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One of the effective ways to crack the "Three Rural Issues" and promote rural revitalization is to improve agricultural labor productivity (ALP). However, at this stage, improving China's ALP is still facing many obstacles and bottlenecks. Promoting migrant workers returning home for entrepreneurship is an important breakthrough point for solving this problem. This paper regards the pilot policy of migrant workers returning home for entrepreneurship as a quasi-natural experiment and empirically investigates the influence of migrant workers returning home for entrepreneurship on ALP and explores its potential mechanism and heterogeneity using county area panel data from 2011–2019. It found the following: Firstly, the policy of migrant workers returning home for entrepreneurship significantly increases ALP. Secondly, migrant workers returning home for entrepreneurship indirectly leads to a rise in ALP through the promotion of agricultural mechanization production. Thirdly, the heterogeneity test demonstrates that migrant workers returning home for entrepreneurship purposes have a significant influence in enhancing ALP in the eastern areas, plains areas and non-agricultural strong areas. The findings of this paper not only provide an important real-world basis for the government to further support migrant workers returning home for entrepreneurship but also provide useful policy insights for the modernization and development of agriculture and rural areas. [ABSTRACT FROM AUTHOR]

The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world's longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km2 delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km2 delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km2·a−1 (0.96% a−1 in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a−1 in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a−1), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a−1) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years. [ABSTRACT FROM AUTHOR]

The conflict between agricultural production and environmental protection, especially vegetable production, is one of the world's most prominent concerns. The acceptance degree and possible response of new agricultural operation subjects, represented by Farmers Professional Cooperatives (FPCs), to green production policies are a core issue that must be considered when designing environmental policies in the future. Based on field survey data of 192 FPCs of vegetables in Shanghai, China, this paper uses a choice experiment method to test the willingness of cooperatives to adopt green production behaviors under different policy settings and to identify the differences under different operation scales. The results show that both mandatory policies and incentive policies have an impact on the willingness of cooperatives to adopt green production behaviors, but significant differences exist among FPCs of different operation scales. Specifically, the willingness of large-scale FPCs to adopt green production behavior is affected by key technology training and income subsidies, whereas the willingness of small-scale FPCs is only affected by income subsidies; the willingness of medium-scale FPCs is simultaneously affected by key technology training, income subsidies, and penalties. Therefore, when formulating relevant policies in the future, policy-makers should consider local conditions, including the endowment heterogeneity of the production and operation subjects, so as to enhance the level of green production. [ABSTRACT FROM AUTHOR]

Land consolidation has become an organized and widely implemented project in rural areas. However, research remains somewhat scarce on the contributing mechanism of land consolidation to farmer income in developing countries. Using provincial panel data from China, this study employs a fixed effects model to analyze the influence of high-standard farmland construction on farmer income and underlying mechanisms. Results suggest that the implementation of high-standard farmland construction can significantly augment farmer income. Reduction in agricultural production cost, improvement in agricultural management benefit and increase in non-farm income have led to the boost in income. The relationship between income and high-standard farmland construction exhibits regional disparities, with the most significant impacts concentrated in economically developed areas and low relief degree areas. Our findings suggest that it is imperative for the Chinese government to persistently promote the establishment of high-standard farmland, and further enhance its positive influence on advancing agricultural cost-effectiveness and expanding non-farm income channels for farmers. [ABSTRACT FROM AUTHOR]

Based on the panel data of provincial units in China from 2000 to 2020, this paper uses the entropy method to calculate agricultural environmental regulation level in China from the perspectives of afforestation projects, water conservancy projects and environmental protection projects. Then, this paper calculates agricultural non-point source pollutant emissions in China by using the unit survey and evaluation method, and calculates agricultural green productivity growth in China by using the SBM directional distance function and Luenberger productivity index. On this basis, the influence of environmental regulation on agricultural green productivity growth in China and its mechanism are empirically analysed. The results show that:(1) During the sample period, agricultural environmental regulation level and agricultural green productivity growth increased significantly, while the emission density of agricultural non-point source pollution decreased significantly; (2) On the whole, environmental regulation significantly promoted agricultural green productivity growth in China, which was mainly reflected in the promotion of agricultural green technology progress change; (3) Environmental regulation can significantly promote agricultural green productivity growth in China through the channel of agricultural innovation investment. The innovation of this paper lies in the measurement of agricultural environmental regulation, and the analysis of the moderating effect of agricultural innovation investment on the impact of environmental regulation on agricultural green productivity growth in China. The research conclusions of this paper verify the 'Porter Hypothesis' theory in the field of agriculture, and have guiding significance for China to promote agricultural green productivity growth by relying on environmental regulation. [ABSTRACT FROM AUTHOR]

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." [ABSTRACT FROM AUTHOR]

Large-scale management is the key to realizing long-term agricultural growth in smallholder countries. Land-scale management and service-scale management are two forms of agricultural large-scale management. The former is committed to changing the small-scale management pattern, but the latter tends to maintain it. There has been a lack of discussion and controversy about the relationship between the two. From the perspective of market maturity, this paper explores whether the two are complementary or mutually exclusive and how their complementary or mutually exclusive relationship affects agricultural green productivity. The results show the following: Land-scale management and service-scale management are complementary, not superficially contradictory. The benign interaction between the two has a consistent improvement effect on green productivity in both the short and long term, which has spatial spillovers appearing in the long term. The reasons are as follows: The farmland rental market can reverse the inhibitory effect of the current low-maturity outsourcing services market on green productivity. The outsourcing services market can delay the arrival of the inflection point beyond which expansion of farmland rental transactions reduces green productivity, and amplify the positive effect of farmland rental on it. Although the degree of benign interaction between the two forms of large-scale management has gradually increased in recent years, it is still low overall. Agricultural large-scale management in China is still in the stage driven by land-scale management. Smallholder countries such as China need not worry prematurely about which large-scale management path to take, and they should treat both forms of large-scale management with an equal perspective to accelerate the high-level interaction between them. [ABSTRACT FROM AUTHOR]

Developing green and low-carbon agriculture is an important and effective way to promote farmers' income growth. Given the country's "dual carbon" goal, the study of the impact of green and low-carbon agriculture on the income of farmers in ethnic minority areas is crucial for China to achieve the goals of socialist modernization and common prosperity. Taking Y Town, Zhijin County, Guizhou Province as an example, this paper uses the OLS regression method to empirically study the impact of green and low-carbon agricultural production methods on the income of farmers in ethnic minority mountainous agricultural areas based on the field survey data of 881 farmers. The regression results indicate that there is a positive correlation between green and lowcarbon agricultural production and the household income levels of farmers; adopting green and low-carbon agricultural production technologies can effectively promote the growth of farmers' household income. In addition, education level, health status, and the new rural social pension insurance have all had a significant effect on the income of rural households, however, due to the difficulty in establishing trust relationships, agricultural service outsourcing has reduced the household income level of farmers. As an example, the land transfer behavior in Y Town has no significant effect on increasing farmers' incomes. Finally, it is recommended to increase fiscal and financial support as well as effectively enhancing farmers' policy awareness and perception of green and low-carbon agricultural production technologies by improving farmers' general trust and institutional trust by strengthening farmers' agricultural education and skills training while cultivating technology-based farming. At the same time, it is necessary to break the geographical restrictions on land transfer scale and achieve moderate-scale land management while promoting the use and adoption of green and low-carbon agricultural production technologies, thereby improving agricultural production efficiency and product quality, and increasing the sustainable growth of farmers' income. The main contribution of this study is to expand the research scope of green and low-carbon agriculture to ethnic minorities and mountainous agricultural areas. [ABSTRACT FROM AUTHOR]

Based on panel data from 2010 to 2020 of 151 A-share listed food-related enterprises in China, this research uses a fixed-effect model to analyse the impact of digital transformation on total factor productivity (TFP) in food--related enterprises. Our findings indicated that digital transformation has a positive and significant catalytic effect on TFP improvement in food-related enterprises. The mechanism test revealed that both cost-saving and innovation capacity enhancement effects of digital transformation contributed to the promotion of TFP improvement in these enterprises. Moreover, our heterogeneity analysis suggested that digital transformation is more effective in enhancing TFP in state-owned enterprises (SOEs) in the food-related industry, indicating that SOEs play a representative role in promoting advanced productivity in agricultural development. We also found that capital-intensive and technology- intensitve food-related enterprises were experiencing productivity paradox traps. Our results confirmed that digital transformation brings catch-up effects to labor-intensive food-related enterprises and those located in major grain production regions. Overall, this research can provide valuable insights for policymakers to upgrade the digital- -enabled food industry. [ABSTRACT FROM AUTHOR]

Using data from the China Health and Nutrition Survey (CHNS) dated from 1991 to 2015, we assess the impact of public bus expansion into villages on income mobility of rural household, particularly, with low income. This paper finds that the income mobility of low-income households is suffered from the expansion of public buses in the rural areas. Due to the 'crowding out' effect, the low-income families are excluded from the non-agricultural employment brought by the public bus expansion, which nevertheless does not improve the agricultural production structure. This can explain why the low-income group has been marginalized during the process of urban-city integration in China. Improvement of the human capital can significantly alleviate the negative impact of public bus expansion on the low-income group in rural areas, while the child-care burden aggravates the issue. These results may also have policy implication for potential solutions to problems such as the 'First Kilometer' to realize common prosperity is not simply about the modernization in the infrastructure but also equalization of opportunities through cultivation of human capital. [ABSTRACT FROM AUTHOR]

Increasing agricultural productivity and reducing carbon emissions are two major challenges that China faces. This paper explores how agricultural insurance affects agricultural green total factor productivity (AGTFP) that addresses these two challenges. First, we adopt DDF-GML to measure AGTFP, and the Dagum's Gini decompositions results show the large differences in AGTFP, with transvariation between subregions contributing the most. Second, we find the U-shaped effect of agricultural insurance on AGTFP in a large country context. The result remains robust after adjusting for time, sample and estimation method of AGTFP. We also construct instrumental variables from the minimum distance from the centroid of counties within a province to the 45 ports in China and two-stage lagged agricultural insurance penetration (AIP) for AIP, and their squares as instrumental variables for AIP2. The conclusion remains robust in 2SLS model. Third, the findings confirm three channels for agricultural insurance to influence the AGTFP: environmentally friendly production, labor inputs and operation scale. We further propose policy advice to promote China's agricultural modernization and point out further research directions in this field. [ABSTRACT FROM AUTHOR]

China has recently become an agent of intensified agricultural production in Southeast Asia by constructing large‐scale irrigation systems. Funded with Chinese development finance, such infrastructure projects have been interpreted as a 'spatial fix' for capital accumulation in China, which helps explain the shifting balance of power within the region's political economy. However, we argue that explaining the local outcomes of these projects requires mapping out Chinese development finance in relation to the multi‐scalar network of actors, circuits of capital, and struggles over water that produce irrigated landscapes. We draw on our joint research about the Chinese‐funded and built Kanghot Irrigation Development Project in Cambodia. We explain how the construction of Kanghot was shaped by the historical and political relations between China and Cambodia. Since completion in 2016, Kanghot irrigation has transformed agricultural production by enrolling farmers into a network of volatile commodity markets and harmful pest ecologies. There have also been ongoing community struggles over Kanghot's water due to the project's design and institutional management. By broadening the idea of infrastructure as spatial fix to include these material and social processes of agrarian landscape production, this paper advances a political ecology of Chinese development finance in Southeast Asia. [ABSTRACT FROM AUTHOR]

Based on the data of 2015 China Household Finance Survey (CHFS), this paper applies the intermediary effect model to identify the intermediate transmission mechanism in which farmland transfers affect agricultural production efficiency. The results show that the output value of households that have transferred farmland is increased by about 27% more than those that have not. In addition, the transfer of farmland has a more significant impact on the agricultural production efficiency of young and middle --aged families. The transfer of farmland from grain production areas has an increased tendency to household output value. The mechanism analysis shows that the transfer of farmland affects agricultural production efficiency in the following two ways. On the one hand, the transfer of farmland can help realize the effective replacement of labor by machinery, increase the mechanization degree of agricultural production, and realize the scale effect of farmland. On the other hand, based on the maximization of their own interests, farmers prefer to plant cash crops and improve agricultural production efficiency through the selection effect. By comparing the above two effects, we found that the planting selection behavior of compacting grain and expanding economic growth is more prominent. Therefore, this article proposes to promote the development of the farmland transfer market and make use of scale advantage. Meanwhile, the self-selection behavior of transferred farmers in planting crops should be valued and young people with advanced concepts to engage in agricultural production activities should be introduced, which inject "fresh blood" into agricultural modernization. However, we should also keep the red line of farmland and alert the phenomenon of "non-agricultural" and "non-grain" in the transfer of farmland. [ABSTRACT FROM AUTHOR]

Climate change poses an urgent threat, necessitating the implementation of measures to actively reduce carbon emissions. The development of effective carbon emission reduction policies requires accurate estimation of the costs involved. In situations where actual prices of commodities are not available in the market, shadow pricing provides a useful method to calculate relative prices between commodities with and without price information. However, most studies focus on the industry, with few contributions on agricultural sector. This paper estimates the shadow price of carbon emissions in the agricultural sector from a provincial perspective, incorporating the impact of livestock into the calculation of carbon emissions and shadow pricing. Our findings indicate that ignoring livestock may overestimate CSP values. On the whole, the level of carbon shadow price is rising, indicating good green development in China's agricultural sector. The two types of convergence results show that there is sigma convergence and beta convergence in the western and central regions, demonstrating a significant improvement in environmental performance. [ABSTRACT FROM AUTHOR]

Rapid urbanization negatively affects the eco-land. The topic of accurate zoning and control of ecological space has become a challenge for many countries. This paper uses the idea of ESP to delineate the control system of China's coastal area. First, three types of ecological sources were identified from the aspects of landscape functions' importance, landscape sensitivity, and landscape connectivity. Then, ecological corridors and nodes were identified using the model of minimum cumulative resistance (MCR) based on the resistance surface. Finally, an ecological control zoning system was constructed by using a "bottom-up" transmission mechanism. The results show that: (1) Most of the landscape function-oriented sources and connectivity-oriented sources are located in the south, where habitat quality is superior. Urban construction and agricultural production are the main threat factors to sensitivity-oriented sources. (2) 81.24% of ecological corridors are reticulated, indicating good structural connectivity, and 11 fragile corridors should be specially protected. (3) Among the three second-level of strictly protected areas, the percentage of restoration area and landscape structure maintenance area are 40.19% and 28.47%, indicating the high threat to eco-land and low landscape connectivity; measures are needed to enhance eco-connectivity and increase the resilience of eco-lands. The research constructs a point-line-plane integrated ecological control zoning system, which can provide a scientific basis for the spatial prioritization of coastal ecological protection in China's coastal areas. [ABSTRACT FROM AUTHOR]

While chemical fertilizers and pesticides have significantly enhanced crop productivity per unit of land in China, the excessive utilization of these chemicals has led to a range of environmental issues that are not conducive to the sustainable development of China's agriculture. Controlling the use of fertilizers and pesticides in crop cultivation is therefore necessary and has been adopted as an action plan since 2015 in China. However, the effects of fertilizer and pesticide reductions have not been systematically investigated. This paper explores how yields and land use for rice, wheat, corn, and soybean cultivation shift when reducing their fertilizer and pesticide inputs using China's provincial crop-land integrated partial equilibrium model (the CPMCL model). Simulation results for different scenarios show that, among the studied crops, rice and wheat exhibit greater adaptability than corn and soybeans. Reducing the use of fertilizers and pesticides within the interval from 0% to 3.5% may increase the total demand of land resources for crop production from 0.220% to 4.21%. Limited land resources will be allocated to more profitable crops to maximize output, which means the land use for wheat production may increase over 20% while for rice, corn and soybean may decrease around 4% under the shock of fertilizer and pesticide reductions. Merely reducing fertilizer and pesticide inputs in crop cultivation may exacerbate the conflict between crop production and land resource conservation in China, which means the technology and efficiency of fertilizer and pesticide use needs to be improved. The findings of this paper can help formulate more province-specific and crop-targeted plans to properly reduce fertilizer and pesticide use, thus promoting sustainable land use while ensuring food security and protecting the environment. • China's provincial PE model integrates crop production and land use is formulated • Interrelationship between chemical inputs, land inputs, and crop yields is revealed • Impacts of fertilizer and pesticide reduction are analyzed nationally and provincially [ABSTRACT FROM AUTHOR]

• The ISP method allows for gathering a large number of historical training samples. • The SRVI values of the same crop planted in neighboring years range from 0.91 and 1.2. • A distinct northward expansion trend is evident for all four major crops, in Heilongjiang Province, China. Mapping agricultural information such as cropping area and type is of great significance for land use and food security and a common method to retrieve such information is satellite imagery classification. The current image classification techniques require a statistically large number of training samples to obtain representative spectral signatures, ideally collected during the satellite overpass time/date. Although this prerequisite sounds simple and easy in principle, it is extremely challenging and sometimes impossible when classifying historical satellite images, as one simply cannot go back in time to collect training datasets or ground truthing. In this paper, we introduce an iterative and subsequent proximation (ISP) method to circumvent this problem for historical image classifications for historical crop mapping. This method assumes that the same crops grown two years apart have similar spectral properties within the same growing season, with limited variation. This allows the use of the crop information classified in any given year (n) to be used as training samples for the next year (n + 1) or the previous year (n-1). Iteratively repeating n-1, n-2... process leads to the mapping of historical cropping information without a priori ground truthing data. To demonstrate the ISP feasibility, we first used the historical Landsat time-series data to map four major stable crops (rice, maize, soybean, and wheat) in Hailun County, Heilongjiang Province, China, and then further expanded the ISP application to the entire Heilongjiang Province to map cropping areas from 1982 to 2020, using the classification and regression trees (CART) algorithm. The results were validated for those years when actual cropping measurement data were available and further verified with statistical data for other years. The results indicated that the proposed ISP method was appropriate for the historical mapping of four major crops, with a mapping accuracy of approximately 80 % when validated with field data, and correlation coefficients of 0.86, 0.85, 0.91, and 0.94, respectively when compared with historical statistical cropping data. The crop mapping results showed distinct trends of northward expansion in each of the four crops in Heilongjiang Province, which agreed well with previous studies. In conclusion, the ISP method is quick, easy, and convenient for historical crop mapping, which is important in understanding the agricultural production history. [ABSTRACT FROM AUTHOR]

Against the backdrop of global warming, intensifying regional conflicts, deglobalization, and the spread of diseases, global food security is facing severe challenges. Studying the food security situation in China and the United States in depth can provide practical experience for formulating food security policies for countries around the world and promoting global food security governance. On the basis of a meticulous review of the evolving connotations of food security, this study adopts six dimensions—quantity security, quality security, circulation security, economic security, ecological resource security, and policy security—as breakthrough points to construct a framework consisting of food security evaluation indicator system comprising 29 specific indicators. The CRITIC–MEREC–MARCOS model is applied to evaluate the status of food security in China and the United States from 2000 to 2022, while the obstacle degree model (ODM) model is utilized to identify factors impeding food security between the two countries. The results indicate that the level of food security in China has shown slight fluctuations initially, followed by a steady upward trend. The gap with the United States is continuously narrowing. However, significant differences between China and the United States still exist in terms of economic security, ecological resource security, and policy security. Furthermore, due to the limited productivity of agricultural labor, scarcity of water and soil resources, and low efficiency in the use of fertilizers and pesticides, China's food security is subject to economic and environmental constraints. The restrictions imposed by economic security and ecological resource security on China's food security are showing an increasing trend year by year. For the United States, with the obstruction of grain exports and the increasing frequency of drought disasters, the impact of circulation security and ecological resource security on food security is becoming increasingly prominent. In the future, China and the United States should join hands to address challenges, actively promote international cooperation in food security, and drive sustainable development for humanity. [ABSTRACT FROM AUTHOR]

Drought, as a widespread natural calamity, leads to the most severe agricultural losses among all such disasters. Alterations in the yield of major global agricultural products are pivotal factors influencing food prices, food security, and land use decisions. China's rapidly expanding demand for sustenance will persist over the forthcoming decades, emphasizing the critical need for an accurate assessment of drought's impact on food production. Consequently, we conducted a comprehensive evaluation of the drought risk in China and its repercussions on agricultural output. Additionally, we delved into the underlying factors driving changes in yield for three primary grain crops (wheat, corn, and rice), which hold particular relevance for shaping effective strategies to mitigate future drought challenges. The findings divulge that both the number of drought months (DM) and the drought magnitude index (DMI) have displayed an upward trajectory over 60 years with a correlation coefficient of 0.96. The overall severity of meteorological drought has escalated across China, and it is particularly evident in regions such as the southwest and central parts of the Huang-Huai-Hai region, the northwestern middle region, and the Xinjiang region. Conversely, there has been some relief from drought conditions in southern China and the Yangtze River Delta. Shifts in the total grain output (TGO) during this period were compared: it underwent three stages, namely "fluctuating growth" (1961–1999), then a "sharp decline" (2000–2003), followed by "stable growth" (2004–2018). Similarly, changes in the grain planting area (GPA) experienced two stages, "continuous reduction" (1961–2003) succeeded by "stable growth" (2004–2018), while maintaining an upward trend for grain yield per unit area (GY) throughout. Furthermore, it was revealed that the drought grade serves as a significant constraint on continuous expansion within China's grain output—where the drought damage rate's influence on the TGO outweighs that from the GY. Our research outcomes play an instrumental role in deepening our comprehension regarding how drought impacts agricultural production within China while furnishing the scientific groundwork to devise efficacious policies addressing these challenges. [ABSTRACT FROM AUTHOR]

Agricultural green production technology (AGPT) is essential for the sustainable development of agriculture, yet adoption rates among farmers are often low due to limited access to education and information. Based on the extended technology acceptance model, this study takes Liaoning, a major agricultural province in China, as a representative region to explore how digital multimedia influences the adoption of AGPT by farmers. The findings show that the perceived ease of use of these technologies significantly enhances farmers' intentions to adopt, while perceived risks detract from these intentions. Although digital multimedia effectively promotes AGPT by improving its perceived ease of use and usefulness, its role in mitigating perceived risks is minimal. Based on these results, we recommend that the government improve the quality of information on digital platforms by involving experts in the field and offer specific digital marketing training to potential users to increase the adoption of sustainable agricultural technologies. [ABSTRACT FROM AUTHOR]

Currently, China's soybean self-sufficiency rate is only 15%, highlighting the soybean crisis and the supply chain risks that pose a major threat to China's food security. Thus, it has become imperative to step up efforts to boost soybean production capacity while promoting the green and sustainable development of regional farmland ecosystems. In this context, the present study comprehensively investigated the effects of intercropping and nitrogen application rate on soybean yield, as well as the changes in gradients generated by different levels of nitrogen application. Based on six consecutive years of maize–soybean intercropping planting patterns, the inter-root soils of soybeans were collected at the flowering stage and evaluated for soil nitrogen content, nitrogen-assimilating enzyme activities, and microbial community composition of soybean, which were correlated with yield, to clarify the main pathways and modes of intercropping effects. The N2 level (80 kg·ha−1) was favourable for higher yield. In comparison to monocropping, the intercropping reduced yield by 9.65–13.01%, photosynthetic characteristics by 1.33–7.31%, and plant nitrogen-assimilating enzyme activities by 8.08–32.01% at the same level of N application. Likewise, soil urease and catalase activities were reduced by 9.22 and 1.80%, while soil nitrogen content declined by an average of 6.38%. Gemmatimonas and Bradyrhizobium enrichment significantly increased soil nitrogen content, photosynthetic characteristics, and soybean yield, while it was reduced by Candidatus_Udaeobacter and Candidatus_Solibacte enrichment. The results of this study provide a theoretical basis for further optimising maize–soybean intercropping, which is crucial for enhancing the agricultural production structure and improving the overall soybean production capacity. [ABSTRACT FROM AUTHOR]

Flood submergence has devastating effects on agricultural production in China, with rice being particularly vulnerable to its impacts. Previous studies on rice submergence stress have primarily focused on immediate yield reduction and short-term growth. In this study, a submergence stress experiment was carried out by using the method of potted rice flooding. The growth recovery characteristics of rice under different submergence stress were analyzed through the continuous observation of rice growth after the disaster. The results showed that submergence stress had a persistent effect on rice growth, which persisted until the recovery period after the disaster. The recovery ability of rice plants decreased with the aggravation of stress, leading to increased damage to the plant. The average yield decreased by 17.07% and 15.56% due to submergence stress during the jointing and booting stage, respectively. The current study pointed out that the growth traits of and, furthermore, the mechanism of physiological changes in rice during the recovery period need to be explored in order to understand the effects of flooding stress on rice. [ABSTRACT FROM AUTHOR]

Aims: Fertilization methods have affected the development of dryland agriculture. There is a need to understand the impacts of different fertilizer application depths on crop production and gas emissions to facilitate the sustainable development of dryland agriculture. Methods: A field experiment was conducted for two years (2019–2020) in a dryland agroecosystem in the Loess Plateau region of China. Five fertilizer placement depths were tested comprising 0 cm (FD0), 5 cm (FD5), 15 cm (FD15), 25 cm (FD25), and 35 cm (FD35). N-P-K fertilizer was applied to all treatments as base fertilizer at the same rate. After sowing, the gas emission fluxes were measured 17 consecutive times. We systematically analyzed the effects of different fertilization depths on the summer maize (Zhengdan 958) yield, ammonia (NH3) volatilization, and greenhouse gas emissions (nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4)). Results: The results showed that the NH3 volatilization, N2O emissions, CO2 emissions, and global warming potential (GWP) decreased as the fertilization depth increased. Compared with the traditional fertilization depth (FD5), deep fertilization at 15 cm clearly reduced the NH3 volatilization, N2O emissions, CO2 emissions, GWP, and greenhouse gas intensity. In addition, compared with FD25 or FD35, FD15 increased the capacity of the soil to absorb CH4. Critically, compared with the traditional fertilization depth, FD15 can effectively improve the summer maize biomass yield (4.2%) and grain yield (18.1%) at the final harvest. Conclusion: FD15 can promote the sustainable development of dryland agriculture in the Loess Plateau region of China by improving crop production and reducing gas emissions. [ABSTRACT FROM AUTHOR]

The rapid development of digital finance has effectively reduced financial challenges in rural regions and created new prospects for agricultural production. This article examines the impact of digital financial development on rice production in Sichuan Province using the 2011–2021 Peking University Digital Financial Inclusion Index and data from 20 prefecture-level cities, as well as a fixed effects model. The mechanism of action is also discussed. The findings reveal that the advancement of digital finance plays an important role in boosting the expansion of rice production, and that digital finance influences rice output by increasing farmers' willingness to participate in insurance and increasing the availability of credit. A heterogeneity analysis reveals that digital finance has a substantial effect on mountainous and economically poor areas. As a result, this article suggests that the breadth and depth of usage of rural digital finance, as well as the development of rural digital financial services in underdeveloped areas, should be expanded. [ABSTRACT FROM AUTHOR]

The agro-pastoral transitional zone in northern China is an important agricultural and pastoral production base. This study focuses on the eastern section of the agro-pastoral transitional zone in northern China. Combined with spatio-temporal analysis, stepwise regression, and gray relation analysis, we analyzed the average annual growth rate, spatio-temporal changes, and influencing factors of agricultural and pastoral production in the study area during 2000–2020. The results show that, in the past 20 years, the agricultural and pastoral production of the 50 municipal districts and counties has significantly changed, among which the agricultural production of 38 municipal districts and counties has shown an extremely significant increase. Generally, the growth rate of agricultural production is higher than that of pastoral production. Agricultural and pastoral production in the study area is influenced by socio-economic and land use/cover factors, with an average correlation degree of 0.79 and 0.88, respectively. Climate change affects agricultural production in agricultural counties, with a correlation degree of 0.85. The results of this research provide valuable insights into understanding the long-term temporal and spatial changes in agricultural and pastoral production and help to develop sound agriculture and pastoral management practices in the eastern section of the agro-pastoral transitional zone in Northern China. [ABSTRACT FROM AUTHOR]

With the facilitation of agricultural modernization, China's agricultural energy consumption continues to rise. This paper empirically tests the agricultural energy rebound effect and its influencing factors in China during 1999–2020. It is believed that the improvement of energy efficiency has not led to the expected energy-saving effect in agriculture due to the "Jevons paradox" of energy efficiency and energy consumption. The average energy efficiency of China's agricultural energy consumption was 0.446, and the average energy rebound effect was 68.9 %. The level of agricultural mechanization, the effective irrigated area of farmland and agricultural investment have a positive impact on the rebound effect of agricultural energy, and the direct effects are 0.062, 0.008 and 0.064, respectively, while agricultural labor force and energy price have a negative impact on the rebound effect of agricultural energy. In particular, technology spillover and scale spillover led by agricultural technology progress have strong negative space spillover effect. As it is argued, 1 % of agricultural technology progress can reduce 3.5 % of agricultural energy rebound effect in surrounding areas. In order to reduce the energy rebound effect, it is suggested to increase the subsidies to agricultural labors and rationally formulate regional differentiated energy regulation policies. • The internal mechanism of rebound effect is expounded from the view of producers and consumers. • The average energy efficiency of China's agricultural energy consumption was 68.9 % during 1999–2020. • The determinants of the agricultural energy rebound effect were further discussed by considering the spatial spillover effect. [ABSTRACT FROM AUTHOR]

This study explores the intricate relationship between agricultural productivity and the pursuit of a just energy transition in China. As the world's largest emitter of greenhouse gases and a nation grappling with environmental degradation and socio-economic disparities, China faces the imperative to transition toward a more sustainable and equitable energy system. This paper investigates the role of agriculture in this transition, recognizing its pivotal position as a significant emitter of greenhouse gases while also being vulnerable to the impacts of climate change. By examining the potential synergies and conflicts between agricultural productivity enhancement and the goals of reducing emissions and promoting social justice, this study aims to shed light on strategies that can effectively align agricultural development with the objectives of a just energy transition. The result indicates substantial internal disparities and strong agglomeration effects (referring to areas with similar agricultural total factor productivity) within China's agricultural total factor productivity distribution. Over the past 17 years (2005–2021), the average agricultural productivity has shown a commendable upward trend, marking a 2.8% growth rate. This increase signifies ongoing efforts and advancements in the agricultural sector, leading to improved productivity levels. Our results also show a significant positive spatial correlation in agricultural total factor productivity, suggesting a tendency for spatial agglomeration. The years 2005 and 2021 stand out as periods marked by significant adverse effects resulting from the interplay of diverse factors on agricultural productivity. By integrating findings from various sectors, this study provides insights into the complex interplay between agriculture and energy transition, emphasizing the need for integrated, holistic approaches that prioritize sustainability, fairness, and resilience in China's pursuit of a just energy future. • This study explores the relationship between agricultural productivity and energy transition. • Our aim is to align agricultural development with the objectives of energy transition. • The analysis connects productivity and equity. • We emphasize sustainability and resilience in China's pursuit of a just energy future. [ABSTRACT FROM AUTHOR]

Leaf spot disease is an extremely common disease in the growth process of maize in Northern China and its degree of harm is quite significant. Therefore, the rapid and accurate identification of maize leaf spot disease is crucial for reducing economic losses in maize. In complex field environments, traditional identification methods are susceptible to subjective interference and cannot quickly and accurately identify leaf spot disease through color or shape features. We present an advanced disease identification method utilizing YOLOv8. This method utilizes actual field images of diseased corn leaves to construct a dataset and accurately labels the diseased leaves in these images, thereby achieving rapid and accurate identification of target diseases in complex field environments. We have improved the model based on YOLOv8 by adding Slim-neck modules and GAM attention modules and introducing them to enhance the model's ability to identify maize leaf spot disease. The enhanced YOLOv8 model achieved a precision (P) of 95.18%, a recall (R) of 89.11%, an average recognition accuracy (mAP50) of 94.65%, and an mAP50-95 of 71.62%, respectively. Compared to the original YOLOv8 model, the enhanced model showcased enhancements of 3.79%, 4.65%, 3.56%, and 7.3% in precision (P), recall (R), average recognition accuracy (mAP50), and mAP50-95, respectively. The model can effectively identify leaf spot disease and accurately calibrate its location. Under the same experimental conditions, we compared the improved model with the YOLOv3, YOLOv5, YOLOv6, Faster R-CNN, and SSD models. The results show that the improved model not only enhances performance, but also reduces parameter complexity and simplifies the network structure. The results indicated that the improved model enhanced performance, while reducing experimental time. Hence, the enhanced method proposed in this study, based on YOLOv8, exhibits the capability to identify maize leaf spot disease in intricate field environments, offering robust technical support for agricultural production. [ABSTRACT FROM AUTHOR]

The quest to eradicate poverty, central to the United Nations Sustainable Development Goals (SDGs), poses a significant global challenge. Advancement in sustainable rural development is critical to this effort, requiring the seamless integration of environmental, economic, and governmental elements. Previous research often omits the complex interactions among these factors. Addressing this gap, this study evaluates sustainable rural development in China by examining the interconnection between agricultural production and government-led poverty reduction, with annual rainfall considered an influential factor of climate change impacts on these sectors and overall sustainability. Utilizing a Meta-frontier entropy network dynamic Directional Distance Function (DDF) within an exogenous Data Envelopment Analysis (DEA) model, we categorize China's 27 provinces into southern and northern regions according to the Qinling-Huaihe line for a comparative study of environmental, economic, and governmental efficiency. This innovative approach overcomes the limitations of previous static analyses. The findings reveal: (1) Rainfall, as an exogenous variable, significantly affects agricultural production efficiency. (2) The overall efficiency in both southern and northern regions increases when accounting for rainfall. (3) Government effectiveness in poverty reduction is comparatively lower in the northern region than in the southern region when rainfall is considered. These insights underscore the importance of including climatic variables in sustainable development policies and emphasize the need for region-specific strategies to bolster resilience against climatic challenges. [ABSTRACT FROM AUTHOR]

Tropospheric ozone (O3) is known to harm crops by intrinsically affecting photosynthesis and other functions during crop growth. In staple crop production bases in the North China Plain (NCP) and Yangtze River Delta (YRD) regions, food security, especially food production, has been reported to be threatened by high O3 concentrations. Studies have been conducted in the NCP or YRD to understand tropospheric O3 and its precursor gases; however, the need to understand the effect of O3 on crops in conjunction with the contributions of precursor gases (VOCs and NOx) to O3 formation using a fine-scale model remains. In this study, the combined Weather Research and Forecast with Chemistry (WRF-Chem) model was used to evaluate the impact of surface O3 on reduced grain yield in China in 2010, covering the crop-growing seasons of single rice, double late rice, and winter wheat. The relative yield loss due to O3 damage was evaluated using the accumulated O3 exposure over a threshold of 40 ppb (AOT40) and a mean 7-hour O3 mixing ratio (M7). The validation showed that the gas-phase chemistry mechanism Model for Ozone and Related chemical tracers, version 4 (MOZART-4), coupled with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol module registered in WRF-Chem, can simulate O3 fairly in the NCP and YRD. The aggregated average rice (wheat) relative yield losses throughout NCP and YRD were estimated to be 5.9% (27.1%) for AOT40 and 2.2% (9.6%) for M7, whereas aggregated rice (wheat) production losses were 2,345 kt (13,947 kt) for AOT40 and 999 kt (3,753 kt) for M7. In addition, reducing anthropogenic emissions of Volatile Organic Compounds (VOCs) from the energy and transport sectors is effective in reducing the surface O3 concentration. The results provide important scientific evidence for achieving sustainable food production in China. [ABSTRACT FROM AUTHOR]

Northeast China (NEC) is the most prominent grain‐producing region in China. However, it is currently facing significant impacts from climate change. Since the climate‐related impacts on crop yield in this region are a major concern for society in the future, quantifying climate change impacts on crop yields in NEC is essential to ensure future food security. This study aimed to quantify the effects of future climate change on crop yields in NEC and explore adaptation strategies using the Crop Growth Model (PCSE) driven by downscaled CMIP6 climate projections under four Shared Socioeconomic Pathways (SSPs) scenarios during 2015–2100. Results showed that there could be average reductions in crop yields of 21.4% for maize and 4.2% for soybean by the year 2100 under SSP585 compared to the 2015 baseline. The increasing temperature was the dominant factor in reducing yields, although elevated CO2 and precipitation offered partial compensation. The optimized planting date brought noticeable benefits for rice and soybean but had limited effects on maize due to heat stress. Relocating rice expansion eastward and implementing earlier planting increased yields by up to 50% but adversely decreased soybean and maize due to competition. This study enriches our comprehension of climate change impacts on NEC agriculture, while also quantifying potential benefits and constraints of evaluated adaptations. The proposed adaptations may help mitigate projected yield declines in other key agricultural regions across the globe. Adjusting crop management practices to capitalize on changing climate factors shows promise as a strategy for sustaining production globally. Plain Language Summary: Northeast China (NEC) is essential for achieving food accessibility and food security in China, but its agricultural production is seriously threatened by climate change. This study investigated how climate change could impact maize, rice, and soybean crop yields in this region from 2015 to 2100, using the PCSE crop model and forcing from the international Coupled Model Intercomparison Project 6 (CMIP6) climate projections. Simulation results suggested rising temperatures would negatively affect crop yields, especially for maize. Increased carbon dioxide and rainfall partially offset these losses. By 2100, average declines were projected for maize (−21%) and soybeans (−4%), respectively. Altering planting dates to match crop needs was an effective adaptation to boost yields, with rice benefiting the most. Relocating rice production eastward and expanding its area substantially increased simulated rice yields (+62%) but decreased other crops due to competition (−32% maize, −28% soybeans). Even with adaptations, some areas still showed yield declines, indicating extra measures may be needed to maintain production. Overall, this study suggests significant risks to crop yields from climate change in Northeast China, with adaptations like optimized planting and strategic crop relocation able to mitigate some but not all of the projected impacts. Key Points: Rising temperatures negatively impacted simulated future crop yields, especially for maizeAdjusting planting dates boosted yields for rice and soybeans but had limited benefits for maizeRelocating and expanding the rice area increased yields substantially [ABSTRACT FROM AUTHOR]

While agricultural green development (AGD) is highly recognized and has become a national strategy in China, it is imperative to bridge the knowledge gaps between AGD and the UN Sustainable Development Goals (SDGs), and to evaluate the contribution of AGD to meeting the SDGs. The first aim of this study was to compare the AGD goals and indicators with those of the SDGs so as to identify their relationship. The next aim was to examine the historical evolution of AGD indicators and analyze the gaps between the current status of various indicators and their benchmarks. Limiting factors were identified in China's transition toward AGD. These findings reveal that the indicators of AGD align with those of the SDGs, but have greater specificity to the context in China and are more quantifiable. There has been a significant increase per capita calorie and protein intakes in China, as well as a notable rise in agricultural output per unit of arable land and rural incomes from 1980 to the 2010s. However, these achievements have been accompanied by a high resource use and environmental pollution, highlighting the need for a more sustainable, environmentally responsible agriculture in China. [ABSTRACT FROM AUTHOR]

The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964–2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha−1 yr−1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008–2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region [ABSTRACT FROM AUTHOR]

Based on a large national sample of the China Family Panel Studies (CFPS) database, the study will to provide some thoughts and suggestions for the transformation and upgrading of China's agriculture, the enhancement of total factor productivity by exploring the agricultural production efficiency from the micro-farmers' perspective. By constructing the models of Charnes, Cooper & Rhodes (CCR), Banker, Charnes & Cooper (BCC), Slacks-Based Model (SBM) and technology optimization Malmquist-Luenberger index, it finally obtained the comprehensive technical efficiency value, pure technical efficiency value, farm household efficiency value and green total factor productivity level value at the micro-farm household level based on the comparative analysis. It was found that: the comparison of the measures based on different models found that although there are differences in the calculated efficiency values, the pure technical efficiency values calculated by BCC are the main factors affecting the micro agricultural production efficiency values at the farmer level, the SBM model should optimize the CCR, BCC models, and more suitable for Chinese government policy formulation and optimization; the technology optimization Malmquist-Luenberger index method is the micro agricultural production efficiency measurement method of choice, with the characteristics of diverse model selection, rich application scenarios and convenient processing of negative outputs; environmental factors in the current evaluation of agricultural green total factor productivity, mainly play a negative inhibitory role, reducing the negative externalities of environmental variables output, become one of the key issues facing the current micro farm layer green total factor production enhancement; the combination of subjective and objective measures of environmental non-desired output is an important way to measure environmental factors of agricultural green total factor productivity, it can be used in practical applications based on a combination of research objectives and data availability. [ABSTRACT FROM AUTHOR]

The carbon storage of terrestrial ecosystems plays a crucial role in mitigating climate change, and the transformation of territorial space has a significant impact on the carbon cycle of a country's terrestrial ecosystems. Therefore, evaluating the impact of space transformation on carbon storage is essential for enhancing regional carbon storage potential and reducing carbon emissions. We use the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to analyze the dynamic changes in territorial spatial transformation and carbon storage from 2000 to 2020 in Suqian, as well as their relationship. On this basis, the optimization strategy and specific path for improving territorial space carbon storage capacity were determined. The results show the following: that (1) from 2000 to 2020, territorial spatial transformation in Suqian was dramatic, with the most significant changes occurring between 2005 and 2010. The scale of mutual transformation between agricultural production space and urban–rural construction space was the largest. (2) Carbon storage gradually decreased in Suqian City, with a total reduction of 1.23 × 106 tons over 20 years and an annual decrease of 1.46%. The carbon density of forested space was significantly higher than that of other spaces. The conversion of agricultural production space and forestland space to urban–rural construction space was the main factor driving a decrease in carbon storage. (3) Territorial spatial transformation is a spatial manifestation of the evolution of human–land relationships. Regulating the function, scale, structure and layout of territorial space as a whole and implementing differentiated management of specific space will be beneficial to optimize carbon storage in Suqian. [ABSTRACT FROM AUTHOR]

Understanding the regional variations and mechanisms of rural hollowing-out in the Yellow River Basin (YRB) is crucial to guiding regional rural revitalization. However, further quantitative evaluation and analysis are essential to address the issue of rural hollowing-out caused by the decrease in rural population and expansion of residential land in the YRB at different spatio-temporal scales. Based on China's census data and residential areas extracted from remote sensing images, the rural hollowing-out in the YRB is classified into five types: smart development type (SDT), human–-land recession type (HRT), population loss type (PLT), land expansion type (LET), and human–land–vacant waste type (HLW). Then, the influential features shaping the spatial diversity of rural hollowing-out types are examined, and the feature importance values at different spatio-temporal scales are assessed using the XGBoost model. The results of rural hollowing-out in the YBR indicate that (1) the geographical types of rural hollowing-out in the YRB are dominated by the HRT type and show significant heterogeneity and distribution at different spatio-temporal scales. At different time stages, the number of counties dominated by HRT in lower reaches accounts for 57% of the total counties, whereas the number of counties in the middle reaches is only 37%. Compared to the rural hollowing-out results from 2000 to 2010, the number of counties dominated by PLT and HLW from 2010 to 2020 in the middle reaches increased by 19% and 16%, respectively. (2) Precipitation had a positive effect on the variability of the rural hollowing-out distribution results based on the feature importance values, whereas agricultural productivity had a negative effect and exhibited a decreasing trend. In the entire study area, economic non-agriculturalization had a negative impact, but the topographic relief was positively correlated with the rural hollowing-out results of regional areas, and the intensity of its effect showed an increased trend from 2000 to 2020. (3) The evaluation results in the entire study area show that the main functional type and the distance from provincial capitals are the most important factors affecting rural hollowing out. Compared to other factors, the level of non-agricultural economic development has a greater impact on the spatio-temporal differentiation of rural hollowing types in different Yellow River basins. Given the significant effect of non-agricultural economic development in the evaluation of regional rural hollowing-out, it can provide methodological and indicator references for the evaluation of rural hollowing-out in different regions. [ABSTRACT FROM AUTHOR]

The core of dual circulation in the Loess Plateau and the greening Yellow River is sustainable development. Gully agricultural sustainable production is extremely important to ensuring a more sustainable Loess Plateau. Here, we investigate the overall characteristics of gully agricultural production sustainable transformation (GAPT) in the Loess Plateau from a macro perspective. We also analyze the evolution, stage characteristics, and trends in gully agricultural production space using theoretical analysis and empirical research from the multi-dimensional perspective of spatio-temporal-development. The findings reveal that: (1) From 2000 to 2020, the gully agricultural production structure in the Loess Plateau exhibited a trend of hierarchical upgrading. In general, gully agricultural production in the Loess Plateau has entered a relatively stable new normal stage of structural adaptation adjustment. (2) Throughout the past two decades, gully agricultural production development in the Loess Plateau has gradually improved, progressing from a low to a high level. Additionally, overall regional disparity has diminished over time. (3) The overall fluctuation of GAPT in the Loess Plateau has increased, with more pronounced changes observed in agricultural functions and ecological security maintenance. At different stages, various factors had demonstrated varying effects on the GAPT, leading to significantly diverse outcomes in production sustainable transformation in response to changes in factor levels. Overall, understanding sustainable gully agricultural production is immensely important for exploring human-earth interactions and forging a sustainable path within this intricate balance. Our research outcomes offer valuable insights for fostering gully rural transformation, optimizing crop planting modes, enhancing the gully living environment, and ultimately propelling the Loess Plateau towards a more sustainable and prosperous future. • This paper proposed a multi-dimension analysis framework for gully agricultural production sustainable transformation (GAPT). • We quantified GAPT 's trends and characteristics of Loess Plateau, China. • Policy suggestions were given for strategy for more sustainable Loess Plateau. • This research has significance for the gully rural revitalization and green sustainable development. [ABSTRACT FROM AUTHOR]

Introduction: Food production stands as a critical global concern necessitating comprehensive investigation. This study utilizes provincial-level data from China to explore the intricate relationships between farmland transfer, agricultural loans, and grain production, with the aim of shedding light on the complexities of these dynamics. Methods: A two-way fixed effects model and instrumental variable approach are applied to assess the interplay between farmland transfer, agricultural loans, and grain production. These methods provide a robust framework for understanding the complex relationships among these variables. Results and discussion: The study reveals a notable positive correlation between farmland transfer and grain production. Conversely, agricultural loans demonstrate a significantly negative impact on grain production. However, the positive interaction term between farmland transfer and agricultural loans suggests a nuanced relationship. While profit-driven financial activities may not inherently favor grain production, they contribute to more efficient utilization of farmland resources, ultimately promoting grain production. The findings underscore the significance of continued government support for rural land system reform and active guidance of farmland transfer. It is emphasized that a moderate-scale operation of farmland is crucial for finance to play a lubricating and catalytic role. Furthermore, there is a need to guide agricultural finance towards investing in medium and long-term projects of agricultural production. Attention is also directed to preventing potential food crises arising from the phenomenon of "non-farming" associated with agricultural loans. [ABSTRACT FROM AUTHOR]

Improved agricultural production systems, together with increased grain yield, are essential to feed the growing global population in the 21st century. Global gridded crop models (GGCMs) have been extensively used to assess crop production and yield simulation on a large geographical scale. However, GGCMs are less effective when they are used on a finer scale, significantly limiting the precision in capturing the yearly maize yield. To address this issue, we propose a relatively more advanced approach that downsizes GGCMs by combining machine learning and crop modeling to enhance the accuracy of maize yield simulations on a regional scale. In this study, we combined the random forest algorithm with multiple data sources, trained the algorithm on low-resolution maize yield simulations from GGCMs, and applied it to a finer spatial resolution on a regional scale in China. We evaluated the performance of the eight GGCMs by utilizing a total of 1046 county-level maize yield data available over a 30-year period (1980–2010). Our findings reveal that the downscaled models created for maize yield simulations exhibited a remarkable level of accuracy (R2 ≥ 0.9, MAE < 0.5 t/ha, RMSE < 0.75 t/ha). The original GGCMs performed poorly in simulating county-level maize yields in China, and the improved GGCMs in our study captured an additional 17% variability in the county-level maize yields in China. Additionally, by optimizing nitrogen management strategies, we identified an average maize yield gap at the county level in China ranging from 0.47 to 1.82 t/ha, with the south maize region exhibiting the highest yield gap. Our study demonstrates the high effectiveness of machine learning methods for the spatial downscaling of crop models, significantly improving GGCMs' performance in county-level maize yield simulations. [ABSTRACT FROM AUTHOR]

Accurate cropland information is critical for agricultural planning and production, especially in foodstressed countries like China. Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades, considerable discrepancies exist among these products both in total area and in spatial distribution of croplands, impeding further applications of these datasets. The factors influencing their inconsistency are also unknown. In this study, we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020, including three state-of-the-art 10-m products (i.e., Google Dynamic World, ESRI Land Cover, and ESA WorldCover) and three 30-m ones (i.e., GLC_FCS30, GlobeLand 30, and CLCD). We also investigated the effects of landscape fragmentation, climate, and agricultural management. Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy (92.3%). These maps collectively overestimated Chinese cropland area by up to 56%. Up to 37% of the land showed spatial inconsistency among the maps, concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps, cropland fragmentation and management practices such as irrigation. Our work shed light on the promotion of future cropland mapping efforts, especially in highly inconsistent regions. [ABSTRACT FROM AUTHOR]

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Highway construction is vital in agricultural production, directly influencing food security and public health. This study utilized the Epsilon-based measurementglobal-Malmquist-model (EBM-GML) and the spatial econometrics model with 31 Chinese provinces' panel data from 2002 to 2020 to investigate the impacts and the mechanisms of low-grade and high-grade highways on the agricultural green total factor productivity (AGTFP). Research findings indicated that (1) lowgrade and high-grade highway construction significantly promote the AGTFP through technological progress, and the high-grade highway exerts a significant positive spillover effect on the adjacent areas' AGTFP. (2) The mechanisms of low-grade and high-grade roads on the AGTFP are heterogenous. Lowgrade roads could improve the AGTFP by encouraging the rationalization of the agricultural industry structure. High-grade highways promote the AGTFP by upgrading the industry structure. And each-grade road could promote the AGTFP by stimulating the integration of planting and breeding. (3) Both lowgrade and high-grade highways improved the AGTFP in non-main-grainproducing areas but inhibited it in main-grain-producing areas. Therefore, this study provided practical policy recommendations for green development in China's agricultural sector and valuable insights for other developing countries. [ABSTRACT FROM AUTHOR]

Irrigation district plays an important role in China's agricultural production. In recent years, China conducted many water-saving renovation construction projects of irrigation districts. However, the current implementation effect of irrigation district water-saving renovation has not been well-characterized. Comprehensive and systematic evaluation of the implementation effect of water-saving renovation in irrigation districts can provide scientific basis for further construction and management of irrigation districts. This study screened preliminary index system in four dimensions: preliminary work, completion of construction tasks, completion of planned investment, management and reform. Based on the statistical results of the questionnaire surveys and subsequently analyzed, fourteen key evaluation indicators were finally identified. Percentile system and expert evaluation method were then used to determine the assigned score of every indicator. Based on the evaluation criteria, the evaluation method of the implementation effect was formulated. Ten key medium-sized irrigation districts in southeastern China were taken as a research example in this study, with the implementation effect of water-saving renovation of 10 irrigation districts being comprehensively evaluated. The results show that these irrigation districts have a relatively high implementation effect of water-saving renovation. The data results from the scores of four dimensions and fourteen indicators show that the index system is reasonable and practicable, and the evaluation results are basically in line with actual situation. These findings have a good practical reference value for making decisions about how to instruct the modernization development of water-saving renovation of irrigation districts in China. [ABSTRACT FROM AUTHOR]

Although straw returning to the field (SRTTF) is conducive to promoting sustainable agricultural production and protecting the environment, straw resources are still wasted due to the lack of suitable straw-returning technology in southern China. Based on the statistical yearbook and a large number of studies, different methods were used to calculate the total straw resources and SRTTF potential, and differences in these methods were compared. The results indicate that the total amount of straw resources in southern China in 2021 was 3.35×108 t. The nutrient content of K2O in the straw accounted for the highest proportion of total nutrient resources (63.66%), followed by N (26.88%) and P2O5 (9.46%). In theory, total SRTTF could replace almost all K2O and part of N and P2O5, indicating that the nutrient substitution potential of SRTTF was high. It is suggested that the SRTTF method be adopted in the middle and lower reaches of the Yangtze River, which mainly uses direct returning (DR) supplemented by indirect returning (IDR). In southeast China, straw returning is carried out by the combination of IDR and IR. In southwest China, straw returning is mainly carried out by IR and supplemented by MDR. This study will provide theoretical support for the government to formulate straw-returning policy. [ABSTRACT FROM AUTHOR]

In recent years, China's crop production growth rate has decreased. This has provoked questions on whether the grain yields have reached their potential. Taking the North China Plain (NCP) as the study area, this study first simulated the potential yield of an irrigated maize crop with the WOFOST model, using daily weather data for 1960–2017. The yield gap was quantified for 1998–2017, and finally, the total potential maize production was estimated. The results indicate that during 1960–2017, the average potential yield for the region varied annually from 9.5 to 13.5 t ha−1, showing an obvious downward trend at a rate of 37.6 kg ha−1 per year. The long‐term mean potential yield at all 327 counties ranged from 9.9 to 13.7 t ha−1, increasing from south to north. The annual maize yield gap was between an average of 2.7–6.0 t ha−1 (29.0%–51.3%) of the potential yield for the NCP during 1998–2017. At county‐level, the yield gap varied between 1.9 and 7.8 t ha−1 and exceeded 5.0 t ha−1 for 99 counties (30.3% of all counties). Attainable yields can be increased by 0.1–5.2 t ha−1 at county‐level, and by 2.2 t ha−1 for the whole NCP, implying that the maize production has the potential to increase with 20.8 Mt. To increase maize production, the focus areas should be the southcentral NCP, which have a larger yield gap during 2012–2017. [ABSTRACT FROM AUTHOR]