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Sustainable agricultural economic development is the core task for achieving the objective of rural revitalization strategy in China, which cannot be separated from the support and guidance of fiscal policy, and agricultural industry integration is a key path for the fiscal promotion of sustainable agricultural economic development. This paper systematically examines the interaction mechanism between fiscal agricultural expenditures and sustainable agricultural economic development by using 31 provincial panel data in China from 2008 to 2020 and adopting a two-way fixed effect model, a panel quantile model, and a mediating effect model, respectively. The results show that the impact of fiscal agricultural expenditures on sustainable agricultural economic development is significantly positive, and appears a dynamic increasing trend with the agricultural development stage upgrading. Moreover, heterogeneity analysis shows that the effect of fiscal agricultural expenditures is more obvious for the samples in the central region and with a high share of primary industry. Further, a mediating effect test finds that agricultural industry integration plays a mediating mechanism between fiscal agricultural expenditures and sustainable agricultural economic development. Therefore, this paper proposes constructing a long-term investment mechanism for fiscal agricultural expenditures, formulating differentiated fiscal support policies for agriculture, and prioritizing support for agricultural industry integration, which provides theoretical support and policy inspiration for promoting sustainable agricultural economic development. [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]

Because the complexity of the external environment has put great pressure on the agricultural economy, making it vulnerable, it is necessary to promote a system of resilience in the agricultural economy so that Chinese agriculture can continue to persevere in the face of serious external uncertainties. Therefore, this paper investigates the spatio-temporal pattern and evolution of the distributional dynamics of China's county-level agricultural economic resilience based on 2000–2020 data covering 2,545 counties. The results are as follows: first, from 2000 to 2020, the mean value of China's county-level agricultural economic resilience showed an obvious upward trend, which indicates that China's agricultural economy gradually increased its ability to resist risks and continued to develop in a favourable manner. Specifically, the county-level agricultural economic resilience index of the northeast region grew the most significantly, while the index of county units in the western region was relatively low. Second, the centre of gravity of the spatial distribution of China's agricultural economic resilience gradually migrated to the northwest, showing a dominant direction from northeast to southwest and a tendency to develop from southeast to northwest. Third, the spatial differences in China's agricultural economic resilience generally showed an upward trend, while county-level differences were the main source of the overall differences, followed by inter-provincial differences, inter-municipal differences and inter-regional differences. Additionally, the contribution of county-level differences to the overall differences fluctuated within the range of 54%-58%. Fourth, there is a possibility of localized convergence in China's agricultural economic resilience, which is continuous in spatial effects and has obvious positively correlated spatial effects at different times and in different county spaces. [ABSTRACT FROM AUTHOR]

Winter wheat is a significant global food crop, and it is crucial to monitor its distribution for better agricultural management, land planning, and environmental sustainability. However, the distribution style of winter wheat planting fields is not consistent due to different terrain conditions. In mountainous areas, winter wheat planting units are smaller in size and fragmented in distribution compared to plain areas. Unfortunately, most crop-mapping research based on deep learning ignores the impact of topographic relief on crop distribution and struggles to handle hilly areas effectively. In this paper, we propose a cross-modal segmentation network for winter wheat mapping in complex terrain using remote-sensing multi-temporal images and DEM data. First, we propose a diverse receptive fusion (DRF) module, which applies a deformable receptive field to optical images during the feature fusion process, allowing it to match winter wheat plots of varying scales and a fixed receptive field to the DEM to extract evaluation features at a consistent scale. Second, we developed a distributed weight attention (DWA) module, which can enhance the feature intensity of winter wheat, thereby reducing the omission rate of planting areas, especially for the small-sized regions in hilly terrain. Furthermore, to demonstrate the performance of our model, we conducted extensive experiments and ablation studies on a large-scale dataset in Lanling county, Shandong province, China. Our results show that our proposed CM-Net is effective in mapping winter wheat in complex terrain. [ABSTRACT FROM AUTHOR]

Vietnam's agricultural exports to China have remained strong, with the country maintaining its position as the top destination for Agri-products. This article primarily utilizes the Revealed Comparative Advantage (RCA) Index, and Trade Complementarity (TC) index to examine the trade comparative advantage, and the complementary of twenty major agricultural products between China and Vietnam from 2012 to 2021. The study results showed that Vietnam and China frequently exchange agricultural products. Vietnam has more stronger competitiveness than China in terms of agricultural products. China's exports to Vietnam were highly complementary to Vietnam's imports in category 0 whiles Vietnam's exports to China showed strong complementarity with China's imports in category 2. This paper analyzes the complementarity and comparative advantages of agricultural trade between China and Vietnam, and proposes informed suggestions for policy-making to promote agricultural trade between the countries. The proposed suggestions aim to expand agricultural trade between the two countries, reduce the trade imbalance, and achieve mutual benefit and win-win results. [ABSTRACT FROM AUTHOR]

Using the panel data of 31 provinces in China between 2000 and 2018, this study theoretically and empirically analyses the impact of environmental regulations on the adjustment of the agriculture industrial structure from the perspectives of rationalisation and optimisation. Overall, variability in the impact of environmental regulation on the adjustment of the agricultural industrial structure is identified: a negative influence on the rationalisation of agricultural industrial structure and a positive influence on the optimisation of agricultural industrial structure. The impact of environmental regulations on the adjustment of agricultural industrial structure also reflects "large country characteristics": environmental regulations are more significant at the medium and low industrial structure levels. Environmental regulation significantly impacts the rationalisation of agricultural industrial structure in central and western regions and its optimisation in eastern and central regions. Through the panel threshold model test, this paper further finds that the effect of environmental regulations on the adjustment of agricultural industrial structure is not invariant. However, there is a non-linear relationship with significant threshold characteristics. Based on the above results, some countermeasures are suggested. [ABSTRACT FROM AUTHOR]

The long-term and stable development of agriculture is the key to China's economic development and social stability. Agricultural total factor productivity and the digital economy have become new kinetic energy and new engines driving agricultural high-quality development. It is of great significance to verify whether there are significant spatial and threshold effects in the process of high-quality development of agriculture and to explore the intrinsic relationship between high-quality development of agriculture and agricultural total factor productivity and digital economy. This paper takes 31 provinces in China from 2011 to 2020 as the research object. The coefficient of variation method is used to estimate the comprehensive evaluation index of agricultural high-quality development and digital economy. And Dea-Malmquist index method is used to estimate agricultural total factor productivity. On this basis, the spatial Durbin model and threshold regression model are constructed to explore the spatial and threshold effects of agricultural total factor productivity, digital economy and other factors and high-quality agricultural development. The conclusion is as follows: the high-quality development of agriculture has significant spatial autocorrelation. Agricultural total factor productivity and digital economy have significant direct effect and indirect spillover effect on the high-quality development of agriculture. Agricultural total factor productivity has stage differences in each range of digital economy level, but its influence on agricultural high-quality development shows a positive state. Based on this, the paper puts forward some countermeasures to promote the high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

In the context of the Chinese government's policy guidance, there is black soil protection and ecological environment protection. The purpose of this paper is to solve the problem that the soil ecology of the black soil in Northeast China is changing year by year, and it is necessary to explore the sowing and fertilization strategy under the new situation; most Chinese growers rely excessively on their personal experience in the process of soybean sowing and fertilization. In this study, we used "Heihe 43" soybeans and used regression experimental design methods to analyze the effects of planting density, nitrogen, phosphorus, and potassium fertilizer application on soybean yield and to determine the optimal planting density and fertilizer ratios. The study reveals that the optimal soybean planting density in Northeast China is 45.37 × 104 plants/ha, with nitrogen at 98.4 kg/ha, phosphorus at 218.96 kg/ha, and potash at 47.62 kg/ha. Under these conditions, soybean yields can reach 3816.67 kg/ha. This study can provide a theoretical method for decision-making to obtain the optimal planting density and fertilizer ratio for different regions of the farming system. [ABSTRACT FROM AUTHOR]

Plant protection drones are fast and efficient application machines that are characterised by high application efficiency and no damage to crops. They are particularly suitable for small areas of farmland and mountainous terrain in regions such as Asia and are currently the dominant insecticide application technology in China. The presence of wind is a prerequisite for the spread and dissemination of airborne diseases and it can directly influence the distance and height of ascent of pathogenic spores. This paper investigates the effect of downwash airflow generated by the flight altitude of a plant protection drone on the horizontal distribution, vertical distribution and ground distribution of powdery mildew spores in wheat. Monitoring the changing dynamics of airborne powdery mildew conidia using spore traps. The test results show that: the number of powdery mildew pathogenic spores is related to various factors such as weather, relative humidity and wind speed; the release of spores is greatly influenced by airflow disturbances but has little effect at the early stages of sporulation; the disease is caused by the accumulation process of pathogenic spores and in the control of powdery mildew in wheat, preventive spraying should be carried out within 2–3 days of the germination of pathogenic spores. The study lays the foundation for further in-depth research on the spread of powdery mildew spores and improved pest control, and provides a basis for scientific and rational spraying and control by agricultural drones. [ABSTRACT FROM AUTHOR]

Agricultural sensors are essential technologies for smart agriculture, which can transform non-electrical physical quantities such as environmental factors. The ecological elements inside and outside of plants and animals are converted into electrical signals for control system recognition, providing a basis for decision-making in smart agriculture. With the rapid development of smart agriculture in China, agricultural sensors have ushered in opportunities and challenges. Based on a literature review and data statistics, this paper analyzes the market prospects and market scale of agricultural sensors in China from four perspectives: field farming, facility farming, livestock and poultry farming and aquaculture. The study further predicts the demand for agricultural sensors in 2025 and 2035. The results reveal that China's sensor market has a good development prospect. However, the paper garnered the key challenges of China's agricultural sensor industry, including a weak technical foundation, poor enterprise research capacity, high importation of sensors and a lack of financial support. Given this, the agricultural sensor market should be comprehensively distributed in terms of policy, funding, expertise and innovative technology. In addition, this paper highlighted integrating the future development direction of China's agricultural sensor technology with new technologies and China's agricultural development needs. [ABSTRACT FROM AUTHOR]

Affected by global warming, the frequency of crop pests and diseases have increased, causing huge losses to agricultural production. To better grasp the development and trends of research on the effects of climate change on crop pests and diseases, the literature on the impact of climate change on crop pests and diseases published from 1990 to 2021 in the Web of Science (WOS) core collection database was used. This study explores the literature characteristics and hotspot evolution through the bibliometric visualization analysis software COOC, VOSviewer, and CiteSpace, with a view to identifying the changing characteristics and trends of research changes in this field. The results showed that the number of literature on the impact of climate change on crop pests and diseases increased rapidly. The main fields involved include environmental sciences, ecology, and agronomy. Papers in these fields mainly published in journals, such as PLos One, Forest Ecology and Management, and Frontiers in Plant Science. The country with the highest number of publications was the United States, followed by China and Australia. The most prolific authors in the top 20 are research scholars from China. The first author of the top 20 highly cited papers was from the United States. It was found that that current research on the impact of climate change on crop pests and diseases mainly focuses on agricultural production and food safety. Modelling and crop growth has maintained steady development. At present, research in this field mainly focuses on pest management strategies under the impact of climate change, the response of single species, and the complex ecological mechanisms behind the response. This study provides unique insights into the research field of the impact of climate change on crop pests and diseases and provides a reference direction for future research development in this field. [ABSTRACT FROM AUTHOR]

Recently, China has exerted great efforts to develop agro-industrial agglomerations and optimize the agricultural industry's regional distribution to increase farmers' income. This study posits that agro-industrial agglomeration should be "dual body," provides a theoretical framework for agro-industrial agglomeration's effects on farmer income, and uses a spatial panel model to prove its influence on farmers' income and the spatial spillover effect. The results show that agro-industrial agglomeration in a specific region significantly impacts farmers' income and also has a spillover effect on income in adjacent regions. Further research shows that, contrary to traditional agglomeration theory, agricultural industry agglomeration has little impact on farmers' agricultural production but primarily promotes the establishment and development of agricultural organizations, thus improving farmers' income. Finally, the paper discusses the positive and negative effects of agro-industrial agglomeration on the Global Sustainable Development Goals(SDGs), and proposes some useful suggestions. [ABSTRACT FROM AUTHOR]

Improving agricultural energy efficiency is essential in reducing energy consumption and achieving agricultural sustainable development. This paper aims to measure the agricultural total-factor energy efficiency in China rather than the partial-factor energy efficiency while taking full account of regional heterogeneity and to investigate the driving factors of agricultural total-factor energy efficiency. The empirical results showed that the average value of agricultural total-factor energy efficiency is 0.814 in China, and the technological gap ratio is 0.853. The regional difference in agricultural total-factor energy efficiency was quite obvious. Higher agricultural energy inputs are associated with higher agricultural total-factor productivity. The total value of potential agricultural energy savings in 30 provinces of China reached 1704.41 billion tons of standard coal. In terms of the absolute amount of agricultural energy saving, the amount was largest in the low-energy-input area, which was 113.87 million tons of standard coal, accounting for 66.81% of the total potential saving amount. Furthermore, we used the Tobit model to analyze the influencing factors of agricultural total-factor energy efficiency. We found that the proportion of agriculture to GDP has a positive impact on agricultural total-factor energy efficiency, while the per capita income of farmers, fiscal support for agriculture, the illiteracy rate of farmers, agricultural labor input, and agricultural capital stock have a negative impact on agricultural total-factor energy efficiency. Finally, we proposed policy implications in terms of agricultural technological progress, agricultural infrastructure, technical training, etc. [ABSTRACT FROM AUTHOR]

With the development of the market economy, agricultural trade has become more and more significant for the development of the agricultural economy, which has triggered people's further thinking and exploration on the impact of agricultural trade on agricultural carbon emissions. This paper takes the measurement of trade implied carbon as the carbon dioxide emission index under the impact of agricultural trade and analyzes the impact of trade implied carbon and implied carbon balance on carbon emission. Taking the impact of Sino-US agricultural trade as an empirical background, this paper measures the impact of environmental changes in agricultural trade opening on China's agricultural development and its carbon emissions, so as to predict changes in China's regional agricultural carbon emissions performance. After calculation, it is found that the scale of China's exports has decreased by 0.089%, which is lower than the decline of 0.361% in the United States. The trade conflict has a significant impact on China's import and export structure. Under the scenario of mutual tariffs on agricultural products, China's exports to the United States are expected to decrease by 6.28%, while China's imports from the United States decreased by 13.02%. The Sino-US agricultural trade dispute will reduce China's carbon emissions by 0.013% and the United States' carbon emissions by 0.024%, which is related to the negative impact on the economy. Improving the performance of agricultural carbon emissions is not only the need for the green and sustainable development of the agricultural economy but also conducive to improving the international competitiveness of agricultural products. [ABSTRACT FROM AUTHOR]

Rice is an important food crop in China, and diseases and pests are the main factors threatening its safety, ecology, and efficient production. The development of remote sensing technology provides an important means for non-destructive and rapid monitoring of diseases and pests that threaten rice crops. This paper aims to provide insights into current and future trends in remote sensing for rice crop monitoring. First, we expound the mechanism of remote sensing monitoring of rice diseases and pests and introduce the applications of different commonly data sources (hyperspectral data, multispectral data, thermal infrared data, fluorescence, and multi-source data fusion) in remote sensing monitoring of rice diseases and pests. Secondly, we summarize current methods for monitoring rice diseases and pests, including statistical discriminant type, machine learning, and deep learning algorithm. Finally, we provide a general framework to facilitate the monitoring of rice diseases or pests, which provides ideas and technical guidance for remote sensing monitoring of unknown diseases and pests, and we point out the challenges and future development directions of rice disease and pest remote sensing monitoring. This work provides new ideas and references for the subsequent monitoring of rice diseases and pests using remote sensing. [ABSTRACT FROM AUTHOR]

Groundwater droughts can explain developments and changes in groundwater from a climatological perspective. The North China Plain (NCP) is a typical underground funnel area. Therefore, groundwater drought studies in the NCP can provide better understanding of the local hydrogeological characteristics from new perspectives. In this paper, the GRACE groundwater drought index (GGDI) was used to evaluate groundwater drought events in the NCP. Additionally, a new method was proposed in this study for investigating groundwater drought events at the spatiotemporal scale. On this basis, the centroid theory was used to construct an appropriate groundwater drought migration model for the NCP. The results showed that (1) the groundwater drought frequency in the NCP was 24.54%. In addition, the most severe groundwater drought events in the study occurred in March 2020. (2) In total, 49 groundwater drought events occurred in the NCP over the 2003–2020 period. The most intense groundwater drought event occurred over the June 2018–December 2020 period (DE.49), covering the entire study area. DE.29 was the second most intense groundwater drought event over the August 2012–September 2013 period (14 months), resulting in a maximum arid area of 75.57% of the entire study area. (3) The migration of the groundwater drought events was in the southwest–northeast and northeast–southwest directions, which was consistent with the terrain inclination, while most of the groundwater drought centroids were concentrated in Area II. The groundwater drought event identification method and the groundwater drought migration model were effective and reliable for assessing groundwater drought events in the NCP and provided a better understanding of developments and changes in groundwater droughts, which is of great practical significance and theoretical value for the rational development and use of groundwater resources, as well as for guiding industrial and agricultural activities. [ABSTRACT FROM AUTHOR]

Based on the background of rural strategy, this paper combines the theories related to supply-side and supply-side structural reform at home and abroad, and dovetails the target contents of agricultural supply-side structure and rural revitalization strategy. Using survey data to analyse the current situation of agricultural supply-side structural reform, summarize the positive achievements of agricultural supply-side structural reform in recent years, and analyse the problems it faces in the process of agricultural supply-side structural reform. Through an in-depth analysis of the current situation of agricultural supply-side structure, we analyse the reasons for promoting agricultural supply-side structural reform and the new situation and contradictions faced and identify the cruxes that restrict the comprehensive efficiency of agriculture and competitiveness of agricultural products. The super-efficient DEA model is used to quantify the financial resource allocation to study the impact efficiency of agricultural supply-side structural reform capacity. This study uses the comparative advantage analysis method to systematically study the production efficiency and farm household income of food crops, and the comprehensive comparative advantage index method is introduced when constructing the comparative advantage analysis index system to derive agricultural products with comparative advantage. The Gray correlation analysis method was used to analyse the degree of influence of agricultural products, major technical means, and institutional measures on the total output value of the plantation industry in the structure of the plantation industry respectively. The original hypothesis was rejected by conducting a Hausman test on the panel data using Eviewsll software. In the empirical analysis, factor analysis was conducted on the index data of agricultural by-products production with the help of the spss tool to derive the index of agricultural by-products industry development. The article provides a strong institutional guarantee to improve the quality of agricultural development and competitiveness of agricultural products, to explore a new road of modern agricultural development with reasonable layout, optimized structure, high quality and efficiency, green health, and openness and sharing for agricultural development. Accelerating the supply-side structural reform of agriculture has become the general keynote of China's agricultural and rural work for the current and future period, and is of great practical significance for maximizing the comprehensive benefits of agriculture, promoting farmers' income, and developing green and sustainable agriculture. [ABSTRACT FROM AUTHOR]

The classification that distinguishes whether machines are driving on roads or working in fields based on their global navigation satellite system (GNSS) trajectories is essential for effective management of cross-regional agricultural machinery services in China. In this paper, a novel field–road classification method utilizing multiple deep neural networks (MultiDNN) is proposed to enhance the accuracy of field and road point classification. The MultiDNN model incorporates a bi-directional long short-term memory network (BiLSTM), a topology adaptive graph convolution network (TAG), and a self-attention network (ATT) to effectively extract spatio-temporal features for field–road classification. The BiLSTM is used to capture temporal relationships along the time axis of a trajectory, providing global contextual information for each point. Then, the TAG network is used to obtain the spatio-temporal relationships between adjacent points in a trajectory, offering local contextual information for each point. Finally, the ATT network assigns varying weights to features to emphasize important characteristics. The performance of the MultiDNN model was evaluated using a wheat harvesting trajectory dataset, and the results showed that it achieved a high degree of accuracy, up to 89.75%, outperforming the best baseline method (GCN) by 2.79%. [ABSTRACT FROM AUTHOR]

China agricultural development has been facing the problem of resource constraints because its resources per capita such as land and energy are relatively lower than the global average. By applying the provincial agricultural panel data from 2000 to 2015 and fixed effect model based on the translog production function, this paper estimates both output elasticities and substitution elasticities of agricultural inputs, which may provide insights into sustainable agricultural development. The results show that, except for capital, the output elasticities of other production factors are all positive. Energy has always played an important role in agricultural production, whose elasticity in agriculture increased from 0.0203 in 2000 to 0.1694 in 2015. We also find a severe scarcity of land, and the high intensity of energy in the field of agriculture. Moreover, there exists a substitute relationship between all factors, which means that in the short term, one production factor can be employed to replace another to maintain agricultural development. From the empirical results of this paper, some policy suggestions are proposed as follows: it is crucial that more attention should be placed on land and to plan energy use wisely. In addition, on account of the current situation in China, the input of labor force should be stepped up and energy should be used more efficiently to make up for the shortage of land resources. The empirical results and policy suggestions in this paper may benefit the sustainable development of China's agricultural economy. [ABSTRACT FROM AUTHOR]

Given the background of the rural population ageing, the reduced agricultural non-point source pollution and the decreased agricultural carbon emission, agricultural producer services, as an important bridge between small farmers and modern agriculture, are an important path to ensure food security and the green development of agriculture. Based on panel data of 31 provinces in China from 2003 to 2020, this paper uses Slack-based measure model with undesirable outputs (SBM-undesirable model)to calculate the agricultural ecological efficiency of 31 provinces. Furthermore, the two-stage least squares, the panel threshold model and the spatial Durbin model are used to empirically analyze the influence mechanism and the spatial spillover effect of agricultural productive services on agricultural ecological efficiency. The results show that agricultural producer services have a significant non-linear impact on agricultural ecological efficiency. Rural residents' income and per capita cultivated land area can adjust the relationship between them. The two main ways for agricultural productive services to improve agricultural ecological efficiency are as follows: reducing undesirable outputs such as pesticides, chemical fertilizers and plastic sheeting for agricultural use and improving agricultural production efficiency. In addition, agricultural producer services have a significant positive spatial spillover effect on agricultural ecological efficiency, and the indirect impact elasticity of spatial spillover is higher than the direct impact elasticity. Therefore, to achieve food security and promote the sustainable development of agriculture, it is necessary to vigorously develop agricultural productive services through multiparty cooperation. [ABSTRACT FROM AUTHOR]

Measuring regional differences in agricultural green total factor productivity (AGTFP) provides a basis for policy guidance on agricultural green development in the Yangtze River Delta (YRD) region. By constructing a two-period Malmquist–Luenberger index under the carbon emission constraint, we measure the AGTFP of cities in the YRD region from 2001 to 2019. Furthermore, adopting the Moran index method and the hot spot analysis method, this paper analyzes the global spatial correlation and local spatial correlation of AGTFP in this region. Moreover, we investigate its spatial convergence. The results show that the AGTFP of 41 cities in the YRD region is on an increasing trend; the growth of AGTFP in the eastern cities is mainly driven by green technical efficiency, while this growth in the southern cities is mainly stimulated by green technical efficiency and green technological progress. We also find a significant spatial correlation between cities' AGTFP in the YRD region from 2001 to 2019, but with certain fluctuations, showing a U-shaped trend of "strong-weak-strong". In addition, absolute β convergence of the AGTFP exists in the YRD region, and this convergence speed is accelerated with the addition of spatial factors. This evidence provides support for implementing the regional integration development strategy and optimizing the regional agricultural spatial layout. Our findings offer implications for promoting the transfer of green agricultural technology to the southwest of the YRD region, strengthening the construction of agricultural economic belts and agricultural economic circles, and improving the efficiency of agricultural resource use. [ABSTRACT FROM AUTHOR]

Effective prevention and control of agricultural non-point source pollution is a major challenge faced by the Chinese local government in the context of rural revitalization, and clarifying the game relationship between stakeholders in agricultural non-point source pollution control actions will help achieve multiple co-governance better. Accordingly, this paper discusses the interactive decision-making relationships between local government and livestock and poultry breeding enterprise (LPBE) under the participation of Environmental non-government organizations (ENGOs) and public, by constructing an evolutionary game model, as well as analyzing evolutionary cooperative stability strategies and realizing the simulation of evolution processes in different scenarios by MATLAB. The results show that government subsidy has an incentive effect on LPBE to adopt the purifying strategy, yet reduces the enthusiasm of local government for supervision. Improving the participation degree and right space of ENGOs is conducive to the realization of multiple co-governance models. Furthermore, the impact of public participation on multiple co-governance of agricultural non-point source pollution is related to the local government's investigation rate and the public reporting fairness; strengthening the local government's supervision capacity and improving the public reporting fairness can achieve better collaborative governance effects. [ABSTRACT FROM AUTHOR]

The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China. [ABSTRACT FROM AUTHOR]

With the increasing severity of global warming, the goal of carbon sequestration and emission reduction in various industries has become an important responsibility for sustainable development. As an important part of carbon sink, the improvement of net carbon efficiency in the plantations industry will make a great contribution to the realization of the "double carbon" target in agriculture. However, there are large spatial and temporal differences in the net carbon efficiency of the plantations sector in various provinces, and there is still a large scope for increasing carbon sink and reducing carbon emission. In this paper, we have analyzed spatial and temporal trends in the net carbon sink efficiency of the plantations' production processes in 31 provinces in China (excluding Hong Kong, Macao and Taiwan) from 2000 to 2020. On this basis, we have analyzed the influencing factors of net carbon efficiency in the plantations' production process through an extended Kaya constant equation. Through the geographically and temporally weighted regression model, we explore the spatio-temporal heterogeneity of the influencing factors, and further analyze the driving and restraining factors of net carbon efficiency in plantations' production process, in order to propose appropriate countermeasures. The study shows that: (1) The net carbon efficiency of plantations sector in China increase between 2000 and 2020, and the development of net carbon efficiency is uneven across regions. (2) The geographic center of net carbon efficiency of China's plantations industry shift from the northeast to the southwest and is consistent with the migration direction of agricultural inputs. (3) The influencing factors of net carbon efficiency in the plantations sector show large regional differences, and can be specifically divided into four major types of zones. In this regard, this paper provides more appropriate countermeasure suggestions for increasing carbon sink and reducing carbon emission in each zone, with a view to achieving the goal of double carbon in agriculture with practical significance. • Net carbon efficiency is a new objective indicator to measure the carbon sink level of cropland. • Cultivated land carbon sink capacity is closely related to agricultural inputs. • Regional differences in the factors influencing net carbon efficiency. [ABSTRACT FROM AUTHOR]

Climate change has a significant impact on agriculture so it is necessary to adapt to climate change to promote agricultural transformation and sustainable development. The key to achieving such a goal is to promote the development of climate smart agriculture (CSA) against the background of climate change. The paper first uses official statistical data to evaluate the effect of climate smart agricultural technology project, and then uses the statistical method of questionnaire survey to further investigate and statistically analyze the implementation effect of climate smart agricultural technology project in the pilot area. Further, semi-structured interview method is employed to conduct more in-depth investigation and analysis on some main topics on the basis of preliminary investigation and statistical analysis. The interviews focus on the environmental and economic effects of project practice, the difficulties of smallholder farmers' technology extension, and the farmers' willingness to participate. The study indicates that to promote climate smart agriculture technologies is an effective way to solve agricultural problem in practice under the background of climate change, and can achieve at least three benefits. The first is to reduce production costs, which can be reduced by 10% to 15% in terms of fertilizers and pesticides alone. The second is to improve productivity, and preliminary results show that food production can be increased by more than 5%. Finally, it has carbon sequestration capabilities and can significantly reduce greenhouse gas (GHG) emissions. Therefore, the promotion of climate smart agriculture (CSA) technologies helps to solve the problem of agricultural transformation and sustainable development. To this end, it is necessary to drive the transformation and optimization of regional agricultural ecological environment and production system, and promote the innovation and extension of CSA technology. In addition, some soft conditions (e.g., talent, system and technology, etc.) and hard conditions (e.g., modern agricultural supply chain, agricultural big data and the Internet of Things, etc.), must be created, too. [ABSTRACT FROM AUTHOR]

China's agricultural economy is developing rapidly, but the unbalanced regional development is still a key issue that needs to be discussed today. By studying the total factor productivity of green agriculture and its factors, this paper analyzes the regional differences in time and space changes between the eastern, central and western parts of China. In this paper, the total factor productivity of green agriculture is calculated and decomposed by Metafrontier Malmquist-Luenberger index based on directional distance function. The results are as follows: First, the total factor productivity level of green agriculture in China is increasing year by year, but the overall level is still at a low level and has greater volatility; Second, although the total factor productivity of green agriculture shows an upward trend, the three regions show a downward trend in turn, which has great differences; Third, there are obvious differences in technological efficiency, optimal production potential and technological gap between the eastern, central and western regions, and there are great differences in productivity among regions and provinces. Based on the results, this paper puts forward policy recommendations, according to the regional heterogeneity, from a number of angles to rely on the joint efforts of many parties to improve the level of total factor productivity of green agriculture. [ABSTRACT FROM AUTHOR]

Background: Shexian Dryland Stone Terraced System (SDSTS) in the Taihang Mountains was formally recognized as Globally Important Agricultural Heritage Systems (GIAHS) by Food and Agriculture Organization on May 20, 2022. People there have been relying on the terraced fields for centuries, using various plants, including medicinal plants. However, little information was reported about the flora in SDSTS, nor medicinal plants. Thus, the present study aims to identify and document medicinal plants traditionally used by the local people living around the SDSTS and associated ethnobotanical knowledge. Methods: We conducted investigations in Shexian County, Hebei Province, North China, where SDSTS is distributed. Then, Wangjinzhuang, a community located in the core zone of SDSTS, was chosen as the case site. We selected the informants through purposive and snowball sampling. The data were collected through semi-structured interviews, participant observation, and key informant interviews. The medicinal plants traditionally used by the local people were documented and analyzed. We examined and confirmed the botanical identification based on voucher specimens and by cross-checking the descriptions with the series of books, scientific papers on medicinal plants, and the plant databases. Results: The local people have rich traditional knowledge to collect and use medicinal plants in SDSTS. Records of 123 medicinal plant species belonging to 51 families were obtained from SDSTS. Asteraceae was represented by 16 species, followed by Fabaceae, Lamiaceae and Ranunculaceae. (They all have 8 species.) The majority of the reported plant species were commonly processed into decoctions. And 180 diseases affecting humans were reported to be treated with traditional medicinal plants from SDSTS. Conclusion: It is the first ethnobotanical study on medicinal plants in China-Nationally Important Agricultural Heritage Systems, and in globally important agricultural heritage systems as well. Medicinal plants are crucial for people living in Shexian County. It is necessary to recognize and respect traditional knowledge peculiar to the mountainous region of northern China, especially for those involved in the human–nature interaction and the role of knowledge in agrobiodiversity conservation and rural development that local residents have persisted for centuries. [ABSTRACT FROM AUTHOR]

[Display omitted] • A comprehensive assessment method of cropland abandonment risk based on AHP and PCA was proposed. • The verification results show that the risk assessment method proposed in our article is objective. • The high risk area is mainly distributed in the Lancang and Honghe River Basin. • Suggestions for preventing cropland abandonment are based on dominant factors of abandonment. Assessing the risk of cropland abandonment in mountainous area is essential for ensuring food security. However, the current evaluation indicator system is incomplete, and the reliability analysis of the results is lacking. This paper proposes a spatially comprehensive assessment method of cropland abandonment risk based on AHP and PCA using multi-source data of land use, abandoned cropland, administrative area, population density, GDP, cropland soil information, and climate, and applies the method to Yunnan Province in China. Firstly, 14 indicators were selected from four aspects, including social factors, farming conditions, cropland quality, and climate factors, to construct a three-layer indicator system of "target-criteria-indicator". Fuzzy membership was used to calculate the indicator layer, and then the PCA method was applied to calculate the first principal component for the criterion layer. Finally, the AHP method was used to calculate the weighted superposition of the criterion layer. The proposed method showed good reliability in the study areas. In Yunnan Province, 33.03% of cropland is at high risk of abandonment, 37.52% is at medium risk, and 29.45% is at low risk. The high risk area is mainly distributed in the Lancang River Basin and Honghe River Basin. Social factors were found to play the greatest role in the risk of cropland abandonment in Yunnan Province. Factors such as low population density, large shape coefficient of cropland, and low annual average precipitation were identified as the main drivers of cropland abandonment in this region. The research results of this paper can provide decision-making reference for preventing and controlling cropland abandonment in mountainous areas. [ABSTRACT FROM AUTHOR]

Agriculture is the foundation of every country's survival and development. This paper analyzes the interaction between the business environment, agricultural opening-up and high-quality agricultural economy from the perspective of China's provinces. According to the panel data of 31 provinces and municipalities in China from 2009 to 2019, the empirical analysis was carried out based on the panel vector autoregression (PVAR) model. The results show that there is a quantitative interaction between China's business environment, agricultural opening-up and high-quality agricultural development, and the long-term time effect is very obvious. Specifically, (1) the impact of the business environment and the high-quality development of agriculture on itself is decreasing year by year. The agriculture opening-up itself has a strong impact and has always maintained strong stability. (2) The high-quality development of the agricultural economy has little impact on the business environment and the opening of agriculture to the outside world, but it has a certain stable and continuous effect. It is particularly important that the agricultural opening-up has an increasingly strong effect on the business environment and the high-quality development of the agricultural economy as time progresses. Therefore, we must always adhere to the agriculture opening-up. The regional business environment and the agriculture opening-up can jointly promote the high-quality development of the agricultural economy. The research results can provide a basis and reference for the central and local governments to formulate relevant agricultural development policies and provide a reference for relevant agricultural economic entities and enterprises. [ABSTRACT FROM AUTHOR]

Accurate forecasting of the agricultural power load is important for rural electricity networks' safe and stable operation. But it is more uncertain and difficult to forecast than industrial, commercial, and residential loads. Multivariate time series prediction methods have problems such as poor refinement of weather services and difficulty in quantifying the influencing factors. Univariate time series prediction methods should be emphasized, and the characteristic information in the historical load data should be fully exploited. Therefore, this paper systematically investigates the decomposition strategy and attention-based recurrent neural network for univariate time-series multi-step prediction. The decomposition strategy is employed to generate derived variable sequences from the target sequence as inputs for the model, while the dual-stage attention mechanism is used for dynamically selecting features. A one-year real-world dataset of agricultural power loads in southern China is used for validation. The effectiveness of two different decomposition algorithms on dual-stage attention-based recurrent neural network (DARNN) is discussed, then the proposed ensemble empirical mode decomposition and dual-stage attention-based recurrent neural network (EEMD-DARNN) is compared with four univariate time series prediction models and three ablation models. The proposed model is optimal in four evaluation indicators, with R 2 , R M S E , M A P E , and M A E of 0.970, 12.298, 0.040, and 7.335 respectively in the shortest forecast horizon (15 min), and 0.941, 17.305, 0.065 and 11.347 respectively in the longest forecast horizon (1 h). It is a significant improvement over the existing models. In conclusion, EEMD-DARNN can achieve more accurate ultra-short-term agricultural power load forecasting. [ABSTRACT FROM AUTHOR]

Being one of the significant conduits linking international and domestic markets, agricultural trade is an area of study that commands attention. While it may bring about transnational carbon emission transfers, it begs the question: does it promote carbon reduction in a country's agricultural sector? Such an inquiry holds profound implications for optimizing agricultural trade and promoting low-carbon agricultural advancement. Utilizing two-way fixed effect model, mediating effect model and dual-fixed spatial Durbin model, this paper examines the impact effects, mechanisms and spatial characteristics of agricultural trade openness (ATO) on agricultural carbon reduction using panel data from Chinese provinces spanning 2000 to 2021. The main findings include: (1) ATO markedly and positively influences the reduction of agricultural carbon emissions (ACE), this conclusion maintains its validity under endogeneity treatment and robustness tests. (2) ATO contributes to reducing ACE through three intermediary channels: scale effect, technological effect, and structural effect. (3) From a spatial perspective, a notable positive spatial spillover effect is observed from agricultural trade openness to agricultural carbon reduction, with the spatial carbon reduction effect being more apparent. (4) The spatial carbon reduction effect of agricultural trade liberalization exhibits heterogeneity across different natural geographical locations and levels of ATO. The study confirms the vital role of ATO in promoting agricultural carbon reduction in typical countries, underscoring the urgency and importance of bolstering cross-border agricultural trade cooperation and domestic agricultural product circulation in the domain of climate change. • The impact of agricultural trade openness (ATO) on agricultural carbon reduction is investigated in China. • The scale, technological, and structural effect of ATO serve as intermediary channels in reducing carbon emissions. • ATO engenders positive spatial spillover effects on agricultural carbon reduction. • Bolstering cross-border agricultural trade cooperation are of importance and urgency in the domain of climate change. [ABSTRACT FROM AUTHOR]

Agricultural and Rural Green Development (ARGD) and economic growth are major challenges prevalent in China, but also in other developing countries. A notable gap in current literature lies in the limited holistic approach to agriculture and rural areas, with scant attention being paid to the spatiotemporal evolution of ARGD and its coordination relationship with economic growth. This paper first offers a theoretical analysis of the interactive relationship between ARGD and economic growth and subsequently examines the policy implementation process in China in this regard. It observes 31 provinces in China from 1997 to 2020 to uncover the spatiotemporal evolution of Agricultural and Rural Green Development Efficiency (ARGDE). Using the coupling coordination degree (CCD) model and the local spatial autocorrelation model, this paper analyses the coordination relationship and spatial correlation between ARGDE and economic growth. The results show that ARGDE in China exhibited a phased growth trend and was greatly affected by policies during 1997–2020. The interregional ARGD produced a hierarchical effect. However, provinces with a higher ARGDE did not necessarily exhibit faster growth, leading to a differential pattern of optimization that involved continuous optimization, phased optimization, and continuous deterioration. Over a long period, ARGDE exhibited a trend of significant upward leaps or jumps. Finally, the CCD between ARGDE and economic growth improved, with a clear trend of high-high agglomeration characteristics that shifted from the eastern and northeastern provinces to the central and western ones. This suggests that promoting "quality agriculture" and "green agriculture" can have practical significance in accelerating the development of ARGD. In the future, it is vital to promote ARGD's transformation while mitigating the risk of degrading the coordinated relationship between ARGD and economic growth. • China's Agricultural and Rural Green Development Efficiency (ARGDE) increased. • Provinces with higher ARGDE did not necessarily have a faster growth rate. • ARGDE exhibits a leapfrogging improvement in a period of 4–5 years. • The coupling coordination degree between ARGDE and economic growth improved. • The High-High cluster have shifted to the central and western regions. [ABSTRACT FROM AUTHOR]

The water-use rights trading system fully embodies a new concept of water resources management of the 'water saving priority' and market-oriented governance. The price mechanism is a core component of this system, and the benchmark price is its cornerstone. Accordingly, this paper analyzes the connotation and characteristics of the water-use rights benchmark price (WURBP). Based on the Marxist labor theory of value and land rent theory, it is proposed that the WURBP should be the economic embodiment of the water-use rights value. Considering the case of the Ningxia Yellow River irrigated area, a WURBP calculation model was established using the fuzzy comprehensive evaluation model to calculate the agricultural WURBP. The obstacle degree model was introduced to analyze the main factors affecting the WURBP. Results show that the WURBP for food crops in the Ningxia Yellow River irrigation area is 0.252 yuan/m3, and 0.652 yuan/m3 for cash crops. Water yield coefficient, runoff coefficient, per capita GDP, farmland irrigation utilization coefficient, and ecological water consumption have gradually become the primary obstacles affecting agricultural WURBP. Water administrative departments should adjust the WURBP according to the actual situation. This paper innovatively puts forward the concept of WURBP. These results have important practical significance for improving China's agricultural water-use rights trading price system. • Proposed the concept of water use rights benchmark price. • Using game theory combination weighting method to calculate weight. • Crops are divided into food and cash crops to calculate the WURBP. • The obstacle degree model is built to analyze the main factors affecting the WURBP. [ABSTRACT FROM AUTHOR]

This paper investigates the decoupling of carbon dioxide (CO 2 ) emissions from agricultural economic growth in 30 Chinese provinces from 1997 to 2014. First, CO 2 emissions from agricultural production activities, farming, and livestock husbandry are computed. Then, this paper explores the spatial and temporal heterogeneity of CO 2 emissions and their intensity in China’s agricultural sector. Finally, this paper compares decoupling of China’s agricultural CO 2 emissions from agricultural output value across different regions and years. The results indicate that fertilizer, in-season rice cultivation, and cattle generated the most CO 2 emissions in the categories of agricultural production activities, farming, and livestock husbandry, respectively. The results also show that East China covered more periods of the strong decoupling of CO 2 emissions from agricultural output value between 1997 and 2014. To decrease CO 2 emissions, this paper suggests imposing a higher value-added tax on fertilizer producers, while waiving value-added tax for organic fertilizer and substituting animal manure for conventional fertilizers where possible. [ABSTRACT FROM AUTHOR]

Agriculture affects and is affected by climate change. The development of climate-smart agriculture (CSA) is an effective way for agricultural production to cope with climate change. The rice-crayfish coculture system is a combination of the concept of climate-smart agriculture with the experience of traditional Chinese mixed crop-fish systems. This paper reviews the advantages and potential risks of rice-crayfish coculture with respect to climate, ecological environment and economic benefits, and summarises the successful management strategies and operation experiences during the implementation of this CSA practice in Qianjiang City. We also introduce various mixed crop-fish systems in China and suggest the potential of using wetland resources to develop mixed crop-fish systems and CSA. [ABSTRACT FROM AUTHOR]

There was presently a lack of multidimensional investigation on the impact of virtual water flow (VWF) on regional water use and scarcity. A framework for impact analysis of VWF in consideration of blue, green and grey water differentiation, taking the crop-water relationship estimation in 31 provinces of China as case study, was established in current paper. Results showed that, VWF, which mainly from northern to eastern plain and southeast, reduced agricultural water footprints by 8.3 (blue), 322.0 (green) and 52.5 (grey) G m3. National water stress index reduced from 1.20 (severe water stress) to 0.92 (high water stress), comparing crop consumption to production perspectives. VWF alleviated the resource-based water scarcity attributed to green water stress in south of the Yangtze River, and transformed the resource-based to systematic water scarcity in Xinjiang (XJ). Clarifying the influences of VWF on blue, green and grey water is the innovation of the analytical framework proposed in current paper. • Influences of virtual water flow (VWF) on blue, green and grey water footprint scarcity were quantified. • Green and grey VWFs and their effects on water resources were more impressive than blue water. • VWF alleviated water stress and changed water scarcity type in crop production of China. • Crop production improvement and optimization are proposed to increase the benefits of VWF. [ABSTRACT FROM AUTHOR]

Agriculture affects and is affected by climate change. The development of climatesmart agriculture (CSA) is an effective way for agricultural production to cope with climate change. The rice-crayfish coculture system is a combination of the concept of climate-smart agriculture with the experience of traditional Chinese mixed crop-fish systems. This paper reviews the advantages and potential risks of rice-crayfish coculture with respect to climate, ecological environment and economic benefits, and summarises the successful management strategies and operation experiences during the implementation of this CSA practice in Qianjiang City. We also introduce various mixed crop-fish systems in China and suggest the potential of using wetland resources to develop mixed crop-fish systems and CSA. [ABSTRACT FROM AUTHOR]

Within the context of climate change and population growth, the development of urban agriculture is of great environmental and economic significance in rapidly urbanizing China. Based on the primary survey data, this paper evaluated the carbon footprint (CF) and economic efficiency of urban agriculture in Beijing (China) using the life cycle assessment method (from cradle to consumption approach). Two cases were analyzed and compared considering their differences in on-farm cultivation and off-farm supply chains: a conventional small householder farm that sells its vegetables directly to consumers in a local market, and a large home-delivery agriculture (HDA) initiative that delivers its vegetables to the consumers' home directly. Both cases were equipped with greenhouses with plastic covering but no heating system. The CF of the production, transportation and distribution of 1 kg fresh vegetables was estimated at 0.318 kg CO 2 -eq kg−1 and 0.624–0.652 kg CO 2 -eq kg−1 for conventional and HDA initiative farm, respectively. However, the HDA initiative showed a better environmental performance than the conventional operation when taking economic efficiency into consideration. The CF per unit of profit of HDA initiative (0.093–0.097 kg CO 2 -eq per CNY) was lower than conventional farm (0.111 kg CO 2 -eq per CNY). The lower CF per unit of product weight of the conventional farm was largely attributed to the high yield and the lower CF per unit of profit of the HDA initiative was mainly due to the outstanding economic profitability through income optimization. The major hotspots of CF in both cases were greenhouse plastic films in the cultivation phase (from cradle to farm gate) and transportation in the supply chain (from farm gate to consumption). Simulation of a switch to biodiesel instead of gasoline and diesel in combination with the replacement of current fossil-fuel-dominated electricity by hydro-powered electricity resulted in 20.0–21.8% reduction in the total CF. By identifying the CF hotspots of two farm cases, particular inputs and activities can be targeted for adjustment in order to effectively reduce the CF of urban agriculture in Beijing. [ABSTRACT FROM AUTHOR]

To balance the supply and demand in China's beef market, beef consumption must be scientifically and effectively forecasted. Beef consumption is affected by many factors and is characterized by gray uncertainty. Therefore, gray theory can be used to forecast the beef consumption, In this paper, the structural defects and unreasonable parameter design of the traditional gray model are analyzed. Then, a new gray model termed, EGM(1,1,r), is built, and the modeling conditions and error checking methods of EGM(1,1,r) are studied. Then, EGM(1,1,r) is used to simulate and forecast China’s beef consumption. The results show that both the simulation and prediction precisions of the new model are better than those of other gray models. Finally, the new model is used to forecast China’s beef consumption for the period from 2019–2025. The findings will serve as an important reference for the Chinese government in formulating policies to ensure the balance between the supply and demand for Chinese beef. [ABSTRACT FROM AUTHOR]

Reducing agricultural carbon emissions is an essential lever for mitigating climate change and promoting high-quality agricultural development. Environmental regulation in the form of resource agglomeration, represented by the high-standard farmland construction policy, plays a vital role in the emission reduction process. Using the panel data of 31 provinces in China from 2001 to 2019 and taking the high-standard farmland construction policy as a quasi-natural experiment, this paper constructs a continuous differences-in-differences (DID) model to explore the impact and mechanism of environmental regulation in the form of resource agglomeration (RAER) on agricultural carbon emission reduction. The results show that RAER significantly reduces agricultural carbon emissions by an average of 3.9%. This conclusion still holds after robustness tests such as endogenous tests, eliminating policy interference, and sample reprocessing. This abatement utility is mainly realized through the technique effect of promoting green technology innovation and the composition effect of optimizing crop cultivation structure. Based on the resource attribute characteristics, the agricultural carbon emission reduction effects of RAER are, in descending order, capital and facility. Further study found heterogeneity in four aspects of the effect of RAER on agricultural carbon emission reduction: regional, planted crops, carbon emission sources, and carbon emission intensity. Therefore, decision-makers should deepen environmental regulation reform through resource agglomeration, implement adapting to local conditions for the high-standard farmland construction policy, and promote policy innovation and system optimization of agricultural carbon emission reduction. [ABSTRACT FROM AUTHOR]

As an important water-saving regulation, the construction of national water-saving city (NWSC) plays an important role in agricultural production, however, there is little research on its impact on agriculture. This paper uses super efficient Slacks-Based Measure (SBM) to measure agricultural total factor productivity (ATFP) in the regions along the Yellow River, and uses difference-in-difference (DID) model to explore the impact of NWSC on ATFP based on the theory of production factor flow. The results show that: First, the ATFP in the regions along the Yellow River demonstrated an initial increase followed by a decrease from 2000 to 2019, the ATFP in the regions along the Yellow River is low in the north and high in the south, and the ATFP of the main grain producing areas is generally higher. Second, the establishment of the NWSC can effectively improve the ATFP, the ATFP has increased by 6.57% compared with the control group, and the dynamic effect of the policy has shown an "N" pattern since its implementation. Particularly, in areas with relatively poor water resources, high agricultural factor intensification and major grain production areas, NWSC has a stronger impact on the ATFP. Third, NWSC has promoted the flow of labor production factors and improved ATFP through income effect, industrial synergy effect and technological innovation effect. The transfer of agricultural labor has also injected strong impetus into industrial development, and improved the return on industrial capital, which can promote agricultural capital more significantly, and further improved ATFP. Our findings provide empirical evidence for achieving high-quality agricultural development through the construction of NWSC. [ABSTRACT FROM AUTHOR]

The uncertainty of the global food supply has increased, and land abandonment has affected food security. Based on nationally representative farm households in 1995, 2002, 2008 and 2020, this paper systematically reveals the extent, drivers, and production loss of farmland abandonment in China, providing a scientific basis for the comprehensive management of land abandonment. The extent of farmland abandonment has been increasing since 1995; 1/5 of farmers have abandoned their farmland, and 1/10 of farmland has been abandoned. The number of counties recording farmland abandonment increased from 34 (11.15%) at the beginning of the study period to 224 (73.44%) by the end, and these counties were mainly distributed in the hilly and mountainous areas along the Yangtze River as well as in Southeast, Southwest, Northwest, and Northeast China. Farmland abandonment is the result of a combination of multiple factors, including basic farmland conditions and socio-economic and ecological factors, among which the low agricultural comparative income caused by agricultural labour shortages and poor-quality farmland conditions is the root cause. In 2020, for example, the ratio of farmland abandonment in major grain-producing and non-grain-producing regions was 7.38% and 16.94%, respectively, resulting in a total loss of 49.23 million tons of grain, which is 7.36% of the total national grain output. The production loss experienced by China could feed 123 million people based on the per capita annual food consumption estimates of 400 kg. Currently, farmland abandonment poses a threat to China's food security, and the government should gradually improve the quality of farmland through comprehensive land management, improve rural infrastructure and develop small-scale machinery suitable for hilly and mountainous areas. [Display omitted] [ABSTRACT FROM AUTHOR]

The cultural differences caused by rice cultivation between the north and south of China provide a unique perspective to study the local effect on corporate pro-environmental behavior. In this paper, we investigate the relationship between the geographical distribution of agricultural planting and corporate pro-environmental behavior. We manually collected the city-level rice planting data and used A-share listed companies' data from 2010 to 2019 in China and found that rice culture in the external environment in which the company is embedded has a positive association with the corporate reactive pro-environmental behavior, while rice culture in the internal values which CEO provided with is positively related to the corporate proactive pro-environmental behavior. Moreover, we find that environmental policy and migration are two moderators through which rice culture affects corporate pro-environmental behavior. This study not only sheds light on the agricultural drivers behind corporate pro-environmental behavior and extends the theoretical understanding of how cultural differences caused by geographical factors within countries influence corporate decisions but also helps firms, managers, and stakeholders effectively conduct self-reflection, management, and supervision on environmental issues through farming cultural dimensions. [ABSTRACT FROM AUTHOR]

This paper develops two-stage inverse data envelopment analysis models with undesirable outputs to formulate resource plans for 16 Chinese listed commercial banks whose outputs are increased and overall efficiency is kept unchanged in the short term. We use these models to meet three different output targets, namely, increasing both the desirable and undesirable outputs by the same percentage, increasing these outputs by different percentages, and increasing only the desirable outputs while keeping the undesirable outputs unchanged. We find that operation cost and interest expense are more flexible than labor in the adjustment process and that deposits have no obvious law of change. The findings of this work provide some suggestions for bank managers. [ABSTRACT FROM AUTHOR]

Based on the calculation of the inclusive financial development level of 22 provinces and 4 municipalities in China from 2004 to 2017, this paper uses the Kernel density estimation method to further analyze the evolution of the inclusive financial index. Based on the above analysis, we make empirical analysis of the impact of China's inclusive financial inclusion development index on farmers' entrepreneurship using static panel and dynamic panel estimation method. The empirical conclusions show that there are certain differences in inclusive financial inclusion development level in various provinces in China. Improving the inclusion development level of inclusive finance can better promote farmers' entrepreneurship. Urbanization level, economic openness and regional economic development level have a significant positive effect on farmers' entrepreneurship, while farmers' income and education level have a significant negative effect on farmers' entrepreneurship. It is possible to promote farmers' entrepreneurship by improving the inclusive development level of inclusive finance, combining urbanization, increasing government investment in productive fixed assets, increasing economic openness and improving regional economic development. [ABSTRACT FROM AUTHOR]

Following the emergence of H7N9 influenza in March 2013, local animal and public health authorities in China have been closing live bird markets as a measure to try to control the H7N9 influenza epidemic. The role of live bird market (LBM) closure on the spread of N7N9 influenza following the closure of LBMs during March to May 2013 (the first wave) and October 2013 to March 2014 (the second wave) is described in this paper. Different provinces implemented closure actions at different times, and intensive media reports on H7N9 in different provinces started at different times. Local broiler prices dropped dramatically in places with outbreaks and more live chickens were transported to other LBMs in neighboring areas without human cases from infected areas when live bird markets were being closed. There were six clusters of human infection from March to May 2013 and October 2013 to March 2014 and there may have been intensive poultry transportation among cluster areas. These findings provide evidence that the closure of LBMs in early waves of H7N9 influenza had resulted in expansion of H7N9 infection to uninfected areas. This suggests that provincial authorities in inland provinces should be alert to the risks of sudden changes in movement patterns for live birds after LBM closure or increased publicity about LBM closure. [ABSTRACT FROM AUTHOR]

Maintaining crop outputs to feed its large population with limited resources while simultaneously mitigating carbon emissions are great challenges for China. Improving the efficiency of resource use in crop production is important in reducing carbon emissions. This paper constructs a methodological framework combining emergy-based indicator accounting and a nonseparable undesirable output slack-based measurement (SBM) data envelopment analysis (DEA) model. This framework is used to explore the efficiency of inputs and outputs and the greenhouse gas (GHG) emissions reduction potential for crop production systems, using Zhejiang province, China, as a case study. It is found that an emergy synthesis and a nonseparable undesirable output SBM-DEA framework is compatible with the case study. Crop production in Zhejiang province has relied heavily on an increase in agrochemical inputs to maintain agricultural output. Energy and chemical fertilizer use are determined as the province’s major carbon emissions sources. Although carbon emissions per unit of monetary output has decreased sharply, the carbon emissions per unit emergy output has increased, demonstrating a high carbon intensity reality. The DEA highlighted the differences in crop production efficiency, resource factor redundancy and carbon mitigation potential in the different prefectures of the province. To conclude this research, policies to support low carbon agriculture development, including subsidizing low carbon agriculture technology development and expansion and the cancellation of subsidies to high carbon production factors, such as chemical fertilizer production and sales, are discussed to conclude the research. [ABSTRACT FROM AUTHOR]

Two bacteria, Streptomyces albireticuli MDJK11 and S. alboflavus MDJK44, which are potential plant growth-promoting rhizobacteria against pathogenic fungi were isolated from the rhizosphere soil of peony in Shandong, China. Their biological characteristics and complete genome sequences were reported in this study. The total genome size of MDJK11 was only 8.14 Mb with 6,550 protein-coding genes and a high GC content of 72.8 mol%. The MDJK44 genome comprises a 9.62 Mb chromosome with 72.1 mol% GC content, 7,285 protein-coding genes, and two plasmids. Some gene sequences in these two genomes were analyzed to be heterologously obtained by horizontal transfer. Gene or gene cluster candidates responding to secondary metabolites production, antimicrobial activities, and plant growth-promoting capacities were also analyzed in this paper. The genomic information and biological characteristics will facilitate the understanding and application of S. albireticuli and S. alboflavus species as biocontrol agents in future agriculture. [ABSTRACT FROM AUTHOR]

It is acknowledged that crude oil prices affect agricultural prices through both direct and indirect transmission schemes (i.e. exchange rate). In China, the matter of energy security may be immediately transmitted to the food security, imposing a pressure to China's macro-economy to a certain extent. Th is paper examines the long-run and short-run influence caused by the world crude oil prices and the RMB-dollar exchange rate on the five individual agricultural commodity prices (soybean, maize, wheat, colza oil, and japonica rice) in China. In this paper, the Granger causality approach is applied to test the long-run interrelationships with the weekly data from June 2002 to August 2013. In addition, the impulse-response analysis is utilized to study how the agricultural prices react to the sudden shocks in oil prices and exchange rate in the short term. The results reveal that the impulse response curves demonstrate that agricultural prices are not significantly affected by the abrupt changes in either oil prices or the exchange rate. Consistently, agricultural prices are neutral to the changes in oil prices in the long run while the exchange rate only Granger causes the prices of soybean. Ultimately, we present some sound reasons to explain the statistical results and propose some policy suggestions aimed at the China's food and energy security. [ABSTRACT FROM AUTHOR]

Granted that the traditional measure methods in calculating trade openness always trigger results of singleness and twisted outcomes, the aim of the paper is to recalculate the Chinese produce trade openness after 1978, using new measure methods consisting of the trade reliance and shares. After calculation and contrasting, obvious differences have been found between the new and traditional methods. The results of the traditional measure methods turn out to be severely underestimated, whereas the new ones are more specific to reveal the extent of the Chinese produce trade openness, along with demonstrating the function of the Chinese produce in world trade market. Based on the results, utilizing the panel data, the LA/AIDS model and price elasticity, the paper analyses the changes that rural food prices were influenced by the agricultural produce trade openness, and the changes of rural food expenditure and consumption. [ABSTRACT FROM AUTHOR]