Development Of Low-carbon Agriculture Research Articles

Response Mechanism and Evolution Trend of Carbon Effect in the Farmland Ecosystem of the Middle and Lower Reaches of the Yangtze River

The farmland system in the global terrestrial ecosystem has dual attributes as both a carbon source and a carbon sink, playing a crucial role in controlling carbon emissions and mitigating global warming. Using carbon source and sink accounting of farmland ecosystems, we applied methods such as standard deviation ellipse, Tapio decoupling theory, and Markov chain to analyze the spatiotemporal changes, response mechanisms, and evolutionary trends of regional carbon effects. The results indicated that from 2011 to 2021, the farmland ecosystem in the middle and lower reaches of the Yangtze River consistently acted as a carbon sink. However, the net carbon sink showed slight fluctuations and significant spatial differences. The migration range of the net carbon sink center in the farmland ecosystem of the middle and lower reaches of the Yangtze River was relatively small, ranging from 115.52 to 115.77° E and 30.14 to 30.27° N. The decomposition of the Tapio decoupling index between the net carbon sink of the farmland ecosystem and agricultural output value showed the order of effects on their coupling relationship as follows: agricultural mechanization level > agricultural mechanization efficiency > agricultural output value > planting scale. The probability of maintaining the original state of net carbon sink in various cities in the middle and lower reaches of the Yangtze River (over 77%) was much higher than the probability of transfer, making it difficult to achieve a leapfrog growth in net carbon sink. The net carbon sink at the city scale exhibits the Matthew effect and spatial spillover effect. The above research results clarify the spatiotemporal changes in carbon effects in agricultural production at multiple levels, including city, province, and region. They also provide a theoretical basis for formulating differentiated regional emission reduction and sink enhancement strategies in the middle and lower reaches of the Yangtze River, promoting the rapid development of low-carbon agriculture in China.

Development of Ecological Low-Carbon Agriculture with Chinese Characteristics in the New Era: Features, Practical Issues, and Pathways

Agriculture is not only the source of carbon emissions, but also an important carbon sink. The development of low-carbon agriculture in China is closely related to achieving the national strategic goal of “dual carbon.” Reducing carbon emissions in China’s agricultural sector and accelerating the development of ecological low-carbon agriculture (ELA) are extremely important and urgent, both from the perspective of the long-term common welfare for mankind and from the perspective of maintaining the sustainable development of agriculture itself. However, ELA is still an emerging concept in China, and its connotation and characteristics are not yet clear. There is a lack of effective paths for orderly and scientific promotion of the development of ELA in China. Based on this, this paper focuses on the emerging concept of ELA and examines ELA with Chinese characteristics from the dimensions of connotation, features, practical issues, and pathways, aiming to provide guidance for the sustainable development of ELA in China. The research results indicate that there are regional development imbalances, low willingness of farmers to participate, insufficient technological reserves, and difficulties in realizing the value of ecological products in China’s ELA. It is necessary to improve the modern agricultural production and operation system, tap into the potential of agricultural emission reduction and carbon sequestration, build a technical system to support the development of ELA, and establish a sound mechanism for realizing the value of ecological products. By continuously improving the regional organizational capacity and performance of ELA, accelerating the advancement of ELA technology and demonstrating its regional promotion, and by establishing and continuously improving the support system for ELA, one can promote the sustainable development of ELA in China. In addition, the research findings of this paper can also provide reference for the ecological low-carbon development of the global agricultural sector, supporting the contribution of the agricultural sector to achieving high-quality global sustainable development goals.

Analysis of the impact of resource misallocation and socialized services on low-carbon agricultural production with DML based on random forest

The substantial increase in agricultural carbon emissions (ACEs) contributes significantly to global warming, and agricultural resource misallocation (ARM) plays a major role in the rise of ACEs. Therefore, the aim of developing modern agriculture is to reduce ARM and promote low-carbon agriculture. To achieve this, the double machine learning model (DML) and moderating effect model are adopted in the present study to explore the correlations between agricultural socialized services (ASS), ARM, and ACEs. Also, the ARM index is calculated using the panel data collected from 31 provinces during the 2004–2020 period in China. The research results are as follows. Firstly, ARM has a significant positive impact on ACEs at the 1% significance level. Secondly, ASS exerts significant negative regulatory effects on ARM and ACEs at the 1% significance level. Lastly, the goodness of fit (R2) reaches 95% and 40% for DML and the fixed effect model (FEM), respectively. Relatively, DML performs better in the goodness of fit according to this study. Furthermore, it is found out in this study that land misallocation, labor misallocation and capital misallocation increase ACEs and impede the development of low-carbon agriculture. Also, as a regulatory variable, ASS mitigates the ARM-induced increase of ACEs. Therefore, these findings provide guidance on the development of low-carbon agriculture for ASS.

Exploring the Impact of Digital Inclusive Finance on Agricultural Carbon Emissions: Evidence from the Mediation Effect of Capital Deepening

Carbon emissions from agriculture should not be underestimated. With the aim for carbon peaking and carbon neutralization and the help of digital inclusive finance, the effective reduction in carbon emissions in agriculture and animal husbandry production is crucial to achieving China’s carbon emission reduction goals. We used the balanced panel data of 31 provinces in China from 2011 to 2021 to study this issue. We empirically tested the impact, mechanism, and heterogeneity of digital inclusive finance on agricultural carbon emissions based on the systematic measurement of agricultural carbon emissions. The results revealed that (1) the development of digital inclusive finance has a significant inhibitory effect on agricultural carbon emissions, and it is an important path to reduce agricultural carbon emissions. (2) Through the intermediary effects’ analysis, it was found that capital deepening is an important transmission mechanism for the promotion of agricultural carbon emission reduction through digital inclusive finance. (3) Further analysis using the quantile regression model reveals that the impact of digital inclusive finance on agricultural carbon emissions is significantly negative at different quantiles. (4) Through the spatial Durbin model, digital inclusive finance has a space carbon enhancement effect. Finally, we put forward suggestions to promote the development of low-carbon agriculture by paying attention to the technical effect of digital inclusive finance, strengthening the connection and cooperation between various regions and promoting the carbon emission reduction role of capital deepening.

Toward Low-Carbon Rice Production in China: Historical Changes, Driving Factors, and Mitigation Potential.

Under the "Double Carbon" target, the development of low-carbon agriculture requires a holistic comprehension of spatially and temporally explicit greenhouse gas (GHG) emissions associated with agricultural products. However, the lack of systematic evaluation at a fine scale presents considerable challenges in guiding localized strategies for mitigating GHG emissions from crop production. Here, we analyzed the county-level carbon footprint (CF) of China's rice production from 2007 to 2018 by coupling life cycle assessment and the DNDC model. Results revealed a significant annual increase of 74.3 kg CO2-eq ha-1 in the average farm-based CF (FCF), while it remained stable for the product-based CF (PCF). The CF exhibited considerable variations among counties, ranging from 2324 to 20,768 kg CO2-eq ha-1 for FCF and from 0.36 to 3.81 kg CO2-eq kg-1 for PCF in 2018. The spatiotemporal heterogeneities of FCF were predominantly influenced by field CH4 emissions, followed by diesel consumption and soil organic carbon sequestration. Scenario analysis elucidates that the national total GHG emissions from rice production could be significantly reduced through optimized irrigation (48.5%) and straw-based biogas production (18.0%). Moreover, integrating additional strategies (e.g., advanced crop management, optimized fertilization, and biodiesel application) could amplify the overall emission reduction to 76.7% while concurrently boosting the rice yield by 11.8%. Our county-level research provides valuable insights for the formulation of targeted GHG mitigation policies in rice production, thereby advancing the pursuit of carbon-neutral agricultural practices.

Exploration and countermeasures for the development of low-carbon agriculture: a study from Chongming District, Shanghai

To achieve the goals of carbon peaking and carbon neutrality, China is actively promoting carbon reduction in many areas. Agriculture is one of the main sources of greenhouse gas emissions, and promoting the development of low-carbon agriculture is a critical way to achieve carbon reduction targets. Taking Chongming District in Shanghai as an example, this study summarizes the experience of low-carbon agricultural development in Chongming and analyzes the problems and challenges faced during its development. Finally, based on the system dynamics method, the causal relationship of carbon emission in Chongming’s agricultural development is constructed, and feasible loop optimization suggestions are put forward.

Exploring low-carbon mulching strategies for maize and wheat on-farm: Spatial responses, factors and mitigation potential

Mulching strategies - including plastic film mulching (FM) and straw mulching (SM) - can enhance crop yields while affecting multiple greenhouse gas (GHG) fluxes. However, most of currently published site-based studies only focus on a certain gas, resulting in an inability to spatially integrated understanding of changes in agricultural global warming potential (GWP) and greenhouse gas intensity (GHGI) caused by mulching across China. Thus, we developed an optimal model considering crop type, meteorology, soil and management variables by four machine learning methods, namely support vector machine, multilayer perceptron, random forest, and gradient boosting machine (GBM). Then we mapped the relative changes in yield and GHG fluxes caused by mulching strategies. The GBM model had the best simulation capability for yield and GHGs in China. Our result showed that FM increased yield in maize (25 %) and wheat (19 %), while SM respectively increased by 14 % and 11 %. Among the relative changes due to mulching strategies, yield and N2O emissions were mainly influenced by soil fertility and soil properties, CH4 uptakes and CO2 emissions were more affected by environmental factors. GWP in maize and wheat average increased by 40 % under FM, while SM decreased GWP by 14 % and 2 %, respectively. Besides, FM average increased GHGI in maize and wheat by 17 % and 9 %, and SM decreased GHGI by 22 % and 12 %, respectively. Spatially, FM reduced maize GWP on 19 % of cropland, while SM reduced maize and wheat GWP on 71 % and 64 % of cropland, respectively. Soil pH was significantly correlated with ΔGHGI in maize and wheat. Our analysis not only estimated for the first time the spatial effects of mulching strategies across China, but also systematically analyzes the agricultural carbon emission mitigation potential of mulching strategies, which promote the development of low-carbon agriculture based on locally appropriate mulching strategies.

The Impact of Farmland Management Scale on Carbon Emissions

In rural China, the conversion between fine-grained farmland and large-scale farmland is a widespread phenomenon, changes in the size of farmland can have an impact on agricultural carbon emissions. Based on the agricultural panel data of Gansu Province for 2000–2020, taking the scale of agricultural land management as the breakthrough point and the consumption intensity of agricultural materials as the intermediary factor, this paper discusses the driving mechanism of agricultural carbon emissions by the scale of agricultural land management. The results including: (1) From the perspective of the intermediary effect, large-scale farmers pay more attention to input efficiency of chemicals such as fertilizers than small-scale farmers, which can effectively promote the development of low-carbon agriculture. (2) A “U-shaped” relationship existed between agricultural land management scale and agricultural carbon emissions. The agricultural carbon emissions were the lowest when agricultural land management scale in Gansu was 0.608 hm2/person. (3) The carbon emission intensity reached its peak when the scale of farmland management in the Hexi region was 0.143 hm2/person. The optimal scale of farmland management in the Longdong and Longnan regions was 0.143 and 0.348 hm2/person, respectively, Longzhong and Gannan regions was all showed complete intermediary effects.

Recovery Nutrient from Agricultural Waste as An Effort To Develop Low-Carbon Agriculture In Thekelan Hamlet

Thekelan Hamlet is located on the slopes of Mount Merbabu which is included in the Mount Merbabu National Park area. The majority of people earn from agriculture and animal husbandry because there is still a lot of land for farming. In the process of agricultural activities, residual materials or so-called agricultural waste are produced in the form of solids or liquids. In Thekelan Hamlet there is no agricultural wastewater treatment, so there is a need for agricultural wastewater management. One of them is by reusing nutrients so that they are still useful and do not pollute the environment. In agricultural wastewater, many types of nutrients can be reused, such as nitrogen and phosphate. So that the recovered nutrient content can be reused and processed into fertilizer. This will support the development of low-carbon agriculture in Thekelan Hamlet. The activity of reusing nutrients from agricultural liquid waste is also supported by the existence of a building to catch and process nutrients for agricultural liquid waste. The agricultural liquid waste runoff will be made into waterways according to the elevation of the land to eventually be accommodated in a storage building and processed into fertilizer with a certain concentration.

Agricultural Cultivation Structure in Arid Areas Based on Water–Carbon Nexus—Taking the Middle Reaches of the Heihe River as an Example

China faces challenges of food security and sustainable agricultural production. However, current studies rarely address the spatial distribution patterns of water consumption and carbon emissions. We studied the irrigation water use efficiency and carbon emission differences of crops in arid areas and their spatial distribution using wheat and maize, two major food crops in the middle reaches of the Heihe River, as examples. Furthermore, we have optimized low-carbon cropping of crops under the multiple objectives of water conservation and economic development. The results show that: (1) The carbon emissions per unit of water consumption for maize are 0.03 × 10−6 t mm−1 and 0.49 × 10−6 t mm−1 for wheat. Irrigation water consumption per unit yield is 515.6 mm t−1 for maize and 426.7 mm t−1 for wheat. (2) The spatial distribution patterns of irrigation water consumption were opposites for maize and wheat. The former has lower irrigation water consumption in the planting area upstream of the Heihe River and higher in the lower reaches. In contrast, the pattern of wheat irrigation is the opposite. (3) After optimizing the cropping mix for both crops, the area planted with wheat should be reduced to 59% of the current size, while maize should be expanded to 104%. The results of the research hold immense importance in guiding the future grain crop planting patterns for water-saving agriculture and low-carbon agriculture development in arid zones worldwide, aligning with the United Nations’ Sustainable Development Goals.

Reducing the carbon emission from agricultural production in China: do land transfer and urbanization matter?

Urbanization and land transfer have triggered a profound reform of the Chinese agricultural sector since reform and opening, leading to a continuous rise in agricultural carbon emissions. However, the impact of urbanization and land transfer on agricultural carbon emissions is not widely understood. Therefore, based on the panel data covering 30 provinces (cities) in China from 2005 to 2019, we adopted a panel autoregressive distributed lag model and a vector autoregressive model to empirically explore the causal relationship between land transfer, urbanization, and agricultural carbon emissions. The main conclusions are as follows: (1) Land transfer can significantly reduce carbon emissions from agricultural production in the long run, while urbanization has a positive effect on agricultural carbon emissions. (2) In the short run, land transfer has a significant positive impact on agricultural carbon emissions, and urbanization also has a positive impact on the carbon emissions of agricultural production, but in insignificant ways. (3) There is two-way causality between land transfer and agricultural carbon emission, and between urbanization and land transfer is the same, but urbanization is the one-way Granger cause of agricultural carbon emissions. Finally, some suggestions are provided for low-carbon agriculture development: the government should encourage the transfer of land management rights and guide high-quality resources to gather in green agriculture.

Development of low carbon agriculture and animal husbandry in Thekelan Hamlet, Indonesia using the participatory rural appraisal approach method

Thekelan Hamlet has residents with the majority working in the agricultural and livestock sector. Village development through agricultural education and low-carbon animal husbandry is a strategy for utilizing natural potential. Biomasses of livestock manure can be used as liquid organic fertilizer which will increase the selling price of agricultural products and be beneficial to the environment. The potential for the use of livestock manure has not been fully exploited because of the low education, knowledge, and capital that residents have. The Participatory Rural Appraisal (PRA) method is used to develop agriculture and low-carbon farms in Thekelan Hamlet. There are three aspects; biogas as the treatment of livestock gas waste, the use of liquid organic fertilizer from livestock manure, and the use of organic pesticides. The results of this study indicate that the community in Thekelan District can apply agriculture and low-carbon farms. The technology used by utilizing livestock manure can reduce household gas emissions in the production process, increase production yields, and increase the level of the community economy. Therefore, the community agrees to contribute and join the development of this program because this can improve the welfare of farmers and benefit the environment.

How do local government information sources affect the purchase willingness of low-carbon agricultural products? The example of regional brand agricultural products.

In order to achieve the carbon peaking and carbon neutrality goals, the agricultural sector has been given high priority to reduce carbon emissions. Since consumption is the ultimate goal of production, the consumption of low-carbon agricultural products is of great significance to promote the reduction of agricultural carbon emissions. Regional brand agricultural product is an important tool to promote the development of regional economy to "green, low-carbon, branded and high-quality", and has the technical and institutional conditions to develop into low-carbon agricultural product, so this study takes regional brand agricultural products as the representative of low-carbon agricultural products. As a information source to guide the public to consume in the green and low-carbon way, local government can effectively develop the market for low-carbon agricultural products and drive the development of low-carbon agriculture from the demand side. Based on structural equation model with bootstrap method, this paper focuses on the mechanism of the influence of local government information source characteristics (credibility, professionalism, and attractiveness) on consumers' willingness to purchase low-carbon agricultural products, and explores the mediating role of perceived benefits and perceived risks. The following findings are established: first, the credibility and professionalism of local governments play a positive role in influencing the purchase willingness of low-carbon agricultural products through perceived benefits, with credibility having the greatest degree of influence. Second, the attractiveness of local governments positively influences consumers' willingness to purchase low-carbon agricultural products through perceived risk. Third, perceived benefits play a fully mediating role between credibility and purchase intention, play a partially mediating role between professionalism and purchase willingness, perceived risks play a partially mediating role between attractiveness and purchase willingness. This study provides new ideas for the construction of low-carbon agricultural products and low-carbon development in the agricultural sector from the perspective of local government information sources.

Does rural energy poverty alleviation really reduce agricultural carbon emissions? The case of China

Energy poverty has led to far-reaching global environmental issues as it can exacerbate carbon emissions, particularly in the rural areas. Alleviating rural energy poverty might be a potentially effective way to mitigate this problem. Accordingly, this paper proposes a novel and comprehensive measurement of Rural Energy Poverty Alleviation (REPA) of 30 provinces in China from 2000 to 2017. The overall REPA index has increased from 2000 to 2017, despite of obvious regional differences. We empirically verify the Environmental Kuznets Curve (EKC) between REPA and agricultural carbon emissions (ACE) through fixed effects model. The results show that REPA exerts an inverted U-shaped effect on ACE, which means that REPA will reduce ACE after a threshold. Notably, the sub-indicators of REPA, Rural Energy Service Availability (RESA) and Rural Energy Consumption Cleanliness (RECC), can jointly affect ACE through the incremental effect and the reduction effect. Moreover, through the panel threshold model, it can be found that REPA may play a greater role in increasing ACE in provinces with abundant agricultural endowments. Finally, several policy implications are highlighted for policymakers to better achieve the dual goals of alleviating rural energy poverty and reducing agricultural carbon emissions. This study may provide a better understanding of the nexus between REPA and ACE for the low-carbon agriculture development.

Influencing Factors and Group Differences of Urban Consumers' Willingness to Pay for Low-Carbon Agricultural Products in China.

Developing low-carbon agriculture has become a development goal for low-carbon economies in various countries, and consumers' awareness and willingness to pay (WTP) for low-carbon agricultural products is an important link in achieving the sustainable development of low-carbon agriculture. The theory of planned behavior is a widely used framework to explain consumers' food choices. Considering the intrinsic norms of consumers, their perceptions of low-carbon agricultural products, and shifts in consumer behavior, our study adds the influence of environmental awareness and consumer preferences to the theoretical framework of analysis. We choose the contingent valuing method (CVM) and use 532 consumer questionnaires in Shanghai to validate Chinese urban consumers' WTP for low-carbon products and its influencing factors. The findings show that Chinese urban consumers have a high overall awareness of low-carbon agricultural products and, after strengthening the conceptual information of consumers, most consumers agree that low-carbon vegetables are more conducive to ecological environment protection, quality, and safety guarantees than conventional vegetables. The existing analysis showed that some variables such as bid price, behavioral attitudes, subjective norms, and consumption preferences significantly influenced consumers' willingness to pay for low-carbon leafy greens, while the effect of the environmental awareness variable was not significant. Further research found that consumers' WTP for low-carbon leafy greens showed significant group differences across income, gender, age, and education. Therefore, to promote the consumption of low-carbon agricultural products in China, we should attach importance to the publicity and guidance of low-carbon vegetables and strengthen the certification of low-carbon vegetable products. This study can provide policy reference for reasonably regulating and subdividing China's low-carbon agricultural products market.

Study on the Spatiotemporal Evolution and Influencing Factors of Agricultural Carbon Emissions in the Counties of Zhejiang Province.

The accurate measurement of agricultural carbon emissions and the analysis of the key influential factors and spatial effects are the premise of the rational formulation of agricultural emission reduction policies and the promotion of the regional coordinated governance of reductions in agricultural carbon emissions. In this paper, a spatial autocorrelation model and spatial Dubin model are used to explore the spatiotemporal characteristics, influential factors and spatial effects of agricultural carbon emissions (ACEs). The results show that (1) From 2014 to 2019, the overall carbon emissions of Zhejiang Province showed a downward trend, while the agricultural carbon emission density showed an upward trend. ACEs are mainly caused by rice planting and land management, accounting for 59.08% and 26.17% of the total agricultural carbon emissions, respectively. (2) The ACEs in Zhejiang Province have an obvious spatial autocorrelation. The spatial clustering characteristics of the ACEs are enhanced, and the "H-H" cluster is mainly concentrated in the northeast of Zhejiang, while the "L-L" cluster is concentrated in the southwest. (3) The results of the Dubin model analysis across the whole sample area show that the ACEs exhibit a significant spatial spillover effect. The disposable income per capita in the rural areas of the county significantly promotes the increase in the ACEs in the neighboring counties, and the adjustment of the industrial structure of the county has a positive effect on the agricultural carbon emission reductions in neighboring counties. (4) The grouping results show that there is heterogeneity between 26 counties in the mountainous areas and non-mountainous areas. In the 26 mountainous counties, the urbanization rate, rural population, mechanization level and industrial structure have significant negative spatial spillover effects on the carbon emissions. In the non-mountainous counties, the agricultural economic development level and disposable income per capita of the rural residents have significant spatial spillover effects on the agricultural carbon emissions. These research results can provide a theoretical basis for the promotion of the development of low-carbon agriculture in Zhejiang according to the region and category.

How does innovation consortium promote low-carbon agricultural technology innovation: An evolutionary game analysis

Low-carbon agriculture is a crucial component of sustainable development; technological innovation is the cornerstone of the agricultural transformation towards low-carbon production. This study developed a tripartite evolutionary game model for agricultural enterprise, university, and the government. It examined the low-carbon technology innovation of the agricultural innovation from an innovation consortium’s perspective, considering the dilemma that China’s low-carbon agriculture development faces owing to the lack of a single subject’s innovation capability. The simulation’s outcomes indicated: (1) The increase in collaborative innovation revenue, default costs (three–six times), and additional social benefits of collaborative innovation effectively promoted the evolutionary game results to (1,1,1), which means agricultural enterprises and universities choose collaborative innovation, and the government chooses to provide subsidies; (2) Enhancing innovation subsidies influenced game outcomes to a certain degree, but the effect was limited. The findings provide theoretical basis for government to enact policies to promote scientific and technological progress and to develop low-carbon agriculture.

Dynamic Linkages among Climate Change, Mechanization and Agricultural Carbon Emissions in Rural China.

Climate change has become a major environmental issue facing all countries, having a significant effect on all aspects of agricultural production, such as the agricultural mechanization process and fertilizer use. Greenhouse gases produced by agricultural machinery and fertilizers during agricultural production are an important cause of climate change. On the basis of the above facts, researching the connection between agricultural mechanization, climate change, and agricultural carbon emissions is crucial for the development of low-carbon agriculture and for addressing climate change. We used a variety of econometric models and methods to analyze data from China's multiple provinces (cities) covering the years 2000 through 2019, in order to meet the research objectives. Furthermore, we utilized rainfall and sunlight as variables to assess climate change and adopted Granger tests to establish the link between rainfall, sunlight, agricultural mechanization, and carbon emissions in farming. The findings indicate a bidirectional causality relationship between rainfall, sunlight, agricultural mechanization, and carbon emissions in farming. Rainfall and sunlight are Granger causes of agricultural mechanization. Furthermore, agricultural mechanization has favorable effects on carbon emissions of agriculture, and climate change has long-term implications on agricultural mechanization and carbon emissions of agriculture. Finally, this paper investigated the green path suitable for the low-carbon development of Chinese agriculture, arguing that the government should formulate low-carbon agricultural policies by region and actively promote the upgrading of agricultural machinery.

Spatiotemporally optimize water-nitrogen management of crop planting in response to carbon emissions mitigation

Greenhouse gas emissions from irrigation and nitrogen fertilizer applications in agriculture are attracting increasing attention, and the development of low-carbon agriculture has become an inevitable trend in the implementation of carbon neutrality. However, the optimization of water and nitrogen in crop planting still lacks precise management at the grid scale. From the perspective of agricultural carbon emission reduction, this study proposes a precise regional water and nitrogen management approach that can optimize irrigation and nitrogen fertilizer application in space and time. In this study, a coupled crop water-nitrogen production function model was constructed by analyzing the response relationship between nitrogen and water on crop yield. The verification results showed that the model had superior fitting accuracy, with R2 and NRMSE values of 0.88, 10.50%, 0.8 and 7.76% for maize and wheat, respectively. After combining the water-nitrogen coupling function with the cellular automaton model, a spatiotemporal optimization model was developed to realize grid-scale regional water and nitrogen management. The case study showed that the optimized irrigation and nitrogen scheme could save 2.73% of agricultural water, decrease nitrogen fertilizer use by 9.69%, and reduce carbon emissions by 4.39%. Correlation analysis of irrigation and fertilization can provide accurate guidance for regional irrigation and fertilization systems. Therefore, considering the contribution of agricultural “carbon reduction sources” to carbon neutrality, water saving, and nitrogen reduction should be considered in low-carbon agricultural development, which is conducive to the green and sustainable development of agriculture.

Research on the Efficiency of Green Agricultural Science and Technology Innovation Resource Allocation Based on a Three-Stage DEA Model-A Case Study of Anhui Province, China.

In order to achieve sustainable development of agriculture, people have gradually begun to attach importance to the development of low-carbon agriculture and to regard green agricultural technology innovation and promotion as increasingly more important. Taking the Anhui Province of China as an example, this study analyzed the impact of green agricultural science and technology innovation resource allocation on rural revitalization by constructing an econometric model. We found that the overall efficiency of the overall allocation of agricultural science and technology innovation resources in Anhui Province increased in the sample period, but the scale efficiency level was relatively low. The key path to improving the overall efficiency of allocation was to improve the scale efficiency level. The allocation of agricultural science and technology innovation resources in 16 cities and prefectures performed well in terms of pure technical efficiency, but there were significant differences in scale efficiency, which further affected the overall allocation efficiency of different regions. Among them, the allocation efficiencies of agricultural science and technology innovation resources in Hefei and Fuyang were at the leading level in Anhui Province. Similar to the overall situation of the province, the improvement path of areas with low comprehensive efficiency lay in the improvement of scale efficiency. In view of this, from the policy level, we need to optimize the relationship between the government and the market, speed up the construction of platforms and carriers, attach importance to the construction of the agricultural science and technology talent training system, and improve the open sharing mechanism.