Farmland In China Research Articles

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.

Spatiotemporal coupling dynamics and factors influencing soil organic carbon and crop yield in Chinese farmlands

Clarifying the correlation between soil organic carbon (SOC) and crop yield is key to achieving carbon neutrality and ensuring food security. However, owing to the lack of analysis based on large-scale farmland monitoring data and research on deep soil, relevant research has not yet reached a consensus. Here, we based on the monitoring data of 118 sample plots from 21 typical farmland and farmland compound ecosystem stations of the China Ecosystem Research Network (CERN) between 2004 and 2020, the temporal and spatial coupling associations between SOC content and crop yield in 0–20 cm and 0–100 cm soil layers and its factors influencing were determined. The findings revealed that between 2004 and 2020, SOC content in 0–20 cm soil layer, SOC content in 0–100 cm soil layer, and crop yield in typical farmland in China showed a fluctuating upward trend, the average annual growth rates were 0.59 %, 0.27 % and 1.07 %, respectively. The coupling relationship between SOC content and crop yield was not always good in different periods, which varies largely in different geographical divisions. Among the anthropogenic factors, exogenous carbon input can improve the coupling relationship between them by increasing the soil organic carbon content and crop yield, while the effect of less tillage and no tillage is limited. Among the natural factors, temperature, soil bulk density, and farmland type all have an impact on farmland SOC content and crop yield at different significance levels. Each variable had different effects on SOC content and crop yield in typical farmlands in different geographical regions. With deepening soil layer, influence of anthropogenic factors such as exogenous carbon input on SOC content decreases, but it still cannot be ignored. Based on these findings, the study recommends that exogenous carbon input play an important role in soil carbon sequestration and improving crop yield.

Spatial zoning and effect evaluation of county high-standard farmland siting delineation for sustainable cultivated land use in China: A case study in Dali, Shaanxi

High-standard farmland construction is critical for sustainable land use and food security in China. Currently, scientific siting delineation for high-standard farmland at the county level is lacking. Delineation through evaluation and zoning is essential to improve land productivity. This study focuses on Dali County in Shaanxi Province, Fenwei Plain. It analyzes cultivated land changes using the land use transfer matrix and the PLUS. By integrating macro “township-parcel-grid” and micro “farmer” perspective, it establishes a comprehensive evaluation system for high-standard farmland delineation. We delineate construction zones and evaluate potential effect of high-standard farmland. The results reveal that: (1) From 2000 to 2020, the cultivated land area generally decreased. The permanent basic farmland positively contributes to the increase of cultivated land. Land use simulation in 2030 results show that the urgency for land consolidation. (2) The delineated high-standard farmland area in Dali is 85,081 hm2, with comprehensive evaluation index values ranging from 0.2229 to 0.5970, indicating that Dali has the potential for continuous construction of high-standard farmland. (3) This study zones high-standard farmland construction according to the difficulty and time sequence. Delineated high-standard farmland can play potential effect of agglomeration and demonstration, sustainable and coordinated development and grain production capacity increasing. We offer a scientific method for delineating zones of high-standard farmland within county, providing recommendations for sustainable high-standard farmland construction. It serves as a reference for the gradual conversion of all permanent basic farmland to high-standard farmland in China.

Spatiotemporal evolution and driving factors of agricultural land transfer in China.

This paper systematically analyzes the spatiotemporal evolution trends and macroeconomic driving factors of farmland transfer at the provincial level in China since 2005, aiming to offer a new perspective for understanding the dynamic mechanisms of China's farmland transfer. Through the integrated use of kernel density estimation, the Markov model, and panel quantile regression methods, this study finds the following: (1) Farmland transfer rates across Chinese provinces show an overall upward trend, but regional differences exhibit a "U-shaped" evolution characterized by initially narrowing and then widening; (2) although provinces have relatively stable farmland transfer levels, there is potential for dynamic transitions; (3) factors such as per capita arable land, farmers' disposable income, the social security level, the urban‒rural income gap, the urbanization rate, government intervention, and the marketization level significantly promote farmland transfer, while inclusive finance inhibits transfer, and agricultural mechanization level and population aging have heterogeneous impacts. Therefore, to achieve convergence of low farmland transfer regions to medium levels while promoting medium-level regions to higher levels, it is recommended that the government increase support for agricultural mechanization, increase farmers' income and social security levels, and optimize marketization processes and government intervention strategies. The main contributions of this paper are (1) systematically revealing the spatiotemporal evolution patterns of China's farmland transfer and (2) employing panel quantile regression methods to explore the heterogeneous impacts of driving factors, providing more precise and detailed empirical support for the government's formulation of farmland transfer policies.

How does the method of farmland transfer affect the “non-grain” of farmland in China?

IntroductionThe phenomenon of “non-grain” of farmland poses a major threat to food security. Currently, there is still debate about the relationship between farmland transfer and the “non-grain” of farmland. Currently, there is no consensus on the relationship between farmland transfer and the non-grain use of farmland. This article focuses on the evolution of farmland transfer methods, examines the impact of farmland transfer methods on the non-grain use of farmland, and highlights the importance of effectively promoting farmland transfer, curbing the non-grain use of farmland, and ensuring food security.MethodsBased on the China Rural Revitalization Survey (CRRS) data, this paper uses probit and ivprobit models to estimate the causal relationship between farmland transfer methods and the “non-grain” of farmland. Grouped regressions are conducted from three dimensions of geographical environment, village governance, and economic development to test the heterogeneity of the impact of farmland transfer methods. Finally, the pathways of action are analyzed from the perspectives of farmers’ identity transformation and contract signing.ResultsThe organized transfer can significantly reduce the degree of “non-grain” of farmland, and its effect is stronger when the village party secretary has a higher level of education and also serves as the village head. This effect is mainly manifested through increasing the probability of farmers becoming new agricultural operators, joining cooperatives, signing formal contracts, and determining the lease term.DiscussionThe policy implications of this study emphasize that to curb the “non-grain” of farmland and ensure food security, it is important not only to increase the rate of farmland transfer but also to promote the organization of farmland transfer transactions. This includes facilitating the transfer of farmland from inefficient smallholders and cultivating new agricultural operators. Simultaneously, leveraging the supervisory and management role of village collectives can encourage farmers to sign more formal written contracts, clarify the purpose of farmland transfer, and supervise and manage the use of farmland during the subsequent contract execution stage. A limitation of this study is that it relies on cross-sectional data and does not observe the time variation of farmland transfer methods for the same farmers or their long-term impact on the “non-grain” of farmland.

Design and Development of a Side Spray Device for UAVs to Improve Spray Coverage in Obstacle Neighborhoods

Electric multirotor plant protection unmanned aerial vehicles (UAVs) are widely used in China for efficient and precise plant protection at low altitude for low volumes. Unstructured farmland in China has various types of obstacles, and UAVs usually use a detour path to avoid obstacles due to flight altitude limitations. However, existing UAV spray systems do not spray when in obstacle neighborhoods during obstacle avoidance, resulting in insufficient droplet coverage and reduced plant protection quality in the area. To improve the droplet coverage in obstacle neighborhoods, this article carries out a study of side spray technology with an electric quadrotor UAV, and proposes the design and development of a side spray device. The relationship between the obstacle avoidance path of the UAV and the spray pattern of the side spray device and their effect on droplet coverage in obstacle neighborhoods was explored. An accurate measurement method of the relative position between the UAV and obstacles was proposed. Spray angle calculations and nozzle selection for the side spray device were carried out in conjunction with the relative position. A rotor wind field simulation model was designed based on the lattice Boltzmann method (LBM), and the spatial layout of the side spray device on the UAV was designed based on the simulation results. To explore suitable spray patterns for the side spray device, comparative experiments of droplet coverage in obstacle neighborhoods were carried out under different environments, spray patterns, and flight parameter combinations. The relationship between the flight parameter combinations and the distribution uniformity of droplets and the effective swath width of the side spray device was explored. The experimental results were analyzed by an analysis of variance (ANOVA) and a relationship model was obtained. The results showed that the side spray device can effectively improve droplet coverage in obstacle neighborhoods compared to a device without side spray using the same flight parameter combinations. The effective swath width in obstacle neighborhoods can be increased by a minimum of 6.35%, maximum of 35.32%, and average of 15.25% using the side spray device. The error between the predicted values of the relational model and the field experiment results was less than 15%. The results verify the effectiveness and rationality of the method proposed in this article. This study can provide technical and theoretical references for improving the plant protection quality of UAVs in obstacle environments.

Re-identifying farmland carbon neutrality gap under a new carbon counting and the framework of regional interactions in China

The farmland ecosystem, with its numerous material cycles and energy flows, is an important part of the carbon cycle in terrestrial ecosystems. Focusing on the carbon neutrality of farmland is meaningful for mitigating global warming and serving national low-carbon strategies. This study enriches the carbon accounting items of farmland and establishes a new research framework to check the carbon neutrality of farmland from the aspect of regional interactions and, subsequently, the inequality among China's provinces. The results revealed that there is still a great gap in the capability of China's farmland to reach carbon neutrality, with a gap value of up to 10,503 × 104 t C. All of the provinces presented net carbon emissions, and the per unit area carbon neutrality gaps showed spatial regularity decreasing from the coastal regions to the inland areas. Anthropogenic carbon emissions on farmland played a dominant role compared with soil organic carbon. Five provinces had reduced interior-regional carbon emissions through grain trade, and the amounts were especially high for developed regions, such as Guangdong, Zhejiang, Beijing, Shanghai and Jiangsu. Sixteen provinces gained external carbon emissions through trade; these were the less developed regions located mainly in the north, such as Inner Mongolia, Hebei, Jilin, Heilongjiang and Xinjiang. Under regional inequality, 15 provinces added to the net amount of the carbon emissions generated in external regions, with China's megacities adding the highest percentage, especially Beijing, with 389.95 % compared with its original emissions. Inequality showed that most provinces had a moderate status. Sichuan and Hunan experienced weak advantages, and six provinces had disadvantages. Therefore, constructing compensation and trade-based rights and responsibilities traceability mechanisms is important.

Spatial Mapping of Soil CO2 Flux in the Yellow River Delta Farmland of China Using Multi-Source OpticalRemote Sensing Data

The spatial prediction of soil CO2 flux is of great significance for assessing regional climate change and high-quality agricultural development. Using a single satellite to predict soil CO2 flux is limited by climatic conditions and land cover, resulting in low prediction accuracy. To this end, this study proposed a strategy of multi-source spectral satellite coordination and selected seven optical satellite remote sensing data sources (i.e., GF1-WFV, GF6-WFV, GF4-PMI, CB04-MUX, HJ2A-CCD, Sentinel 2-L2A, and Landsat 8-OLI) to extract auxiliary variables (i.e., vegetation indices and soil texture features). We developed a tree-structured Parzen estimator (TPE)-optimized extreme gradient boosting (XGBoost) model for the prediction and spatial mapping of soil CO2 flux. SHapley additive explanation (SHAP) was used to analyze the driving effects of auxiliary variables on soil CO2 flux. A scatter matrix correlation analysis showed that the distributions of auxiliary variables and soil CO2 flux were skewed, and the linear correlations between them (r < 0.2) were generally weak. Compared with single-satellite variables, the TPE-XGBoost model based on multiple-satellite variables significantly improved the prediction accuracy (RMSE = 3.23 kg C ha−1 d−1, R2 = 0.73), showing a stronger fitting ability for the spatial variability of soil CO2 flux. The spatial mapping results of soil CO2 flux based on the TPE-XGBoost model revealed that the high-flux areas were mainly concentrated in eastern and northern farmlands. The SHAP analysis revealed that PC2 and the TCARI of Sentinel 2-L2A and the TVI of HJ2A-CCD had significant positive driving effects on the prediction accuracy of soil CO2 flux. The above results indicate that the integration of multiple-satellite data can enhance the reliability and accuracy of spatial predictions of soil CO2 flux, thereby supporting regional agricultural sustainable development and climate change response strategies.

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."

Two Novel Alkaliphilic Species Isolated from Saline-Alkali Soil in China: Halalkalibacter flavus sp. nov., and Halalkalibacter lacteus sp. nov.

The degradation of farmland in China underscores the need for developing and utilizing saline-alkali soil. Soil health relies on microbial activity, which aids in the restoration of the land's ecosystem, and hence it is important to understand microbial diversity. In the present study, two Gram-stain-positive strains HR 1-10T and J-A-003T were isolated from saline-alkali soil. Preliminary analysis suggested that these strains could be a novel species. Therefore, the taxonomic positions of these strains were evaluated using polyphasic analysis. Phylogenetic and 16S rRNA gene sequence analysis indicated that these strains should be assigned to the genus Halalkalibacter. Cell wall contained meso-2,6-diaminopimelic acid. The polar lipids present in both strains were diphosphatidyl-glycerol, phosphatidylglycerol, and an unidentified phospholipid. The major fatty acids (>10%) were anteiso-C15:0, C16:0 and iso-C15:0. Average nucleotide identity and digital DNA#x2013;DNA hybridization values were below the threshold values (95% and 70%, respectively) for species delineation. Based on the above results, the strains represent two novel species of the genus Halalkalibacter, for which the names Halalkalibacter flavus sp. nov., and Halalkalibacter lacteus sp. nov., are proposed. The type strains are HR 1-10T (=GDMCC 1.2946T = MCCC 1K08312T = JCM 36285T), and J-A-003T (=GDMCC 1.2949T = MCCC 1K08417T = JCM 36286T).

Effects of antimony on the soil enzymes, microbial, and rhizobial activity of legumes

ABSTRACT Leguminous farmland in China is severely polluted by antimony. Here, to explore the effects of antimony stress on rhizobia and soil microorganisms in leguminous plants, mung beans, kidney beans, and peanuts were grown in soil with different concentrations of Sb3+, Sb5+, and Sb3++Sb5+. Antimony had a promotional effect on soil sucrase and catalase activities and an inhibitory effect on urease activity. The effects of Sb3+ on sucrase, catalase, and urease activities were 3.3–11.1, 1.27–1.29, and 1.24–3.05 times those of Sb5+, respectively. Antimony reduced the rhizobial activity by 20.63–57.84%, with the inhibitory effect positively related to the antimony content. Additionally, the inhibitory effect of Sb3+ was 1.10–2.22 times that of Sb5+. This inhibition decreased the total nitrogen and ammonia nitrogen content in the soil. However, the decrease in Sb3+ was 0.46–1.54 times that of Sb5+. Sb3+ significantly altered the microbial activity.

Spatial Process Analysis of the Evolution of Farmland Landscape in China

Accurately identifying the patterns of evolution in farmland plays an important role in optimizing farmland management. The aim of this study is to classify the evolution patterns of farmland in China and explore related mechanisms, providing a reference for constructing a systematic farmland management plan. Using land cover data from five periods in China, nine types of farmland evolution process are described and identified based on landscape process models. We analyzed these processes’ spatiotemporal dynamics and, by examining regional variations, achieved a zoned mapping of China’s farmland evolution. In this study, we combined natural and socioeconomic factors to analyze the mechanisms driving the evolution of farmland landscapes in China. The results indicated that from 1980 to 2020, areas of both lost and restored farmland showed a trend of first increasing and then decreasing, while the total area of farmland fluctuated. The remaining farmland types consisted mainly of core and edge. Their distribution was similar to that of the major agricultural regions in China. Expansion was the main means of farmland restoration. Farmland fragmentation was widespread, and, over time, it became increasingly severe. Shrinkage and subdivision dominated the farmland fragmentation. Altitude and slope had the greatest impact on the evolution patterns of farmland. Increasing urban industrialization and an increase in population density led to an increase in the demand for food production, which placed greater demands on the farmlands in the region. The farmland evolution pattern is a result of the interactions among multiple factors.

Experimental archaeological study in China: implications for reconstruction of past manuring and dietary practices indicated by δ15N values of Setaria italica and Panicum miliaceum

Understanding the crop management practices of millet agriculture is pivotal for comprehending the development of Chinese civilization. Recent studies have indicated that organic manuring plays a crucial role in ensuring sustainable millet cultivation on the Loess Plateau. However, uncertainties still exist regarding how manuring practices impact the δ15N values of C4 millets compared to C3 cereals. Furthermore, inadequate information on crop δ15N at archaeological sites has led to controversial interpretations of animal and human diets. In this study, we present new findings from an experimental archaeological research conducted in actual loess farmland in China to explore the potential range of variability in grain δ15N values of millets. Our results demonstrate that animal manure significantly increases Setaria and Panicum grain δ15N values, ranging from 2.7 to 9.3‰. Considering trophic enrichment effects on nitrogen isotopes, humans consuming manured millets may yield values ranging from 5.7 to 12.3‰, suggesting alternative explanations for high δ15N values other than animal protein consumption. Opposite to the general hypothesis, the grain δ15N values are systematically lower than those of leaves. The difference between the values of Setaria and Panicum and the process of manure influencing the grain δ15N values are also discussed. Our study provides novel insights into the nitrogen stable isotopic indicator of millet manuring and will serve to set reconstructions of past manuring and diet practices in northern China on a firmer foundation.

The shape of reactive nitrogen losses from intensive farmland in China

Reactive nitrogen (Nr) pollution has changed radically accompanied by severe intensive farming. This pollution further contributes to ecological degradation and climate warming. Despite this recognition, little is known about the spatial pattern of various Nr loss from croplands and corresponding environmental costs. Here, we identified the major pathway of Nr loss based on provincial estimates in 2008 and 2018, and validated by synchronous observation of ammonia volatilization, N runoff and N leaching using historical literature synthesis. We also evaluated environmental costs at provincial scale and detected the influence factors that dominating the pollution swapping among different Nr forms. Our results show that the total Nr loss was 6.28 ± 1.81 and 5.56 ± 2.30 Tg N yr−1 for Chinese croplands in 2008 and 2018. Ammonia volatilization, which accounted for more than half of the total Nr at the national scale, was proven to be the major Nr loss for two-thirds of the provinces and 80 % of the field observations. The contribution of runoff, which is dominant by precipitation, soil clay content and CEC, was gradually smaller than that of leaching from southeast to northwest. Ammonia and nitrous oxide contributed of 59.3 % ∼ 65.4 % of TNr but 80.9 % ∼ 81.5 % of total environmental damage caused by Nr in China. The use of nitrification inhibitors and straw return indicated pollution swapping among various Nr forms. This study emphasizes that the future practices to reduce total Nr loss need to account for local environmental conditions and have pollution swapping in sights.

Evaluating the potential of agri-environmental measures (AEM) in mitigating biodiversity loss due to land consolidation in China: Understanding the function of linear habitats

Semi-natural habitats (SNHs) surrounding agricultural fields contribute significantly to biodiversity in agricultural landscapes. SNHs can be divided into large habitat patches such as contiguous patches of forests, and smaller, interspersed linear habitat types such as grassy field margins. Traditional small-holder agricultural farmlands in China, replete with rich linear habitats, are notably beneficial for biodiversity. However, as these farmlands undergo consolidation to enhance the efficiency of machinery, linear habitats are being removed, a process that could adversely affect biodiversity. Appropriate agri-environmental measures (AEM), such as the restoration of field margins via strategic planting, could serve as an effective countermeasure to maintain biodiversity in consolidated land. This paper discusses how biodiversity monitoring can aid in evaluating the impact of land consolidation and the efficacy of AEM in China, from species richness and species composition perspectives. The paper also discusses the function of linear habitats and how they interact with large habitat patches in promoting biodiversity, while noting that outcomes are likely to vary among taxa. Long-term, multiple-taxa and comprehensive assessments are recommended in further studies, and a collaborative approach that involves multiple stakeholders is essential to ensure a success implication of AEM in China.

Spectral Heterogeneity Analysis and Soil Organic Matter Inversion across Differences in Soil Types and Organic Matter Content in Dryland Farmland in China

Soil organic matter (SOM) plays an important role in agricultural production and arable land quality improvement. Hyperspectral technology enables frequent surveys over large areas. In this study, we explored the spectral heterogeneity of differences in soil types and SOM content, and proposed a method for measuring SOM content in large areas using spectroscopy. The results indicate regional variations in factors affecting soil spectral absorption peaks, with noticeable latitudinal disparities. The first-order differential partial-least-squares method provided the best prediction for the SOM inversion. The coefficient of determination (R2) for the SOM inversion model was 0.93, and the root mean square error (RMSE) was 3.42, with an 8.49 g/kg difference in the SOM content. When the difference in SOM content fell between 8 and 15 g/kg, the inversion effect model performed best. The optimal model R2 exceeded 0.95, and the RMSE was less than 5. The comprehensive analysis showed that the organic matter content was an important factor affecting the SOM content estimate and must be considered in the real process. In addition, it is crucial to categorize soil samples on the basis of distinct soil types while maintaining a consistent range of SOM content within the same soil type, ideally between 8 and 15 g/kg. Subsequently, the first-order differential partial least squares method is applicable. These results are expected to contribute to the acquisition of high-quality information on variations in the SOM of complex large-scale areas.

Analysis of the Current Situation of Medium and Low Yield Fields in China

The area of medium to low yield farmland in China is huge and widely distributed. As a strategic reserve farmland resource, it is of great significance for ensuring food security. This article systematically reviews the problems of declining fertility, organic matter content, and biodiversity in China's medium and low yield fields, and clarifies the focus on the development of ecological improvement materials in the future. This helps to explore the path to improve green, high yield, and efficient production capacity in low to medium yield fields, and promote the achievement of food security and sustainable development goals.

Discussion on the Current Situation and Future Development of Unmanned Smart Farmland

At present, unmanned smart farmland in China is in the early stage of demonstration and promotion, and technological research mainly focuses on single machine intelligent control technologies such as autonomous driving and precision operation. However, related technologies such as multi machine collaboration, host machine and machine operation collaboration, as well as collaboration between agricultural production scenarios and autonomous agricultural machine operation, are insufficient. Building unmanned smart farmland is an important way to alleviate the shortage of rural labor and promote the modernization of agriculture and rural areas. It provides precise planting, visual management, and intelligent decision-making for agricultural production, and also allows agriculture and rural areas to share the achievements of technological development in the era.

The battle of crops: unveiling the shift from grain to non-grain use of farmland in China?

ABSTRACTChina is issuing a warning regarding the ‘unprecedented’ hurdles it faces in safeguarding its food security. The substantial conversion of farmland for non-grain cultivation is exacerbating the situation, necessitating urgent investigation into the underlying causes. Nonetheless, previous studies have revealed a dearth of village-level analysis and have been marred by a bias stemming from econometric methodologies. To remedy this, the present paper employs a sophisticated approach combining econometric modelling and machine learning techniques to unravel the intricate driving forces at the village level. The study yields three principal findings. Firstly, the availability of farmland, poverty incidence, and the age of village leaders exert a detrimental influence on non-grain use of farmland (NGUF). Secondly, a conglomerate of factors, such as the aging rural workforce, income levels, positively impact the planting of non-grain crops, with remarkably increasing effects. Finally, it is pivotal to acknowledge that the influencing factors display sensitivity to the spatial scale examined. Village-level research provides a comprehensive overview, transcending individual household decisions. Collectively, this study underscores the indispensability of incorporating the underlying principles into policy formulation. Township and county authorities should craft guidelines, policies, and regulations in accordance with the ascertained village-level drivers, rather than relying solely on household-level determinants.

Roles of historical land use/cover and nitrogen fertilizer application changes on ammonia emissions in farmland ecosystem from 1990 to 2020 in China

In the past decades, China has witnessed significant changes in its land use/land cover (LULC) pattern. These changes have led to a direct impact on ammonia (NH3) emissions in soil background, and indirectly affected the total nitrogen fertilizer (N-fertilizer) application, crop planting amount and the resulting straw mass through the changes of cropland area. Great changes have also taken place in the amount and structure of fertilizer application in China, which affects the NH3 emissions from farmland ecosystems caused by N-fertilizer application. The aforementioned changes have led to significant alterations in NH3 emissions from China's farmland ecosystems over the past 30 years. The process of these changes remains to be analyzed, and the contributions of LULC changes and N-fertilizer application in this process are yet to be assessed. This study aims to investigate the NH3 emission changes and spatiotemporal variation characteristics from farmland ecosystems during 1990 and 2020 due to the LULC changes. Additionally, the study employs scenario analysis method to discuss the effects of LULC changes and N-fertilizer application changes on NH3 emissions in farmland ecosystems. Results indicate that there is evident spatiotemporal heterogeneity in China's LULC pattern, particularly in eastern China. The southeast region is predominantly characterized by the conversion of cropland into construction land. Moreover, some regions such as Northwest China and Northeast China have experienced the conversion of other land types into cropland, significantly influenced by national development policies. From 1990 to 2020, the national NH3 emissions from farmland ecosystem range from 3294.75 Gg to 4064.20 Gg. NH3 emissions and their interannual variation in farmland ecosystems exhibit significant differences across various regions. The regions with higher contributions to NH3 emissions in farmland ecosystems are East China, Central China, and North China, accounting for 25.32 %–37.26 %, 18.85 %–22.46 % and 11.24 %–18.50 % of the total emissions, respectively. NH3 emissions in each region are influenced by cropland area, N-fertilizer application, and regional development characteristics. Compared to LULC changes, changes in N-fertilizer application have a more pronounced impact on NH3 emission changes in farmland ecosystems. From 1990 to 2020, the contribution (increase or decrease) of N-fertilizer application changes to NH3 emission changes in farmland ecosystems in China ranges from 0.11 % to 16.61 %, while the contribution (increase or decrease) of LULC changes ranges from 0.47 % to 2.38 %. South China demonstrates a unique situation regarding the influence of LULC changes. This region has a relatively small cropland area, and fluctuations in cropland area significantly affect NH3 emissions in farmland ecosystems. The influence of policies is evident. From the changes in cropland area in Northwest China and Northeast China to changes in N-fertilizer application, policy changes have consistently impacted the changes in NH3 emissions in China's farmland ecosystems. From “soft policies” involving encouragement and guidance to “hard policies” encompassing the establishment of necessary targets, the degree of strictness in policy directly affects the timeliness of policies effectiveness. The results of this study indicate that reducing the application of N-fertilizers is the primary approach to reducing NH3 emissions in China's farmland ecosystems. In terms of policy guidance, compared to implementing structural and pathway adjustments, implementing clear total control of fertilizer usage is a timely and effective choice for reducing NH3 emissions.