Ensuring food security is an eternal issue in the development process of human society, and as a major global grain-producing country, China has played an important role in stabilizing world food security. However, China’s food security is facing new challenges in the context of the new development pattern, and the existing grain statistics are fragmented and not comprehensive enough to meet the needs of current food security assessment studies. In this study, we constructed the time-series China food security comprehensive assessment dataset (CFSAD), which includes five categories of grain, rice, wheat, maize and soybean, and covers five dimensions of the basic guarantee level, the market operation situation, the scientific and technological support capacity, the resource and environmental conditions, and the level of purchasing power, and includes fourteen indicators. Our dataset enables a more scientific and comprehensive assessment of China’s food security situation, which can provide data support for effective government policy making and academic research.

Livestock products provide essential micro-nutrients and animal protein to rural residents. Upgrading the consumption pattern of livestock products is not only crucial for improving rural residents’ health and quality of life but also for achieving food security and a healthy China under the “Great Food View” development concept. To identify the characteristics and determinants of residents’ livestock products consumption structure in rural China, we used the Logit model to empirically analyze the key factors affecting rural residents’ consumption structure of livestock products from the perspective of household characteristics and regional heterogeneity using a survey data of 4529 rural residents across 10 provinces. The findings reveal that, firstly, rural residents consume a variety of livestock product categories, predominantly meat, meat-egg, meat-milk, and meat-egg-milk. Secondly, the family characteristics of the number of people eating at home, education level, access to food nutrition and health information, ethnicity, and age structure significantly affect the consumption structure of livestock products among rural residents. Thirdly, self-raising of livestock and poultry can support rural residents’ consumption of livestock products. Fourthly, there are notable variations in the consumption structure of livestock products between different regions. Based on this, we suggest strategies to optimize and support the consumption structure of livestock products for rural residents, such as promoting consumption upgrading, advocating market segmentation for livestock products, and improving regional self-sufficiency.

This paper attempts to establish the accurate and timely forecasting model for the total output value of agriculture, forestry, animal husbandry, and fishery (TOVAFAF) in various provinces of China using NPP-VIIRS nighttime light (NTL) remote sensing data and machine learning algorithms. It can provide important data references for timely assessment of agricultural economic development level and policy adjustment. Firstly, multiple NTL indices for provincial-level administrative regions of China were constructed based on NTL images from 2013 to 2023 and various statistics. The results of correlation analysis and significance test show that the constructed total nighttime light index (TNLI), luminous pixel quantity index (LPQI), luminous pixel ratio index (LPRI), and nighttime light squared deviation sum index (NLSDSI) are highly correlated with the TOVAFAF. Subsequently, using the relevant data from 2013 to 2020 as the training set, the four NTL indices were separately taken as single independent variable to establish the linear model, exponential model, logarithmic model, power exponential model, and polynomial model. And all the four NTL indices were taken as the input features together to establish the multiple linear regression (MLR), extreme learning machine (ELM), and particle swarm optimization-ELM (PSO-ELM) models. The relevant data from 2021 to 2022 were taken as the validation set for the adjustment and optimization of the model weight parameters and the preliminary evaluation of the modeling effect. Finally, the established models were employed to forecast the TOVAFAF in 2023. The experimental results show that the ELM and PSO-ELM models can better explore and characterize the potential nonlinear relationship between NTL data and the TOVAFAF than all the models established based on single NTL index and the MLR model, and the PSO-ELM model achieves the best forecasting effect in 2023 with the MRE value for 32.20% and the R² values of the linear relationship between the actual values and the forecasting values for 0.6460.

Source classification of rural residents is related to the effectiveness of domestic waste classification and treatment. The development of the habit of domestic waste classification by rural residents requires the incentive of environmental regulations. Using data from the 2022 CLES (China Land Economic Survey) database survey of 1189 farm households, we analyzed the impact and path of environmental regulation on the level of domestic waste classification among rural residents using the Oprobit model. This study found that approximately half of the samples used the classification method to dispose of domestic waste. The level of waste classification was low, and only 5.72% of the samples used the four-classification method to dispose of domestic waste. There is still a long way to go in classifying the domestic waste of rural residents. Guided environmental regulation, constrained environmental regulation, and incentive environmental regulation can directly improve the level of domestic waste classification of rural residents. However, it can also indirectly promote the level of domestic waste classification by promoting the understanding of domestic waste classification, improving the living environment, and improving environmental cognition through a sense of identity related to family responsibility. Accordingly, countermeasures are proposed to guide rural residents in classifying domestic waste by continuously strengthening the publicity of domestic waste classification, improving the system of policies and regulations, and raising the environmental awareness of rural residents.

The social intercourse application of agricultural product quality traceability is facing historical opportunities such as the growth of member agriculture, consumption upgrading and grading, rapid development of social media and social services in the current internet era. This research divides the users of social intercourse application of agricultural product quality traceability into producers, consumers and distributors, and points out that the application should have the features of being open and easy to spread, free of charge and easy to access, interesting and attractive, real-time and interactive and for dissemination, it can be carried out through searching and subscribing the producers, recording and forwarding the content, as well as scanning agricultural product traceability QR code. Based on the above-mentioned methods and ideas, the “Nongdu Easy to Trace” Wechat program based on Wechat platform has been developed and has been widely promoted and used in many provinces in China.

This paper examines the relationship between supply chain digitalization and firm-level supply chain resilience using the staggered rollout of China’s Supply Chain Innovation and Application Pilot Program as a quasi-natural experiment. Based on panel data for Chinese A-share listed manufacturing firms from 2012 to 2023, the difference-in-differences estimates indicate that policy exposure is associated with a statistically significant increase in supply chain resilience. The coefficient remains stable across parallel trends tests, placebo exercises, additional controls, high-dimensional fixed effects, and policy-selection diagnostics. Because pilot assignment followed an evaluation process, rather than randomization, the estimates remain subject to possible selection on unobserved characteristics. Subgroup regressions yield larger positive coefficients for firms in less marketized regions, non-state-owned enterprises, and mature firms. Sobel tests support the financing constraint pathway, whereas the information transparency pathway is only marginally significant. Asset turnover, the operating cycle, and inventory alignment are associated with resilience in the outcome equations, but the corresponding first-stage policy coefficients are not robust in the preferred firm- and year-fixed effect specifications. The findings document a positive quasi-experimental association between supply chain digitalization and resilience, while highlighting the institutional and firm-level conditions that shape the estimated relationship.