2.1 Land transfer mechanism

A well-defined property rights system is fundamental for enabling the fluid movement of land. Through the issuance of legally binding certification documents, the reform strengthens the stability and security of farmers’ land contracting rights, thereby increasing the stability, security, and exclusivity of agricultural land property rights [22]. This legal assurance reduces farmers’ concerns about potential risks associated with long-term rentals, boosting their willingness to transfer agricultural land [23]. Building on the existing separation of ownership and contracting rights, the separation of three rights reform introduces an additional division between contracting and management rights, further expanding the functional scope of agricultural land property rights. At the policy level, the reform encourages the transfer of management rights, raising expectations for returns on these transfers and promoting the outward movement of low-return or underutilized farmland. In parallel, rural land management right transfer markets have been established across various regions, along with strengthened oversight to facilitate orderly transactions. These developments contribute to a more market-driven transfer of agricultural land across regions.

Land transfer facilitates the intensification of agricultural land management. It allows agricultural land resources, which are less efficient in grain production and where contractors have a strong desire to exit grain planting and expect to earn income from land transfers, to be transferred to contractors with higher grain production efficiencies, achieving more intensive land management. Intensified management of land aids in the scientific combination and intensive use of grain production factors, significantly increasing per unit grain yield, and also allows the cost of agricultural machinery and land improvements to be spread over a larger area. Land transfer is a necessary prerequisite for moderate-scale operations [24], which are a crucial pathway to enhancing the efficiency of grain production [25]. On one hand, the costs of production and market transactions gradually decrease at higher scales of grain crop production, and compared to cash crops, grain crops exhibit stronger economies of scale, resulting in higher returns from grain cultivation than from non-grain crops [26], thereby boosting farmers’ enthusiasm for continuous grain production. Therefore, land transfer can lead to a ’grain-oriented’ trend in land production [27]. On the other hand, scaled operations can mitigate the impacts of aging rural labor forces, such as abandoned or extensively managed farmland, and increase the use of modern grain production technologies and management practices like improved seeds, mechanization, insurance, meteorological services, and scientifically balanced fertilizers and pesticides, enhancing the resilience of grain production to risks.

2.2 Agricultural productive investment mechanism

When agricultural land rights are unstable, farmers perceive a heightened risk of future land infringement, reducing their motivation to invest in land over the medium to long term. By formalizing the legal status of farmers’ land contracting rights, the reform enhances their sense of security and ownership, thereby increasing their willingness to make productive investments. This reform promotes the consolidation of management rights among farmers with higher production efficiency and a stronger commitment to agricultural production, while securing stable contracting rights. For farmers acquiring land management rights, the clarity in defining the transferred land area and the long-term stability of these rights lower transaction costs and mitigate contract breach risks, fostering investment incentives driven by economies of scale. Compared to small-scale farmers, larger agricultural operators benefit from easier access to land management right mortgages, which expands their investment capacity in agricultural production [28]. Furthermore, these larger-scale operators are more inclined and able to adopt green production technologies, thereby enhancing both their engagement with and investment in sustainable agricultural practices.

Investment in agricultural machinery can reduce labor costs [29], increase the possibility of multiple cropping [30], and enhance the ecological coordination and foundational capabilities of grain production. The input of agricultural machinery also strengthens the resilience and regenerative capacity of grain production through the “technology introduction effect.” On one hand, it can enhance the technological coverage across various stages of grain production. Technological innovations in machinery can enhance the resilience and regenerative abilities of grain production; for example, during the seeding phase, mechanical seeding not only improves seeding efficiency, but also allows for precise monitoring of soil moisture, nutrient status, and crop growth [31], enhancing the capacity of grain production to withstand natural risks. During the harvesting phase, mechanical harvesting efficiency significantly surpasses manual harvesting, and can better avoid harvesting losses. On the other hand, investment in agricultural mechanization can stimulate advances in grain production technology.

Based on the above analysis, this paper proposes the following research hypotheses:

H1: The Reform of the Separation of Three Rights of Agricultural Land Enhances Resilience in Grain Production.

H2: Enhancing Grain Production Resilience Through Agricultural Land Transfer in the Separation of Three Rights Reform.

H3: Enhancing Grain Production Resilience Through Agricultural Productive Investment Under the Separation of Three Rights Reform.

3.1 Model setup

3.1.1 Baseline regression model.

The DID model,as a tool for policy evaluation, has gained increasing favor among scholars in recent years.This study employs a DID model,leveraging the agricultural land “three rights separation” reform as a quasi-natural experiment to analyze the effects of land rights reform on food production resilience.Although the “three rights separation” reform was formally introduced by the Chinese government in 2014, but its implementation timeline varied across local governments.However,traditional DID models,which typically examine policies with only a single shock point,cannot accurately estimate the effects of policies that have multiple shock points. Therefore,this paper adopts a multi-period DID model to assess the policy effects of the separation of three rights of agricultural land. The empirical model constructed in this paper is as follows:

(1)

In Formula (1): is the dependent variable,representing the resilience of grain production in province i during period t; is the explanatory variable,coded as 1 for years after the initiation of land titling and 0 otherwise; includes control variables such as regional economic development level,urbanization rate,rural human capital, farmer income,agricultural industry concentration, regional industrial structure, and agricultural insurance density. Additionally, represents the constant term; indicates the policy effect; are the coefficients for the control variables; represents fixed effects for provinces; represents fixed effects for years; is the error term.

3.1.2 Parallel trends test model.

The validity of the multi-period DID model estimation is contingent on meeting the parallel trends test. This paper uses the event study approach to examine the trend changes in grain production resilience before and after the separation of three rights of agricultural land, with the specific model being:

(2)

In Formula (2), represents a set of dummy variables,assigned a value of 1 if land titling was implemented in province i during year t,and 0 otherwise; ,, are the coefficients to be estimated; ,, retain the same meanings as in Formula (1).

3.2 Variable selection

3.2.1 Dependent variable.

Based on previous studies [8,32], this paper defines grain production resilience as the capacity of the grain production system to maintain or swiftly recover its production functions in the face of various unforeseen shocks, while undergoing fundamental transformations to ensure the stability of grain supply and enhance its capacity for sustainable development.A resilience evaluation index system for grain production has been constructed,encompassing three dimensions resilience, recovery, and regeneration including six secondary indicators and twenty-one tertiary indicators,as detailed in Table 1. Given the suitability of the entropy method for evaluating different research subjects across multiple periods,this method will also be used to determine the weights of the indicators. Based on this, a comprehensive index of the resilience development level of grain production in various provinces from 2005 to 2021 will be calculated. Additionally, this paper employs the coefficient stripping method to isolate grain production inputs from broader agricultural inputs for some indicators.

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Table 1. Evaluation index system for grain production resilience.

https://doi.org/10.1371/journal.pone.0313772.t001

Resistance capacity in food production refers to a system’s capacity to withstand unpredictable shocks, serving as a measure of its overall functional robustness. This study conceptualizes resistance capacity through two primary dimensions: foundational security of food production and stability of production capacity. Foundational security encompasses the essential conditions that underpin food production, providing a basis for assessing resource input levels. Specifically, this study utilizes three tertiary indicators to capture this dimension: effective irrigated area, grain sown area, and workforce size within primary industries. Stability of production capacity, on the other hand, reflects the consistency of food production outputs. A higher level of output stability indicates enhanced system resistance, which is assessed here via metrics such as the coefficient of grain yield fluctuation, per capita grain availability, and grain yield per unit sown area—each reflecting the scale and stability of production capacity.

Restorative capacity denotes the system’s ability to recover to normal production levels following exposure to external shocks. This study examines restorative capacity across two secondary dimensions: ecological coordination and recoverability. Ecological coordination assesses the degree of alignment between food production processes and environmental systems; a stronger alignment reduces the rigidity of resource and environmental constraints, promoting sustainability. To quantify this coordination, this study applies negative indicators, including pesticide usage per unit sown area, agricultural diesel consumption, fertilizer application rates, agricultural plastic film use, and agricultural water consumption. These indicators offer insight into the ecological demands of food production and its sustainability profile. Recoverability in food production indicates the system’s capability to resume normal production levels following external shocks. This ability is assessed by examining the impact of disasters, ecological protection and restoration efforts, and other contributing factors. Specifically, metrics such as disaster/damage area, soil erosion control area, and crop rotation index are used to gauge the system’s resilience. Additionally, economic growth plays a pivotal role in enabling food production systems to recover from external shocks, representing the underlying vitality of regional food production. This is quantified by the added value of total agricultural output, which serves as a proxy for regional economic growth and its capacity to support recovery.

Transformative capacity in food production refers to the system’s ability to not only withstand unpredictable shocks but also to forge new growth pathways in response. This study conceptualizes transformative capacity through two secondary indicators: diversity and collaboration in food production and innovation in food production. Food production diversity encompasses metrics such as crop diversification, the proportion of feed grain sown area relative to the total grain sown area, and the ratio of output from agricultural services to the overall output in agriculture, forestry, animal husbandry, and fishery sectors. Here, crop diversification is defined as the proportion of non-grain crop sown area to the total crop sown area, reflecting the breadth and adaptability of production. Innovation in food production represents the role of funding and technological support in enhancing the quality and efficiency of production activities. This study includes four primary indicators to measure this dimension: fiscal expenditure on agricultural, forestry, and water affairs; agricultural research expenditure; and the workforce in agricultural science and technology. The latter two indicators—agricultural research expenditure and agricultural science personnel are calculated as follows: Agricultural research expenditure = total research and development expenditure × (agricultural output/total output of agriculture, forestry, animal husbandry, and fishery). Agricultural science and technology personnel =total number of science and technology workers × (agricultural output/total output of agriculture, forestry, animal husbandry, and fishery). Together, these metrics provide a robust depiction of the system’s innovative capacity and its ability to achieve higher production quality and resilience through strategic investments in financial and technological resources.

3.2.2 Explanatory variable.

The core explanatory variable in this study is the agricultural land “three rights separation” policy. Building on the work of Cao ZJ et al. [16]. and Gong MG and Chen SF [17], the commencement of each province’s comprehensive land rights certification and registration marks the initiation of the policy. This approach generates a binary dummy variable for the “three rights separation” policy, coded as 1 for years following the reform’s implementation and 0 for years preceding it. Table 2 provides the sequence and timeline for land certification implementation across the 30 provinces studied.

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Table 2. Start time of confirmation of agricultural land rights and registration in each province.

https://doi.org/10.1371/journal.pone.0313772.t002

3.3 Data sources

Considering data availability and completeness, this study includes 30 provinces in China (excluding Tibet, Hong Kong, Macau, and Taiwan) as the research sample, covering the period from 2005 to 2021. The research data primarily come from the “China Statistical Yearbook,” “China Rural and Agricultural Statistics Yearbook,” “China Science and Technology Statistics Yearbook,” “China Water Resources Yearbook,” “China Rural Operations Management Annual Report,” as well as the National Bureau of Statistics, provincial statistical yearbooks, the EPS database, and the Breck Agricultural Database platform. Missing data were filled using linear interpolation. Descriptive statistics for the main variables are shown in Table 3.

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Table 3. Descriptive statistics of major variables.

https://doi.org/10.1371/journal.pone.0313772.t003

4.1 Measurement and analysis of grain production resilience levels

Based on the grain production resilience evaluation indicator system constructed from Table 1, this paper calculates the resilience levels of grain production in 30 provinces in China from 2005 to 2021 as shown in Table 4. Due to space limitations, only the years 2005, 2009, 2013, 2017, and 2021 are listed here.

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Table 4. Comprehensive scores of China’s grain production resilience.

https://doi.org/10.1371/journal.pone.0313772.t004

Temporally,during the observation period,the resilience level of grain production in China generally showed an upward trend,with the national average increasing from 0.1858 in 2005 to 0.3082 in 2021, a growth of nearly 1.66 times. However,the overall resilience level of grain production remains not high,with significant room for growth. Since the new century, to ensure national food security, China has abolished the agricultural tax and has been continuously increasing subsidies for grain production, which has enhanced farmers’ enthusiasm for grain cultivation. Since the 18th National Congress, food security has been elevated to a national security strategy, and strategies such as storing grain in the land and technologies,as well as initiatives like high-standard farmland construction,enhancement of agricultural mechanization, and revitalization of the seed industry,have been implemented,which have contributed to the sustained improvement of grain production resilience. Nevertheless, China’s grain production still faces multiple challenges such as resource and environmental constraints, insufficient development of agricultural technology, inadequate farmer enthusiasm for grain cultivation, and extreme climate changes, making the path to enhancing grain production resilience arduous and long.

From the perspective of the three main functional zones for grain production , as illustrated in Fig 1, the resilience levels of these zones followed a general upward trend during the observation period, mirroring the national trajectory, though significant disparities were observed between zones. Overall, the distribution pattern was as follows: major production areas > balanced production and marketing areas > major marketing areas. The resilience of grain production in major production areas consistently surpassed that of both major marketing areas and balanced production and marketing areas, as well as the national average. Furthermore, the resilience gap between major production areas and the other zones has continued to widen, largely due to the richer grain production resources and the preferential allocation of policies and technologies to these areas, aligned with their designated function. While the resilience of grain production in balanced production and marketing areas exceeds that of major marketing areas, it remains below the national average.

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Fig 1. 2005–2021 Development trends in grain production resilience in China’s three major functional zones.

https://doi.org/10.1371/journal.pone.0319387.g001

The results shown in Table 4 indicate that in 2021, Jiangsu Province led the nation in grain production resilience, achieving a level of 0.5439. Shandong, Heilongjiang, and Henan followed closely, each surpassing a resilience level of 0.5, with only marginal differences among them. On the opposite end, Qinghai Province recorded the lowest resilience at just 0.1010, while Hainan and Ningxia ranked second and third lowest, with scores of 0.1077 and 0.1688, respectively. Additionally, Tianjin, Shanghai, and Fujian also reported resilience scores below 0.2, highlighting significant potential for improvement. Compared to 2005, all provinces showed growth in resilience, with Jiangsu experiencing the most substantial increase at 246.52%,while Qinghai saw the smallest increase at 112.83%. Provinces with resilience growth rates exceeding 200% included Jiangsu, Heilongjiang, and Guangdong. Fifteen provinces exhibited growth rates be-tween 150% and 200%, while the remaining 12 had rates below 150%. These results illustrate that, while the resilience of grain production in China has improved rapidly from 2005 to 2021, considerable disparities between provinces persist.

4.2 Baseline regression results

Table 5 presents the estimated effects of the separation of three rights of agricultural land on grain production resilience. The findings show that, after controlling for fixed individual and time effects, the separation of three rights of agricultural land positively impacted grain production resilience, significant at the 1% level. Specifically, for every 1% increase in the effectiveness of the separation of three rights of agricultural land, grain production resilience improved by 7.9%. Overall, the implementation of these policies has had a favorable effect on enhancing grain production resilience, thereby confirming Hypothesis H1. This suggests that future policy efforts should further explore the separation of three rights of agricultural land reforms to provide stronger institutional support for improving grain production resilience.

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Table 5. Baseline regression model results.

https://doi.org/10.1371/journal.pone.0313772.t005

4.3 Parallel trends test

The reliability of the DID model estimation results hinges on passing the parallel trends test, which requires no significant differences in regression coefficients in the years preceding the implementation of the “three rights separation” policy, while significant differences should emerge post-implementation. This study applies the event study method proposed by Jackson L S et al. [34]. and employs Formula (2) to conduct the test. To mitigate multicollinearity and potential interference from other policies, this paper follows the methodology of Xu W and Zhang JH [35], shortening the sample period and using panel data from 2010 to 2018 for the parallel trends test, with 2013 as the baseline group.

In Fig 2, the changing trend of the regression coefficient is illustrated. The corresponding estimated parameters are represented by round dots, while the 95% confidence intervals are indicated by the vertical lines. On the horizontal axis, the value –4 represents four years prior to the policy’s implementation, 0 indicates the initial year of implementation (2014), and 4 represents the fourth year after implementation. The results reveal that, prior to policy implementation, the estimated policy coefficients remain close to zero, showing no significant differences in the interaction term estimates before 2014. Post-implementation, the confidence intervals for these estimates consistently exceed zero, indicating significant differences. These findings confirm that the parallel trends test has been successfully passed, affirming the reliability of the baseline regression results and demonstrating that the implementation of the agricultural land “three rights separation” policy significantly enhances grain production resilience.

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Fig 2. Parallel trend test dynamic effect plot.

https://doi.org/10.1371/journal.pone.0319387.g002

4.4 Robustness tests

4.4.1 Placebo test.

To ensure that the baseline regression results are not influenced by other policies or unobservable random factors, a double-random counterfactual estimation framework was constructed based on the timing and location of the separation of three rights of agricultural land implementation. This test was used to assess the authenticity of the effects generated by the randomly assigned the separation of three rights of agricultural land. As shown in Fig 3, following 500 randomly generated policy shocks, the simulated estimation coefficients for grain production resilience were found to follow a normal distribution with a mean close to 0. The actual estimated coefficient of 0.073, indicated by the vertical dashed line, stands out as an outlier within the distribution of simulated coefficients. This finding suggests that the positive effect of the separation of three rights of agricultural land on grain production resilience is not a random occurrence, thereby affirming the robustness of the study’s conclusions.

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Fig 3. Placebo test plot.

https://doi.org/10.1371/journal.pone.0319387.g003

4.4.2 Substitution of the dependent variable.

Grain total output, as a critical indicator of both grain production resilience and food security, was used to substitute the dependent variable in Formula (1) for a robustness check, employing the variable substitution method. As shown in column (1) of Table 6, the regression coefficient remains significantly positive, further confirming the robustness of the model.

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Table 6. Robustness tests.

https://doi.org/10.1371/journal.pone.0313772.t006

5.1 Mechanism analysis

The empirical results indicate that a significant positive impact on improving grain production resilience has been caused by the separation of three rights of agricultural land. It is suggested by theoretical analysis that this effect occurs through a transmission mechanism, primarily by facilitating land transfers and increasing agricultural productive investments. In the following section, the internal mechanisms by which the separation of three rights of agricultural land enhances grain production resilience will be further investigated.

To test these mechanisms, a two-step approach has been adopted in this paper, following the method outlined by Jiang T [36] to analyze the mediating effect. In the first step, the core independent variable is regressed on the dependent variable, as shown in column (1) of Table 5. In the second step, the core independent variable is regressed on the mediating variable. If significance is found in the second regression, the mediating effect is confirmed, supported by the theoretical analysis of the mechanism. The results of this mechanism test are presented in Table 7.

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Table 7. Mechanism analysis.

https://doi.org/10.1371/journal.pone.0313772.t007

To examine the mechanism related to land transfer, this paper uses the proportion of land transferred in a given province relative to the total contracted land area in that year to quantify the level of land transfer. By substituting this variable into the baseline regression model (1), the results, shown in column (1) of Table 7, reveal a coefficient of 0.175 for the effect of the separation of three rights of agricultural land on land transfer, significant at the 1% level. This indicates that the policy’s implementation has substantially promoted land transfer. Motivated by land transfer incentives, farmers with low willingness or profitability in grain farming activities transfer the management rights of their farmland to larger-scale production and operation entities. This ensures that the overall grain sowing area does not decline, improves land use efficiency and output efficiency, and further enhances the resilience of grain production in the face of external shocks. Land transfer fosters specialized division of labor, increasing agricultural production efficiency and risk resistance. Specialized division of labor enables better responses to market fluctuations and natural disasters, thereby strengthening the resilience of the grain production system. After land transfer, operators have greater motivation and resources for technological innovation, such as introducing efficient planting techniques and pest and disease control methods, to improve the quality and yield of grain production. Additionally, land transfer promotes innovation in management, such as through strategic planting plans and efficient supply chain management, thereby enhancing the transformative capacity of the grain production system. Furthermore, the large-scale operators formed after land transfer can more easily access financial instruments like green credit and green insurance, providing sustainable financial support for grain production. This addresses financing challenges in the grain production process, reduces risks associated with grain production and operation, and strengthens the resilience of grain production.

In investigating the mechanism of agricultural productive investment, this study utilizes the grain machine-harvested area in a given year from a specific province as a proxy for grain productive investment . By substituting this variable for the dependent variable in the baseline regression model (1), a re-estimation is conducted. The results, presented in column (2) of Table 7, show a significantly positive coefficient for the effect of the separation of three rights of agricultural land on grain productive investment. This finding suggests that the implementation of the policy substantially stimulates investment in grain production. Agricultural productive investments can be utilized to purchase advanced agricultural technologies and equipment, such as mechanized farming equipment, drone-based pest control, smart irrigation systems, and precision agriculture technologies. These technologies enhance the stability and disaster resilience of grain production. Additionally, agricultural productive investments can be directed towards the research, development, and promotion of new grain production techniques, thereby improving grain production efficiency and quality. For instance, biotechnology can cultivate higher-yielding and more disease-resistant crop varieties, while information technology enables intelligent management of grain production. Moreover, investing in infrastructure for farmland water conservancy, such as constructing irrigation canals, drainage systems, windbreaks, and mechanized farming roads, can effectively mitigate the impact of natural disasters on grain production. Furthermore, increasing investments in farmer education and training enables farmers to master advanced cultivation techniques, management methods, and market information, thus enhancing their management of grain production. On the other hand, when grain production faces external shocks, farmers can respond and make decisions more swiftly and scientifically, thereby enhancing the resilience of grain production.

5.2 Heterogeneity analysis

5.2.1 Heterogeneity in natural geographic location.

Given the variations in natural resource endowment, geographic location, and levels of economic development, the impact of the separation of three rights of agricultural land on grain production resilience may differ across regions. This study categorizes China’s 30 provinces (including municipalities and autonomous regions) into three regions—eastern, central, and western—to explore the heterogeneity based on geographic location. The results, displayed in columns (1) to (3) of Table 8, indicate that the policy’s effect in the central region is significantly positive, whereas the estimated coefficients for the eastern and western regions are not statistically significant. This suggests that the separation of three rights of agricultural land has notably enhanced grain production resilience in the central region. A possible explanation for this is that the western region, with its less favorable resource endowments for grain production and lower levels of economic development, experiences limited effects of the separation of three rights of agricultural land on agricultural scaling and standardization. In contrast, the eastern region, characterized by a more developed economy and higher land value, tends to prioritize the growth of secondary and tertiary industries over agricultural production. The central region, comprising the largest number of key grain-producing provinces, possesses a stronger agricultural foundation and bears greater political responsibility for ensuring national food security. Consequently, the policy’s impact on promoting land transfers at scale and enhancing agricultural productive investment is more pronounced in this region.

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Table 8. Heterogeneity analysis.

https://doi.org/10.1371/journal.pone.0313772.t008

6.1 Conclusions

Based on the previous research findings, this paper draws the following conclusions:

1. (1) From 2005 to 2021, China’s grain production resilience exhibited a steady upward trend, although the overall level remains low, indicating significant potential for further improvement. Notable disparities exist in grain production resilience across the three major functional zones, following the pattern of major grain-producing areas > balanced production and marketing areas > major grain-marketing areas. In 2021, Jiangsu Province ranked first in the nation for grain production resilience, recording the highest growth among all provinces, with an increase of 246.52%.
2. (2) The separation of three rights of agricultural land has a significantly positive impact on grain production resilience, with notable improvements at the 1% statistical level. The effect of the policy on enhancing grain production resilience is stable and sustainable. After conducting a series of robustness checks,such as substituting the dependent variable and adjusting the sample size—the estimated conclusions remain robust.
3. (3) The mechanism analysis identifies two pathways through which the separation of three rights of agricultural land enhances grain production resilience. First, the policy promotes land transfers, thereby improving resilience. Second, it encourages farmers to increase their investment in agricultural production, which further strengthens resilience.
4. (4) The heterogeneity analysis reveals that the policy’s impact on grain production resilience varies according to China’s natural geographical regions, grain production functional zones, and north-south grain planting patterns. Geographically, the policy exerts a significantly positive effect on grain production resilience in the central region, while its impact in the eastern and western regions is not significant. Regarding functional zones, the policy’s influence is more pronounced in major grain-producing areas. As for the north-south grain planting pattern, the policy positively affects grain production resilience in both regions, with a stronger effect observed in the northern region.

6.2 Discussion

In the context of food security, this article investigates how the separation of the three rights in agricultural land reform impacts the resilience of grain production. The theoretical analysis identifies two mechanisms through which this reform affects resilience: land transfer and agricultural production investment. Utilizing statistical data from 30 provinces in China from 2005 to 2021 and applying a multi-period difference-in-differences (DID) model, the empirical analysis demonstrates a positive up-ward trend in the resilience of China’s grain production over the years, with the separation of the three rights in agricultural land reform contributing to this increase.

Land, as the primary factor in agriculture, is widely recognized as crucial for enhancing grain production. However, its fixed location and stable area inherently limit its potential contribution. Unlike other inputs, institutional factors do not directly impact grain production and agricultural development; rather, they modulate the effectiveness of inputs such as land, capital, technology, and labor. As the core component of land institutions, the agricultural land property rights system influences not only land inputs but also other production factors in agriculture. Thus, examining the impact of property rights reform on grain production within the constraints of agricultural land resources is of critical importance. Building a resilient grain production system is fundamental to mitigating uncertain risks and safeguarding food security. Research on grain production resilience is still in its early stages, with studies remaining limited, particularly regarding the impact of specific policies on resilience. While scholars have explored the concept of ’three rights’ separation within the context of property rights, few have investigated its effects on enhancing grain production resilience and securing food security. This article addresses this gap by leveraging China’s separation of the three rights in agricultural land reform as a quasi-natural experiment to assess the impact of agricultural land property rights reform on grain production resilience. This study offers several contributions: first, it expands the scope of resilience measurement in grain production; second, it provides both theoretical and empirical insights into the influence of three rights separation in agricultural land reform on resilience; and finally, it presents policy recommendations for fully implementing rural property rights reform to strengthen resilience in grain production.

While this study provides valuable insights, several limitations should be noted. First, due to constraints in data availability, the analysis was limited to the provincial level. Additionally, the complex relationship between the separation of agricultural land rights and grain production resilience involves micro-level stakeholders, such as individual farmers, rural households, and agricultural enterprises, which this study does not encompass. Furthermore, the analysis includes mediation tests only on land transfer and agricultural production investment. Future research could benefit from examining the effects of agricultural land rights separation and grain production resilience at the city or county levels within China. Expanding the research focus to encompass micro-level land operators and incorporating additional variables may also offer a more comprehensive understanding of potential mediation and moderation effects.

6.3 Policy recommendations

Based on the research conclusions, this paper offers the following policy recommendations:

1. (1) Governments at all levels should enhance the promotion of confirmation of agricultural land rights policies, elevate the legal status and value of land rights certificates, and increase their recognition in rural markets. Furthermore, efforts should be made to strengthen the protection of land use and property rights, thereby reinforcing farmers’ sense of security and stability regarding land property rights.
2. (2) Governments should expedite the establishment of farmland transfer market centers and information exchange platforms, standardize the operational mechanisms of farmland transfer markets, develop clear regulations for land transfers, ensure the enforcement of contracts, and mitigate moral hazards associated with contract execution. Additionally, improving price formation mechanisms for farmland transfers and reducing transaction costs are essential. These efforts will promote the standardization, scaling, and specialization of grain production, ultimately improving production efficiency.
3. (3) The government should raise awareness among farmers and financial institutions about land contract management rights as collateral. The government should encourage banks at all levels and other financial institutions to explore models of mortgage loans based on agricultural land contracting and management rights, expand financing channels for farmers’ agricultural production, and provide financial support for the expansion of grain reproduction..
4. (4) The government should explore incentive and subsidy models for different scales of grain-producing households in the areas of purchasing grain cultivation machinery, socialized services for grain production, and the construction of small-scale agricultural water conservancy facilities, in order to provide technical support for the resilience of grain production.
5. (5) The government should strongly advocate for green grain production. Efforts should be made to increase the adoption rates of soil testing and formula fertilization techniques, green pest control methods, pest monitoring technologies, and water-saving irrigation systems, thereby ensuring the scientific, precise, and efficient use of production inputs. The costs associated with green grain production technologies can be reduced through measures such as financial subsidies and tax incentives. For instance, the prices of organic fertilizers and eco-friendly pesticides could be decreased.
6. (6) The government must rigorously enforce the arable land protection system. In accordance with the principle of “ensuring no reduction in the quantity, no decline in quality, and no ecological damage to arable land,” the system for safeguarding the quantity, quality, and ecology of arable land should be enhanced. A comprehensive protection assessment system should be established, and the responsibilities of arable land resource supervision departments should be rigorously enforced. The standards for identifying arable land destruction should be clarified, and penalties for destructive behaviors should be increased accordingly. Additionally, innovative models for high-standard farmland construction should be actively explored and promoted, to encourage the participation of agricultural enterprises, cooperatives, family farms, and large-scale grain producers in such projects. Furthermore, regions should be encouraged to develop land reclamation and re-cultivation models that are tailored to local conditions.