Major Grain-producing Areas Research Articles

Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020

Amid persistent global food security challenges, the efficient utilization of cultivated land resources has become increasingly critical, as optimizing Cultivated Land Utilization Efficiency (CLUE) is paramount to ensuring food supply. This study introduced a cultivated land utilization index (CLUI) based on Fractional Vegetation Cover (FVC) to assess the spatiotemporal variations in Henan Province’s CLUE. The Theil–Sen slope and the Mann–Kendall test were used to analyze the spatiotemporal variations of CLUE in Henan Province from 2000 to 2020. Additionally, we used a genetic algorithm optimized Artificial Neural Network (ANN) and a particle swarm optimization-based Random Forest (RF) model to assess the comprehensive in-fluence between topography, climate, and human activities on CLUE, in which incorporating Shapley Additive Explanations (SHAP) values. The results reveal the following: (1) From 2000 to 2020, the CLUE in Henan province showed an overall upward trend, with strong spatial heterogeneity across various regions: the central and eastern areas generally showed decline, the northern region remained stable with slight increases, the western region saw significant growth, while the southern area exhibited complex fluctuations. (2) Natural and economic factors had notable impacts on CLUE in Henan province. Among these factors, population and economic factors played a dominant role, whereas average temperature exerted an inhibitory effect on CLUE in most parts of the province. (3) The influenced factors on CLUE varied spatially, with human activity impacts being more concentrated, while topographical and climatic influences were relatively dispersed. These findings provide a scientific basis for land management and agricultural policy formulation in major grain-producing areas, offering valuable insights into enhancing regional CLUE and promoting sustainable agricultural development.

Human interventions have enhanced the net ecosystem productivity of farmland in China

Human interventions, such as farmland management, have long been considered crucial for soil carbon sequestration, but little is known about the exact impact of these interventions on the net carbon flux, represented by net ecosystem productivity (NEP). Here, using multiple long-term, large-scale data and statistical data, we reveal that 75.54% of farmland NEP in China experiences an increase, with northern regions showing the greatest potential for future farmland carbon sequestration. This growth is primarily attributed to the role of farmland management, especially the enhancement of no-tillage, land consolidation and multiple cropping level (17.02%, major grain-producing areas in 2020). Notably, the current unreasonable practices of mechanized straw returning and irrigation have a negative impact on farmland NEP. Our results show that it is imperative to acknowledge the crucial role of human interventions on farmland NEP to strike a balance between food security and farmland carbon sequestration.

Heterogeneous Impacts of Traditional and Modern Information Channels on Farmers’ Green Production: Evidence from China

Efficient agricultural input is crucial for agricultural green production and sustainable development. The swift evolution of information and communication technologies has diversified the avenues through which farmers access information. However, how different information channels affect farmers’ production input remain poorly understood. Leveraging a two-way fixed-effects model and the Karlson-–Holm–Breen (KHB) method, this study delves into the mechanisms underlying the influence of both traditional and modern information channels on farmers’ inputs of seeds, chemical fertilizers, and pesticides (SCFP) based on over 15,000 sample of Chinese farmers. The findings reveal the following: (1) modern information channels significantly decrease farmers’ SCFP input, whereas traditional channels exhibit the opposite effect; (2) environmental pollution perception acts as a mediator in the influence of both traditional and modern information channels on farmers’ SCFP input; (3) traditional information channels significantly promote farmers’ SCFP input in the grain production and marketing balance areas, and modern information channels inhibit farmers’ SCFP input in major grain-producing areas; and (4) traditional and modern information channels have an impact on farmers’ SCFP input in the western region, but not in the central region. To promote sustainable agricultural development, government departments should enhance rural Internet access, diversify information sources, advocate for eco-farming, ensure regional digital equity, and enhance green agri-tech promotion.

Effects of Agricultural Insurance on Water Pollution in China

Water pollution is the most serious environmental problems in China now, water pollution directly affects people's quality of life and the sustainable development of agriculture, and the biggest source of water pollution is agricultural non-point source pollution, so we need to pay more attention to the environmental impact of agricultural production and reduce agricultural non-point source pollution. This paper examines the environmental impact of agricultural insurance on water pollution. Using annual data from 30 provinces across China between 2011 and 2019, this paper employs a two-way fixed-effects model to examine the correlation between agricultural insurance development and agricultural pollutant emissions. Additionally, it takes agricultural carbon emissions and agricultural output value as dependent variables to comprehensively investigate the environmental and economic impacts of agricultural insurance. The research results indicate that the development of agricultural insurance has a significant effect on reducing agricultural water pollution and carbon emissions. The pollutant reduction effect is more significant in the major grain-producing areas. The positive environmental effect of agricultural insurance is based on the fact that the development of agricultural insurance is conducive to reducing the use of pesticides and chemical fertilisers and does not come at the expense of increased agricultural output.

The Current Scenario of Farmland Abandonment in China: A Systematic Review

The significant expansion of farmland abandonment not only poses a threat to agricultural sustainability, but also challenges biodiversity conservation and food security. This study aims to initiate a deep systematic analysis of the current scenario of Chinese farmland abandonment, which is timely and urgent as a starting point to fully understand the current state of knowledge of it. In total, 181 articles out of 5384 articles through four databases (CNKI, Web of Science core collection, Scopus, and CAB Abstracts) are extracted and synthesized by the PRISMA method. A total of 12 experts from 11 countries with specialized knowledge in the research field are interviewed. It is found that farmland abandonment in East China is the most frequently reported, which is followed by the Southwest. The research focus in China has shifted from mountainous areas to agricultural and pastoral areas and major grain-producing areas. Chinese farmland abandonment is defined principally from the perspective of the managerial approach. An inventory that categorizes these different drivers of farmland abandonment is built, which includes socio-economic aspects, biophysical attributes, policy, household characteristics, and specific events. Socio-economic aspects, especially off-farm employment, are the most commonly studied factors. Meanwhile, the aging of the population is also noteworthy. Different trajectories should be applied accordingly due to the significant differences between North and South China. Furthermore, there is an optimistic attitude towards the ecological impact of abandoned farmland in China. However, more evidence should be given on it. Those findings will hopefully provide some insights for the scientific community and policy makers.

Spatial Differentiation Characteristics of Soil Organic Carbon and Its Influencing Factors in Cultivated Land in Major Grain-producing Areas： A Case Study of Hebei Province

Assessing the spatial differentiation characteristics of soil organic carbon （SOC） in cultivated land in major grain-producing areas is important for regional cultivated land quality management and national food security. We investigated 519 soil profiles of cultivated land in Hebei Province （0-120 cm equally divided into six layers）, and obtained 2961 samples. We used geostatistical methods and spatial exploratory analysis to reveal the spatial distribution pattern of SOC in cultivated land in Hebei Province and the impacts of climate, topography, geomorphology, soil properties, and anthropogenic use on the spatial distribution of SOC in cultivated land soils. The results showed that： ① The SOC content of cultivated land in Hebei Province showed a decreasing trend with the increase in soil depth, with the highest mean value of ω（SOC） of 9.57 g·kg-1 in A1 （0-20 cm） and the lowest mean value of 4.17 g·kg-1 in A6 （100-120 cm）, and the coefficient of variation showed an increasing trend with the increase in soil depth. ② The SOC at different depths of cultivated land in Hebei Province had similar horizontal spatial distribution characteristics, and in general, showed a trend of being high in the northwest and low in the southeast. ③ Soil texture and topography were the main influencing factors for the spatial variation of SOC in cultivated land in Hebei Province, showing that the more clay-rich the soil texture, the greater the SOC content, and the higher the elevation, the greater the SOC content. Soil pH also influenced the SOC content of the profile. The SOC content of the surface layer is mainly affected by anthropogenic use, whereas the bottom layer is affected by the cumulative temperature.

Impacts and mechanisms of digital village construction on agricultural green total factor productivity

Green is the foundation of agricultural development. By leveraging modern information technology, digital village construction injects new momentum into the green growth of agriculture. Using balanced panel data from 31 provinces in China from 2011 to 2022, this paper employs the entropy approach and SBM-GML index to measure the indicators of digital village construction and agricultural green total factor productivity (AGTFP). The impacts and mechanisms of digital village construction on AGTFP are examined through fixed effect, mediating effect, and threshold models. The findings are as follows: (1) AGTFP in China shows an overall increasing trend from 2011 to 2022, with significant growth in the western region compared to the eastern and central regions. (2) Digital village construction significantly accelerates the improvement of AGTFP, a conclusion supported by robustness tests. (3) Mechanism analysis indicates that digital village construction advances AGTFP by fostering agricultural technology innovation, enhancing agricultural human capital, and improving agricultural productive services. (4) Digital village construction has a more significant impact on major grain-producing areas, economically underdeveloped areas, and northern region compared to other regions. (5) Environmental regulation acts as a threshold effect on the impact of digital village construction on AGTFP. Digital village construction substantially impacts AGTFP when environmental regulation is below the threshold, with the positive effect continuing beyond this point but at a reduced intensity.

The Impact of Farm Structure on Agricultural Growth in China

Farm structure has changed significantly since the land transfer policy was introduced in China. The quantity of and land area utilized by scale farmers and new agricultural entities are increasing, while the numbers of smallholders are decreasing. To analyze the impact of farm structure on agricultural growth in China, this study used provincial-level panel data from 2010 to 2021 and a fixed-effects model for empirical testing. The results show that (1) the structural change among farmers has a positive effect on agricultural growth, accounting for 16% of the contribution; (2) compared with scale farmers, new agricultural entities (NAEs) play a stronger role in improving agricultural growth, which is approximately five times higher than that of the former; and (3) unlike scale farmers, who only promote agricultural growth in central and major grain-producing areas, new agricultural entities have a positive effect on the entire area. Therefore, this study emphasizes the role of human capital in agricultural growth, especially in terms of promoting new agricultural entities, supporting land transfer, and optimizing farm structure.

How can agricultural water use efficiency be promoted in the North China Plain?

Water resources are reliable guarantees for high quality development of agriculture in the North China Plain. Improving agricultural water use efficiency is one of the essential ways to solve agricultural water resources shortage. This study measured agricultural water use efficiency (AWUE) using a stochastic frontier analysis (SFA) model and estimated agricultural water-saving potential (AWP) for 74 prefecture-level cities in the North China Plain. The main factors that influenced AWUE were further identified by developing spatial econometric models. The results showed that: (1) From 2000 to 2020, the AWUE of the study area ranged from 0.701 to 0.755 and first rose then fell, and then leveled off. (2) Spatially, the best AWUE was in the central part, followed by the north, and the worst was in the south, and nearly 65% of prefectural cities had annual average AWUE below 0.8. (3) Significant gaps in AWUE and AWP were observed in different regions. Shijiazhuang, Anyang, Hebi and Xinxiang should be considered as key targets to improve AWUE. (4) The effective irrigation degree, per sown area annual precipitation, and annual average temperature had positive effect on AWUE. Increasing the corn sowing area appropriately and reducing the input of per sown area machinery power could also improve AWUE. Therefore, adopting deep plowing measures, developing semi-arid agriculture, and advancing water-saving irrigation technology were feasible ways to improve AWUE and contribute to sustainable agriculture in the North China Plain. These findings can provide a reference for the formulation of high-water efficiency agricultural management strategies in other similar major grain-producing areas.

Rural human settlement environment, non-agricultural transfer of labour and arable land abandonment in China

The arable land abandonment caused by the large-scale non-agricultural transfer of labour has attracted substantial attention from all walks of life in China. Promoting improvement in human settlement environment can accelerate the construction of infrastructure, ameliorate grassroots organization and enhance management capacities while simultaneously decelerating agricultural production costs. High level of human settlement environment can also attract the labour force to return, stimulate the vitality of rural elements and endogenous powers. Then, can improving rural human settlement environment alleviate the phenomenon of arable land abandonment caused by non-agricultural labour transfer? In order to answer this question, based on the micro-survey data of 1325 households in 5 provinces of China, this paper uses the Tobit model to empirically test the effects of rural human settlement environment and non-agricultural transfer of labour on arable land abandoned. The results revealed that rural human settlement can alleviate the arable land abandonment caused by non-agricultural transfer of labour to a certain extent. In particular, the improvement of rural human settlement environment that mainly based on the infrastructure construction and organizational management level, has significantly alleviated the arable land abandonment caused by the non-agricultural transfer of labour. Heterogeneity analysis disclosed that, compared with mountainous and hilly areas, the improvement of rural human settlement environment had a more obvious mitigation effect on arable land abandonment in plain areas. Promoting infrastructure construction and strengthening organizational management ability were effective ways to alleviate arable land abandonment in plain areas. Farmer households with high place attachment level were more likely to be attracted by the improvement of rural human settlement environment to return to their hometown, so as to make use of arable land resources. Improving infrastructure, strengthening organizational management level, and promoting cultural and community development were the main measures for farmer households with high place attachment level to reduce arable land abandonment. In addition, there were significant differences in arable land abandonment and its driving factors in different regions. In the central and eastern regions or major grain-producing areas, improving human settlement environment had a significant mitigation effect on arable land abandonment. Therefore, improving the rural human settlement environment according to local conditions, promoting the supportive policy will be inclined to mountainous and hilly areas, enhancing the attractiveness of rural areas, encouraging farmers with high place attachment level to return to their hometowns for employment and entrepreneurship, and accelerating the cultivation of new types of agricultural operators, which will help alleviate the arable land abandonment caused by non-agricultural transfer of labour.

Assessing the Effect of Factor Misallocation on Grain Green Production Capacity: A Case Study of Prefecture-Level Cities in Heilongjiang Province

Improving the efficiency of factor allocation in food production is the foundation for accelerating the formation of new quality productivity and achieving an agricultural green transformation. However, there has been no scholarly focus on their mechanisms and the interactions involved. This exploration is an important reference for enhancing the green production capacity of major grain-producing areas. In this study, 13 prefecture-level cities in Heilongjiang Province, China’s largest grain production base, were selected as the research samples. A model for identifying factor misallocation and grain green total factor productivity (AGGTFP) was constructed to identify the spatiotemporal differences in factor misallocation and green total factor productivity. A fixed effects model was used to explore the impact of single-factor misallocation and the interaction of dual-factor misallocation with AGGTFP. The results show that from 2004 to 2022, the AGGTFP in 13 prefecture-level cities in Heilongjiang Province has shown a slow growth trend. The inhibitory effects of single-factor misallocation of land, labor, and capital on green total factor productivity are sequentially enhanced. The interaction effects of capital misallocation and labor misallocation and labor misallocation and land misallocation strengthen the inhibitory effects of misallocation on the AGGTFP. Therefore, it is necessary to further promote the optimization of production factors and improve the green production capacity for grain.

Big data development and agricultural carbon emissions: Exacerbation or suppression? A quasi-natural experiment based on the establishment of the National Big Data Comprehensive Pilot Zone

As a strategic resource, big data has become a key force affecting carbon emission reduction in agriculture. However, its impacts remain controversial, and relevant empirical evidence remains to be explored. Based on quasi-natural experimental analysis, this study explored the impact and mechanism of the construction of the National Big Data Comprehensive Pilot Zone (NBDCPZ) on agricultural carbon emissions (ACE) in China and adopted a difference-in-difference (DID) model using China's provincial panel data from 2003 to 2020. The results showed that the ACE in the NBDCPZ establishment area was significantly reduced by 11.91%, a finding that remained robust following the parallel trend test and the placebo test, among others. Mechanism analysis showed that the ACE was reduced through industrial upgrading and technological innovation. Heterogeneity analysis showed that more pronounced policy gains were achieved in China's central-eastern regions as well as in non-major grain-producing areas compared to western and major grain-producing areas. This research provided supporting evidence for the prospect of big data application in ACE and provided useful guidance regarding the promotion of green and sustainable agricultural development.

Effect of Taobao village certification on agricultural fertilizers and pesticides usage in China

Employing the Taobao village certification (TVC) as an exogenous policy shock and leveraging balanced panel data at the county level from 2007 to 2021, our multi-period Difference-in-Differences (DID) analysis reveals that the TVC reduces agricultural fertilizers and pesticides usage by 5 % to 10 %. This environmental benefit primarily stems from facilitating labor transfer and advocating for environmentally sustainable agriculture. Moreover, a more pronounced pollution reduction effect is observed in counties with higher marketisation level and major grain-producing areas. Our paper holds significant practical implications for rural environmental governance and potentially for other agricultural powerhouses where e-commerce is flourishing.

The Spatiotemporal Correlation between Human Activity Intensity and the Evolution of Ecosystem Service Value in the Songnen Plain, China

For the main grain-producing areas worldwide that balance multi-tasks of grain production, ecological protection, and economic development, quantitatively revealing the correlation between human activity intensity (HAI) and ecosystem service value (ESV) is conducive to formulating adapted ecological protection policies and promoting the coordinated development of the regional economy, society, and ecosystem. In this paper, we took the Songnen Plain of China as an example, employed a modified Equivalent Factor Method (integrating socio-economic data, the normalized difference vegetation index (NDVI), and land use data), and the HAI Assessment Model (based on the data of land use, night-time light, and population spatial distribution) to measure the ESV and HAI in the Songnen Plain of China for the years 1990, 1995, 2000, 2005, 2010, 2015, and 2020. We further applied the standard deviational ellipse method, the coupled coordination degree model, and the bivariate spatial autocorrelation models to reveal the spatiotemporal dynamics and correlation characteristics of ESV and HAI. The results showed the following: (1) Temporally, the ESV declined from 950.96 billion yuan in 1990 to 836.31 billion yuan in 2015, and then increased to 864.60 billion yuan in 2020, with the total loss attributed to the significant decline in the ESV of the natural ecosystem. Spatially, the ESV in the western and northeastern regions was relatively high, with a significant increase in the northeast. (2) HAI showed an upward trend from 1990 to 2020, while the high HAI levels gradually shrank after reaching the peak in 2000. Low HAI levels were mainly distributed in the northeast and southwest, aligning with the ecological space, while high HAI levels were distributed in the middle and southeast. (3) The interaction between ESV and HAI was marked by a negative correlation, transitioning from conflict to coordination. The spatial pattern of HAI and ESV showed H (HAI)-L (ESV) and L-H clustering, with H-H and L-L scattered distributions. This study contributes to providing a framework, methods, and suggestions for the sustainable planning and utilization of land and ecological protection in order to offer scientific references for the Songnen Plain, other major grain-producing areas, and related studies.

The food security risks in the Yangtze River Delta of China associated with water scarcity, grain production, and grain trade

Grain production consumes a large amount of water and is affected by the degree of water scarcity and participation in the grain trade in various regions. The grain trade has changed the food security risks in regions where grain exports and imports. Therefore, it is crucial to consider regional water scarcity to understand food security risks from the grain trade network. Here, we construct a new framework for measuring regional food security risks associated with water scarcity, grain production, and grain trade based on a cross-city grain trade network combined with virtual water flows to evaluate the regional food security risks in the Yangtze River Delta region (YRD) of China in 2017. The results show that under the current domestic grain trade pattern in China, the YRD and its four provincial-level administrative regions are in a net grain import state. The grain trade within the YRD is concentrated in exports from the two major grain-producing areas of Anhui and Jiangsu to Zhejiang and Shanghai, especially from northern Jiangsu to southeastern Zhejiang. The net import results of virtual blue water in most cities indicate that the YRD has shifted its water resource pressure to other grain exporting regions in China, with Shanghai and Zhejiang being the greatest beneficiaries. Extreme risk only exists in Shanghai, and severe and moderate risks are concentrated in Jiangsu. The current grain trade has reduced the overall food security risk in the YRD by 1.3 % but increased the risks in Shanghai and Zhejiang by 2.1 % and 0.8 % respectively. This study highlights the potential risks that excessive production of food in water-scarce areas in the grain trade system may bring to a stable food supply, providing useful information for a comprehensive understanding of the food and water security situation and for future trade-offs.

The Effect of High-Standard Farmland Construction Policy on Grain Harvest Losses in China

The United Nations included reducing harvest losses as a Sustainable Development Goal in 2015, sparking heightened research and policymaker interest in reducing losses to ensure food security. High-standard farmland construction plays a crucial role in ensuring food security. Few studies have combined high-standard farmland construction with grain harvest losses. Drawing on the data from the 2022 Chinese Post-Harvest Loss Survey (CPHLS 2022), the study utilizes OLS (ordinary least square) and quantile regression models to explore the impact of high-standard farmland construction on grain harvest losses. Empirical results show that high-standard farmland construction can significantly reduce grain harvest losses. The research conclusions are still valid after passing a series of robustness tests. The heterogeneity analysis shows that high-standard farmland construction significantly impacts on grain harvest losses for farmers in major grain-producing areas, plain areas, and eastern regions. Mechanism analysis reveals that high-standard farmland construction mainly reduces grain harvest losses by expanding operational scale and enhancing mechanization application. Based on research findings, the Chinese government should formulate a targeted high-standard farmland construction policy, optimize the agricultural machinery operating environment, and promote appropriate operational scale to ensure national food security.

Analysis of Land Use Gravity Center Change and Carbon Emission Impact in Chengdu Plain of China from 2006 to 2022

As the economic center and major grain-producing area in Southwest China, the calculation of the carbon budget and the protection of cultivated land in the Chengdu Plain are of vital significance for China to achieve a carbon peak strategy and ensure food security. For the purpose of clarifying the trend of land use focus and carbon emissions in the Chengdu Plain, the carbon peak level of land use in 33 counties in the Chengdu Plain was explored. Based on the gravity center model and IPCC carbon emission coefficient method, the changing trend of land use gravity center and carbon emission in Chengdu Plain from 2006 to 2022 was clarified. PLS regression model and LMDI model were used to explore the main influencing factors of the carbon emission of cropland and the carbon emission of building land. PLUS model was used to simulate future land use patterns and carbon emissions. (1) The center of gravity of cropland, building land, water, and other and unused land shifted to the northeast by 4.23 km, 5.46 km, 8.44 km, and 31.58 km, respectively, and that of forest and grass shifted to the southeast by 11.12 km and 3.41 km, respectively. For major food crops, the centers of gravity of rice and maize moved northeastward by 15.47 km and 7.52 km, respectively, while wheat moved southwestward by 17.77 km. (2) From 2006 to 2022, carbon emissions from land use in the 33 counties of the Chengdu Plain are all on the rise, with a total increase of 13.552 million tons, and carbon sinks in the 31 counties continue to decline, with a total decrease of 0.691 million tons. (3) Under the natural scenario, carbon sink scenario, and carbon reduction scenario, the carbon emissions from land use decrease by 0.5391 million tons, 3.4728 million tons, and 4.5265 million tons from 2022, respectively. Among the 33 counties in the Chengdu Plain, 11 counties did not achieve carbon peak under the natural scenario, 5 counties did not achieve carbon peak under the carbon sink scenario, and all the counties achieved carbon peak under the carbon sink scenario. During the study period, there was a serious loss of cropland in the Chengdu Plain, mainly to building land in the central part of the Chengdu Plain and to forests within the Longmen Mountain, Longquan Mountain, and Leshan City, and there is a need to strengthen cropland protection in this region in the future. Under the natural scenario, carbon sink scenario, and carbon reduction scenario, land use in the Chengdu Plain region can achieve carbon peak, and the carbon reduction model will be more helpful for the counties to achieve carbon peak.

Study on the Mitigation Effect and Promotion Mechanism of Agricultural Digitalization on the Agricultural Land Resource Mismatch

The objective of this research is to explore the impact mechanism of agricultural digital transformation in alleviating the mismatch of agricultural land resources and provide an effective path for the formation of new quality agricultural productivity. Using the balance panel data of 29 provinces in China from 2011 to 2022, this paper analyzed the mitigation effect and mechanism of agricultural digitalization on agricultural land resource misallocation from the perspectives of land scale management and agricultural socialization services. The results indicate that agricultural digitalization can alleviate the misallocation of agricultural land resources, promote the large-scale management of agricultural land, and improve the level of agricultural socialization services, all significant ways to reduce the mismatch of agricultural land resources. The heterogeneity test showed that the mitigation effect of agricultural digitalization on the agricultural land resource mismatch in eastern and central China and major grain-producing areas was better than that in western China and non-major grain-producing areas. Hence, we ought to strengthen the construction of agricultural digital infrastructures and play into the role of agricultural land scale management and agricultural socialization services in slowing down the mismatch of agricultural land resources.

Analysis of spatial patterns and influencing factors of farmland transfer in China based on ESDA-GeoDetector

Farmland transfer is a critical component in facilitating agricultural scale management and improving agricultural production efficiency. This study examines the spatial distribution of farmland transfer in China and identifies the factors influencing it, offering valuable guidance for advancing China’s farmland transfer practices. Through the application of mathematical statistics and GIS spatial analysis, the study investigates changes in spatial patterns related to the scale, rate, mode, and recipients of farmland transfer across China's 30 provinces from 2015 to 2020. Geographical detectors are also employed to identify the key factors influencing the extent and pace of farmland transfer. The study reveals that between 2015 and 2020, China's farmland transfer area increased from 29,789 to 37,638 million hectares. Provinces with abundant farmland resources generally experienced larger farmland transfers, while economically developed regions and major grain-producing areas saw higher rates of farmland transfers. The predominant mode of farmland transfer in China was leasing (subcontracting), accounting for over 80% of the total transferred area. Large-scale grain growers and family farms were significant participants in farmland transfers, acquiring approximately 60.1% of the transferred lands, followed by professional cooperatives (21.5%), enterprises (10.4%), and other entities (7.9%). Key factors influencing the farmland transfer area include the "regional farmland area", the "proportion of family farms supported by loans", and the "proportion of non-agricultural population", with explanatory powers of 0.663, 0.319, and 0.225, respectively. Notably, there is a substantial interaction between the "regional farmland area" and factors such as the "proportion of family farms supported by loans" and the "grain yield per unit area", with explanatory powers reaching 0.957 and 0.901, respectively. These findings offer valuable insights for promoting farmland transfer in agriculturally rich regions. Factors affecting the farmland transfer rate include "grain yield per unit area", "GDP per capita", and the "proportion of non-agricultural population", each with an explanatory power above 0.500. Moreover, their interactive explanatory powers with other indicators exceed 0.600, indicating that provinces with high agricultural productivity or economic development levels are more likely to undergo farmland transfer. The paper concludes by proposing strategies and recommendations to promote farmland transfer in both "large agricultural areas" and "metropolitan suburbs."

Do Factor Misallocations Affect Food Security? Evidence from China

The reasonable allocation of grain production factors is of vital importance to food security and agricultural development. To assess the impact of agricultural factor misallocation on food security, this paper, based on the panel data from China spanning from 2005 to 2019, conducted a comprehensive evaluation of agricultural factor misallocation and food security coefficients across 31 provinces in China, using a spatial Durbin model to examine the effects of factor misallocations on food security. The findings are as follows: (1) Production factor misallocation has significant negative impacts on food security, among them, capital misallocation and labor misallocation inhibiting food security in the local and neighboring areas, and land misallocation has a significant negative impact on food security in local areas, while its spatial spillover effect is no longer significant. (2) Mechanism analysis shows that capital misallocation and labor misallocation hinder the development of transportation infrastructure and the transfer of rural labor, thereby reducing food security. Land misallocation has accelerated the construction of transportation infrastructure, promoted the migration of rural labor, and helped ensure food security. (3) The regional heterogeneity test reveals that capital misallocation and labor misallocation hinder food security in major grain-producing areas and both sides of the Hu Huanyong Line (Hu Line). Meanwhile, land misallocation hinders food security development in various grain-producing areas, as well as the southeast of the Hu Line. Based on the above conclusions, this paper proposes suggestions to improve the efficiency of land and labor resource allocation, accelerate the construction of transportation infrastructure, and encourage the transfer speed of surplus agricultural labor.