pest management worldwide.

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.

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.