Evolving patterns of agricultural production space in China:A network-based approach

The agricultural production space,as where and how much each agricultural product grows,plays a vital role in meeting the increasing and diverse food demands.Previous studies on agricultural production patterns have predominantly centered on individual or specific crop types,using methods such as remote sensing or statistical metrological analysis.In this study,we characterize the agricultural production space(APS)by bipartite network connecting agricultural products and provinces,to reveal the relatedness between diverse agricultural products and the spatiotemporal characteristic of provincial production capabilities in China.The results show that core products are cereal,pork,melon,and pome fruit;meanwhile the milk,grape,and fiber crop show an upward trend in centrality,which is in line with diet structure changes in China over the past decades.The little changes in community components and structures of agricultural products and provinces reveal that agricultural production patterns in China are relatively stable.Additionally,identified provincial communities closely resemble China's agricultural natural zones.Furthermore,the observed growth in production capabilities in North and Northeast China implies their potential focus areas for future agricultural production.Despite the superior production capa-bilities of southern provinces,recent years have witnessed a notable decline,warranting special attentions.The findings provide a comprehensive perspective for understanding the complex relationship of agricultural prod-ucts'relatedness,production capabilities and production patterns,which serve as a reference for the agricultural spatial optimization and agricultural sustainable development.

Unveiling the impact and mechanism of digital technology on agricultural economic resilience

Enhancing the economic resilience of agriculture is essential for promoting sustainable and high-quality agricultural development.The emergence of digital technology has created new opportunities in this field.However,existing research predominantly focuses on traditional agricultural factors and technologies.Therefore,the impact of digital technology on agricultural economic resilience within the broader context of the“production-operation-industry”system in agriculture has not been comprehensively explored.To bridge this gap,this study analyzes panel data from 30 Chinese provinces from 2011 to 2020.It employs the static Van Dorn’s law and a dynamic spatial panel model to examine how digital technology empowers agricultural resilience.The findings indicate a continuous strengthening of digital technology development in China,albeit with significant polarization and spatial imbalances.Moreover,the resilience of the agricultural economy undergoes notable fluctuations,initially narrowing and subsequently displaying an upward trend.Digital technology clearly plays a pivotal role in empowering resilience through agricultural scale operation,industrial transformation,and technological progress.Its impact,particularly on the promotion of resilience in the eastern region and non-grain-producing areas and on high-level agricultural economies,also shows regional and technological variations.

Agricultural intensity for sustainable regional development:A case study in peri-urban areas of Karawang Regency,Indonesia

Peri-urban areas are playing an increasingly crucial role in the agricultural development and intensification in Indonesia.Peri-urban agriculture is highly vulnerable to change compared with urban and rural agriculture,due to its location in transitional areas.Indicators of peri-urban agricultural intensity can help guide regional development.In this study,we assessed the sustainability of peri-urban areas based on agricultural intensity in Karawang Regency,Indonesia.We developed a village-based index to assess the region’s agricultural intensity by rescaling the village agriculture index(VAI)and combining the local sustainability index(LSI)with factor analysis.Since the unit of analysis is the village,we modified the LSI to the village sustainability index(VSI).In addition,we also developed a logical matrix analysis to determine the level of agricultural sustainability(LoAS)of each village.The combined results of the three indices(VAI,VSI,and LoAS)generated information about agricultural sustainability.The results indicated that peri-urban villages with high agricultural intensity tended to exhibit low levels of social welfare,economic development,and disaster risk.Moreover,high agricultural intensity did not necessarily ensure the prosperity of the people.Instead,there was the economic disparity among the villages in the study area.Encouraging diversity of agricultural intensity seems to be more critical than promoting agricultural intensity itself.Overall,this study highlights the distinctive characteristics and dynamic of peri-urban areas.New approaches,variables,and information regarding the combination of agricultural intensity and sustainability need to be developed as valuable tools for regional planning.

Spatio-Temporal Agricultural Drought Quantification in a Rainfed Agriculture, Athi-Galana-Sabaki River Basin

This study employs a quantitative approach to comprehensively investigate the full propagation process of agricultural drought, focusing on pigeon peas (the most grown crop in the AGS Basin) planting seasonal variations. The study modelled seasonal variabilities in the seasonal Standardized Precipitation Index (SPI) and Standardized Agricultural Drought Index (SADI). To necessitate comparison, SADI and SPI were Normalized (from −1 to 1) as they had different ranges and hence could not be compared. From the seasonal indices, the pigeon peas planting season (July to September) was singled out as the most important season to study agricultural droughts. The planting season analysis selected all years with severe conditions (2008, 2009, 2010, 2011, 2017 and 2022) for spatial analysis. Spatial analysis revealed that most areas in the upstream part of the Basin and Coastal region in the lowlands experienced severe to extreme agricultural droughts in highlighted drought years. The modelled agricultural drought results were validated using yield data from two stations in the Basin. The results show that the model performed well with a Pearson Coefficient of 0.87 and a Root Mean Square Error of 0.29. This proactive approach aims to ensure food security, especially in scenarios where the Basin anticipates significantly reduced precipitation affecting water available for agriculture, enabling policymakers, water resource managers and agricultural sector stakeholders to equitably allocate resources and mitigate the effects of droughts in the most affected areas to significantly reduce the socioeconomic drought that is amplified by agricultural drought in rainfed agriculture river basins.

Professional Cognitive Education Model for Agricultural Water Conservancy Engineering under the Background of New Agricultural Science

The construction of new agricultural science requires the use of modern scientific and technological means to transform and enhance current agricultural related majors.The agricultural water conservancy engineering major,with its inherent disciplinary advantages,plays an indispensable and important role in the construction of new agricultural science.In recent years,the lack of professional cognitive education has gradually become a significant problem in the training of talents in agricultural water conservancy engineering.Therefore,this paper deeply analyzes the problems and reasons faced by professional cognitive education,and proposes specific educational strategies for several key aspects such as enrollment promotion,freshman enrollment education,construction of teacher team,combination of scientific research and teaching,and strengthening professional cognition through competition activities.It aims to provide reference for improving the quality of professional cognitive education and exploring effective ways.

The Study of Mutual Benefits and Potential in China-Mongolia Agricultural Trade

This article aims to explore the mutual benefits and potential of agricultural trade between China and Mongolia,analyzing the current situation of agricultural resources,trade history,and policy environment of the two countries.The study finds that China-Mongolia agricultural trade shows significant economic complementarity.Trade activities not only promote economic growth in both countries but also deepen social and cultural exchanges.However,technical standards,political risks,and logistics costs remain major challenges facing trade cooperation.By strengthening policy coordination,investing in agricultural technology and infrastructure,and expanding the variety and markets of trade,the potential for cooperation in China-Mongolia agricultural trade can be further enhanced.These measures will help improve the efficiency and benefits of bilateral trade,achieving a win-win development.

Global Change in Agricultural Flash Drought over the 21st Century

Agricultural flash droughts are high-impact phenomena, characterized by rapid soil moisture dry down. The ensuing dry conditions can persist for weeks to months, with detrimental effects on natural ecosystems and crop cultivation. Increases in the frequency of these rare events in a future warmer climate would have significant societal impact. This study uses an ensemble of 10 Coupled Model Intercomparison Project(CMIP) models to investigate the projected change in agricultural flash drought during the 21st century. Comparison across geographical regions and climatic zones indicates that individual events are preceded by anomalously low relative humidity and precipitation, with long-term trends governed by changes in temperature, relative humidity, and soil moisture. As a result of these processes, the frequency of both upperlevel and root-zone flash drought is projected to more than double in the mid-and high latitudes over the 21st century, with hot spots developing in the temperate regions of Europe, and humid regions of South America, Europe, and southern Africa.

An agent-based model of agricultural land expansion in the mountain forest of Timor Island,Indonesia

The Mutis-Timau Forest Complex,located on Timor Island,Indonesia,is a mountainous tropical forest area that gradually decreases due to deforestation and forest degradation.Previous modelling studies based on patterns indicate that deforestation primarily occurs at lower elevations and near the boundaries of forests and settlements,often associated with shifting cultivation by local farmers.This study adopts a process-based modelling approach,specifically the agent-based model,to simulate land changes,particularly farmers'expansion of agricultural land around the Mutis mountain forest.The underlying concept of this agent-based approach is the interaction between the human and environmental systems.Farmers,representing the human system,interact with the land,which represents the environmental system,through land use decision-making mechanisms.The research was conducted in the Community Forest of the Timor Tengah Utara District,one of the sites within the Mutis-Timau Forest Complex with the highest deforestation rate.Land use change simulations were performed using agent-based modelling from 1999 to 2030,considering the socio-economic conditions of farmers,spatial preferences,land use decisions,and natural transitions.The results revealed that the agricultural area increased by 14%under the Business as Usual scenario and 5%under the Reducing Emission from Deforestation and Forest Degradation scenario,compared to the initial agricultural area of 245 hectares.The probability of farmers deciding to extend agricultural activities was positively associated with the number of livestock maintained by farmers and the size of the village area.Conversely,the likelihood of farmers opting for agricultural extensification decreased with an increase in the area of private land and the farmer's age.These findings are crucial for the managers of the Mutis-Timau Forest Complex and other relevant stakeholders,as they aid in arranging actions to combat deforestation,designing proper forest-related policies,and providing support for initiatives such as reducing emissions from deforestation and forest degradation programs or further incentive schemes.

How to enhance agricultural plastic waste management in China?Insights from public participation

Agricultural plastics play a pivotal role in agricultural production.However,due to expensive costs,agricultural plastic waste management(APWM)encounters a vast funding gap.As one of the crucial stakeholders,the public deserves to make appropriate efforts for APWM.Accordingly,identifying whether the public is willing to pay for APWM and clarifying the decisions’driving pathways to explore initiatives for promoting their payment intentions are essential to address the dilemma confronting APWM.To this end,by applying the extended theory of planned behavior(TPB),the study conducted an empirical analysis based on 1,288 residents from four provinces(autonomous regions)of northern China.Results illustrate that:1)respondents hold generally positive and relatively strong payment willingness towards APWM;2)respondents’attitude(AT),subjective norm(SN),and perceived behavioral control(PBC)are positively correlated with their payment intentions(INT);3)environmental cognition(EC)and environmental emotion(EE)positively moderate the relationships between AT and INT,and between SN and INT,posing significant indirect impacts on INT.The study’s implications extend to informing government policies,suggesting that multi-entity cooperation,specifically public payment for APWM,can enhance agricultural non-point waste management.

Mixed Integer Robust Programming Model for Multimodal Fresh Agricultural Products Terminal Distribution Network Design

The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network.To reduce costs and optimize the distribution network,we construct a mixed integer programmingmodel that comprehensively considers tominimize fixed,transportation,fresh-keeping,time,carbon emissions,and performance incentive costs.We analyzed the performance of traditional rider distribution and robot distribution modes in detail.In addition,the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network.In order to resist uncertain interference,we further extend the model to a robust counterpart form.The results of the simulation show that the instability of random parameters will lead to an increase in the cost.Compared with the traditional rider distribution mode,the robot distribution mode can save 12.7%on logistics costs,and the distribution efficiency is higher.Our research can provide support for the design of planning schemes for transportation enterprise managers.

Health risk assessment of trace metal(loid)s in agricultural soils based on Monte Carlo simulation coupled with positive matrix factorization model in Chongqing, southwest China

This study aimed to investigate the pollution characteristics, source apportionment, and health risks associated with trace metal(loid)s(TMs) in the major agricultural producing areas in Chongqing, China. We analyzed the source apportionment and assessed the health risk of TMs in agricultural soils by using positive matrix factorization(PMF) model and health risk assessment(HRA) model based on Monte Carlo simulation. Meanwhile, we combined PMF and HRA models to explore the health risks of TMs in agricultural soils by different pollution sources to determine the priority control factors. Results showed that the average contents of cadmium(Cd), arsenic (As), lead(Pb), chromium(Cr), copper(Cu), nickel(Ni), and zinc(Zn) in the soil were found to be 0.26, 5.93, 27.14, 61.32, 23.81, 32.45, and 78.65 mg/kg, respectively. Spatial analysis and source apportionment analysis revealed that urban and industrial sources, agricultural sources, and natural sources accounted for 33.0%, 27.7%, and 39.3% of TM accumulation in the soil, respectively. In the HRA model based on Monte Carlo simulation, noncarcinogenic risks were deemed negligible(hazard index <1), the carcinogenic risks were at acceptable level(10^(-6)<total carcinogenic risk ≤ 10^(-4)), with higher risks observed for children compared to adults. The relationship between TMs, their sources, and health risks indicated that urban and industrial sources were primarily associated with As, contributing to 75.1% of carcinogenic risks and 55.7% of non-carcinogenic risks, making them the primary control factors. Meanwhile, agricultural sources were primarily linked to Cd and Pb, contributing to 13.1% of carcinogenic risks and 21.8% of non-carcinogenic risks, designating them as secondary control factors.

Continual Reinforcement Learning for Intelligent Agricultural Management under Climate Changes

Climate change poses significant challenges to agricultural management,particularly in adapting to extreme weather conditions that impact agricultural production.Existing works with traditional Reinforcement Learning(RL)methods often falter under such extreme conditions.To address this challenge,our study introduces a novel approach by integrating Continual Learning(CL)with RL to form Continual Reinforcement Learning(CRL),enhancing the adaptability of agricultural management strategies.Leveraging the Gym-DSSAT simulation environment,our research enables RL agents to learn optimal fertilization strategies based on variable weather conditions.By incorporating CL algorithms,such as Elastic Weight Consolidation(EWC),with established RL techniques like Deep Q-Networks(DQN),we developed a framework in which agents can learn and retain knowledge across diverse weather scenarios.The CRL approach was tested under climate variability to assess the robustness and adaptability of the induced policies,particularly under extreme weather events like severe droughts.Our results showed that continually learned policies exhibited superior adaptability and performance compared to optimal policies learned through the conventional RL methods,especially in challenging conditions of reduced rainfall and increased temperatures.This pioneering work,which combines CL with RL to generate adaptive policies for agricultural management,is expected to make significant advancements in precision agriculture in the era of climate change.

Agricultural drought severity in NE Italy: Variability, bias, and future scenarios

This study investigated the variability of agricultural drought severity,as depicted by vegetation indices,and the bias in identifying drought events when considering a stationary vs nonstationary climate reference.The work leveraged gridded climate data(NCEP CFSv2,CHIRPS 1981–2022),soil properties(OpenLandMap),satellite imagery(Sentinel2/Landsat,2000–2022),and future climate projections(NEX-GDDP,2050)together with local knowledge of selected farms,to augment drought monitoring techniques and identify potential issues for agriculture.For the study domain,significant differences were observed when comparing drought characteristics using stationary and nonstationary drought indexes,with biases being not ubiquitous in either space or time of year.When developing sustainable drought mitigation and adaptation strategies,decision-makers should carefully address this uncertainty to avoid a possible underestimation of drought magnitude.Results showed a drought increase(∼50%)by the mid and late twenty-first century.Projection of future climate highlighted an even more significant impact(∼80%)with a wide variability of risk across the domain.As drought impact was also related to soil organic carbon(SOC),our results suggest that improving SOC content could be a sustainable strategy for enhancing soil drought resilience,especially in areas commonly characterized by low concentrations of organic carbon and nutrients.The analysis highlighted that drought impacts were also modulated by investment in irrigation infrastructure and irrigation efficiency.Researchers and land managers could apply the proposed analysis design to address historical,current and future indicators of vegetation conditions within irrigated regions.By providing spatio-temporal information on the patterns of drought impacts and their bias,this study supports identifying priority regions for targeted drought risk reduction and adaptation options,including water resources and soil management sustainability criteria,to move towards more resilient agricultural systems.

How to promote cooperative innovation in environmentally friendly technology:a case of agricultural biotechnology in China

This study explored the factors influencing cooperative innovation in environmentally friendly agricultural biotechnology in China.First,we constructed an evolutionary game model comprising the factors of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies.Using MATLAB simulation,we assigned different values to the aforementioned variables to explore the evolutionary trend of innovators’willingness to cooperate.Results showed that when the values of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies exceeded the threshold,innovators’willingness to cooperate was significantly enhanced.Furthermore,the proportion of innovators who cooperated with others gradually increased to 100%;otherwise,it gradually decreased to 0%.Comparing the simulation curve with the real evolution curve of cooperative innovation in agricultural biotechnology in China,we found that the gradual decline in the willingness to cooperate could be due to insufficient subsidies for cooperative innovation,low income from cooperative innovation,weak profitability of innovators,and weak market constraints.

Spatio-temporal variation and relationship between agricultural efficiency and irrigation intensity in a semi-arid region of India

A surging population in Karnataka State,a semi-arid region in India,poses a threat to both food security and livelihood sustainability,necessitating a concentrated effort to bolster agricultural efficiency and achieve United Naton’s Sustainable Development Goal 2(zero hunger).Therefore,in order to address the pressing issue of food scarcity in Karnataka,this study meticulously examined the spatio-temporal variation of agricultural efficiency and irrigation intensity in Karnataka,uncovering its significant dependence of agricultural efficiency on irrigation intensity.Specifically,this study used a one-way analysis of variance(ANOVA)to ascertain significant differences in the means of agricultural efficiency and irrigation intensity during 2004-2005 and 2018-2019.This study showed that the maximum improvement in agricultural efficiency index was recorded in Belgaum(40.24),Gulbarga(24.77),and Yadgir districts(22.92)between 2004-2005 and 2018-2019,which indicated the progressing trend and better scope for agriculture extension.On the contrary,some districts expressed threat(a decline of above 20.00 of agricultural efficiency index)and needed special care for the improvement of agricultural efficiency in four northern districts(Bagalkot,Bidar,Raichur,and Bijapur),three southern districts(Chitradurga,Chikballapur and Hassan),and two southern districts(Koppal and Gadag)in Karnataka.During 2004-2005,irrigation intensity varied from 3.19%to 56.39%,with the lowest irrigation intensity in Kodagu District and the highest irrigation intensity in Shimoga District.During 2018-2019,irrigation intensity changed from 0.77%to 72.77%,with the lowest irrigation intensity in Kodagu District and the highest in Dakshin Kannad District.Moreover,the research scrutinized the complex relationship between agricultural efficiency and irrigation intensity,with the correlation coefficient increased from 0.162 during 2004-2005 to 0.255 during 2018-2019.It implies that in both periods,a low positive correlation existed between these two variables.Over time,several factors(high-yield seeds and chemical fertilizers)other than irrigation intensity gradually became essential for agricultural efficiency.This research offers a wealth of valuable insights for regional planners and policy-makers contending with comparable challenges in various regions of India and other developing countries.

Thoughts on Pairing Assistance to Tibet for Promoting Agricultural High-quality Development in Southern Tibet from the Perspective of Agricultural Power

In the new era,there is an urgent need to further promote pairing assistance to Tibet,promote the simultaneous construction of a strong agriculture in Tibet and the China's Mainland,and compose a Chinese-style modernization.Southern Tibet,located in the southeastern part of the Tibet Autonomous Region,includes Shannan City and Nyingchi City,is a region assisted by four provincial partners including Hubei Province.This paper introduces the agricultural environment in southern Tibet,studies its agricultural characteristics,and analyzes the main issues of its pairing assistance.Taking forging the strong consciousness of the Chinese national community as the main line,the paper explores strategies for promoting agricultural high-quality development in southern Tibet through pairing assistance to Tibet from the perspective of agricultural power,and proposes some strategies,such as inheriting agricultural cultural heritage,promoting the upgrading of modern seed industry,enhancing the characteristic advantages of highland barley(naked barley)and animal husbandry industries,and developing edible fungi and cold water fish industries.

Construction of BDS Spatiotemporal Information Agricultural Product Digital Credit System

Spatiotemporal information,positioning and navigation services have become important elements of new type infrastructure.The rapid development of global digital trade provides a large-scale application scenario for the use of Beidou Navigation Satellite System(BDS)spatiotemporal information to support the certification of origin of agricultural products.The BDS spatiotemporal information agricultural product digital credit system uses such modules as BDS,spatiotemporal information collection,spatiotemporal coding,and spatiotemporal blockchain.It incorporates multi-level joint supervision mechanisms such as government,associations,and users.Starting from the initial production link of agricultural products,it realizes the correspondence and locking of online and offline products,effectively improves the integrity and credibility of information in the production process,finished product quality and circulation process of products,effectively manages the green production and anti-channel conflicts of producers,and provides credible information for consumers,thus realizing the digital credit certification of products.The successful practice of characteristic agricultural products in Yunnan Province has verified the application ability of the BDS spatiotemporal information agricultural product digital credit system.This system has played a significant role in promoting the online and offline locking,credible information,effective supervision and high quality and high price of characteristic agricultural products from the field.The BDS provides services for global digital trade and contributes to the further enhancement of the global application scale of GNSS.

Optimization of Agricultural Industrial Structure in Changping District of Beijing Based on Grey Relational Analysis

In the economic development of Beijing,although the share of the total amount of agricultural industry in the overall economy is relatively low,it has an important impact on the daily life of residents,social stability and the development of other industries.Changping District,as an important agricultural production base of Beijing,its agricultural development has an indispensable strategic significance for the stability and growth of the entire regional economy.Therefore,it is very important to study the structure of agricultural industry in Changping District.Based on the detailed analysis of the agricultural industrial structure of Changping District,this paper uses the grey relation theory to analyze the different industries in the agricultural industrial structure of Changping District,including planting,forestry,animal husbandry,fishery and agricultural,forestry,service industries,in order to reveal the impact of these industries on the agricultural industrial structure of Changping District.Through this study,it comes up with specific and feasible suggestions for the optimization of agricultural industrial structure in Changping District,and provides valuable reference for the agricultural development of other areas in Beijing.

Analysis of Regional Difference of Agricultural Land Productivity in Heilongjiang Province

The sustenance of humanity is contingent upon the production of food.The foundation of this production is agriculture,which in turn is dependent upon the cultivation of the land.As a fundamental element of agricultural advancement,the rational development and utilization of land play a pivotal role in the process of rural revitalization.Agricultural land productivity serves as a principal indicator of the efficacy of land utilization and the extent of agricultural advancement.Nevertheless,there is a paucity of research examining the productivity of agricultural land,particularly a lack of specialized research on large agricultural provinces.In light of the aforementioned considerations,this paper presents a comprehensive examination of agricultural land productivity and its regional variations in Heilongjiang Province in 2022,with the aid of pertinent statistical data.The findings of the analysis indicate that among the prefecture-level cities,Daqing and Suihua exhibit the highest levels of agricultural land productivity.Additionally,Zhaodong City,Zhaozhou,Qinggang,Wangkui,and Lanxi counties exhibit high levels of agricultural land productivity within their respective prefecture-level cities.There are notable disparities in agricultural land productivity across various regions,including Yichun,Heihe,Harbin,Daqing,Hegang,and Suihua.In contrast,other regions demonstrate a more balanced spatial distribution.In order to facilitate the prosperous development of the agricultural industry in Heilongjiang Province,it is essential to optimize the spatial planning of the land,to investigate the potential for agricultural development in each region,to establish effective collaboration between resources and industries,and to create a development synergy that will collectively advance rural revitalization.

Promoting High-quality Development of Grain and Oil in Ethnic Areas of the Yangtze River Economic Belt from the Perspective of Agricultural Power

Accelerating the construction of agricultural power,further promoting the high-quality development of the Yangtze River Economic Belt,and better supporting and serving Chinese-style modernization are the key issues at present.This paper first introduces the Yangtze River Economic Belt and its ethnic areas,and studies the characteristics of the grain and oil industry in the ethnic autonomous areas of the economic belt,as well as the current situation of various types of intellectual property resources,such as industrial cultural heritage,scientific and tech-nological innovation,and brand marking intellectual property.Besides,it analyzes the main problems in the high-quality development of grain and oil in the Yangtze River Economic Belt ethnic areas.Finally,it comes up with recommendations,including protecting the intellectual prop-erty rights of cultural heritage in the field of grain and oil,leading the inheritance and development of excellent traditional Chinese culture,use scientific and technological innovation intellectual property rights to promote the innovation-driven development strategy of the grain and oil in-dustry,and providing counterpart assistance to ethnic autonomous areas in the Yangtze River Economic Belt to further promote the high-quality development of the Yangtze River Economic Belt.