Agricultural Eco-efficiency Research Articles

Can farmers’ adoption of conservation tillage achieve sustainable agricultural production targets? Evidence from the Jianghan Plain, Hubei, China

ABSTRACT As a major agricultural country, China is under threat from land degradation because of long-term high-carbon-emission land use patterns. Conservation tillage (CT) technologies are expected to restore soil fertility, transform agricultural production models, and improve sustainability. However, the impacts of farmers’ CT adoption on achieving sustainable agricultural development remain unclear. To investigate the heterogeneous ecological effects resulting from farmers’ adoption of CT technologies, this study estimates the ecological effects of CT and examines the differences in these effects across different technologies, utilizing survey data from 1,449 farmers in the rural Jianghan Plain of China. The results show that farmers’ technology perceptions, previous adoption behaviour, and collective economic conditions significantly affect their CT adoption behaviour. The agricultural eco-efficiency in the Jianghan Plain is only 0.65. After removing bias from self-selection and unobservable factors, the ecological effect of CT adoption was 8.43%. The four different CT technologies evaluated in this study were found to increase agricultural eco-effects and achieve sustainable agriculture. However, the agricultural eco-effects of different CT technologies vary, indicating heterogeneity. Finally, policies that include implementing different combinations of CT models according to local conditions, technical training, and establishing subsidies for CT adoption are highly recommended.

Has the Policy of National Agricultural Green Development Pilot Zones Enhanced the Agricultural Eco-Efficiency? Observation Based on the County-Level Data from Hubei Province of China

China’s agricultural green development is of great significance to protecting the ecological environment, ensuring food security, and promoting rural revitalization. This study considers China’s agricultural green development pilot zones policy as a natural experiment to examine its impact on regional agricultural eco-efficiency. Based on county-level data in Hubei Province from 2013 to 2021, the EBM-Undesirable model was employed to measure regional agricultural eco-efficiency. Then, the staggered DID model was conducted to estimate the policy impact. The results indicate that the pilot zones policy significantly enhances the agricultural eco-efficiency in the designated areas. The results from heterogeneity and mechanism analysis indicate that the pilot zones policy has a more substantial effect on the western region and less-affluent counties, and rural innovation serves as an intermediary variable for the policy to exert the “green” effect. Therefore, it is crucial for the government to consider regional disparities and the role of rural innovation when advancing policy implementation. Tailoring measures to suit specific local circumstances and consistently enhancing agricultural eco-efficiency in different regions is essential.

Agricultural Eco-Efficiency: Progress, Challenges, and Prospects

Agricultural Eco-Efficiency: Progress, Challenges, and Prospects

Socio-Eco-Efficiency in Agroforestry Production Systems: A Systematic Review

Eco-efficiency has emerged to reduce environmental impacts and improve competitiveness in various industries, including agriculture. However, the application of eco-efficiency in agroforestry, incorporating social variables, is a relatively recent development. This study conducted a review of the scientific literature on eco-efficiency to address key questions. The analysis utilized the Web of Science Core Collection database, focusing on categories such as sustainable eco-efficiency, agricultural eco-efficiency, forestry eco-efficiency, and socio-eco-efficiency. The objective of this work is to offer a bibliometric analysis on socio-eco-efficiency in agroforestry production systems. The results revealed three stages in eco-efficiency research: an initial stage with low publication numbers, a second stage marked by significant growth and a focus on sustainable development, and a third stage characterized by rapid growth and increasing interest. In the field of agricultural eco-efficiency, there has been a recent increase in publications, reflecting the growing importance of agriculture in eco-efficiency analyses. China emerged as the leading country in terms of scientific advancements in eco-efficiency. The study also identified key research areas and institutions contributing to the literature on agricultural eco-efficiency. Overall, the findings highlight the expanding interest and future potential of socio-eco-efficiency in agroforestry research.

Achieving higher eco-efficiency for three staple food crops with ecosystem services based on regional heterogeneity in China

Farmland ecosystems can provide both economic products and ecosystem services that are important in maintaining food security and ecological safety. However, the ecological functions of farmland ecosystems have not been adequately evaluated in China, especially from the perspective of ecological efficiency for three staple food crops (wheat, maize and rice). Moreover, the contribution of ecosystem services value (ESV) to agricultural eco-efficiency (AEE), and the factors that influence AEE for the three staple food crops in different regions are still unclear. In this study, data envelopment analysis (DEA) was applied to calculate the AEE using group-frontier and meta-frontier methods based on regional heterogeneity. We measured AEE for wheat, maize and rice production with and without ESV and compared the gap between ecological inefficiency resulting from management inefficiency and technology gap inefficiency. The research results showed that, first, the involvement of ESV could effectively promote AEE. In particular, water conservation, soil conservation and the nutrient cycle contributed to the promotion of eco-efficiency. The mean ΔAEE (the difference in AEE with or without ESV) of wheat, maize and rice increased by 15 %, 10 % and 13 % with group-frontier and by 20 %, 10 % and 11 % with meta-frontier, respectively. Second, the improvement of AEE was higher in ecologically sensitive areas than that in other areas, especially for wheat and rice. Third, although the involvement of ESV reduced ecological inefficiency, specifically for management inefficiency, its contribution differed significantly across regions. We provide suggestions on improving AEE and reducing inter-regional differences in China. In brief, these findings suggest that, except for grain yields, ecosystem services need to be recognized in the production of three staple food crops, especially in ecologically sensitive areas. This is helpful for crop planning and planting division in terms of sustainable development.

Coupling Coordination between Agricultural Eco-Efficiency and Urbanization in China Considering Food Security

When studying the coupling coordination relationship between agricultural eco-efficiency and urbanization, it is crucial to consider food security, especially in a populous country like China. This paper focuses on 31 provinces in China as the research units, covering the time period from 2000 to 2020. Based on the concept of agricultural eco-efficiency, an evaluation index system was developed to include undesirable outputs (carbon emissions), and agricultural eco-efficiency scores were calculated using the SBM–DEA model. An urbanization evaluation index system, covering six dimensions and twelve indexes, was constructed. A comprehensive index of urbanization is measured using the entropy method. On this basis, a coupling coordination model was applied to quantify the relationship between agricultural eco-efficiency and urbanization at the provincial scale in China. The results showed that the agricultural eco-efficiency of all provincial units in China exhibited an overall trend of improvement. Average efficiency followed a spatial pattern of majority grain-consuming areas > grain production–consumption balance areas > majority grain-producing areas. The level of coupling between agricultural eco-efficiency and urbanization is generally low. Currently, no regions have reached the stage of synergy or high-level coupling. Most regions are currently in an antagonistic stage with a coupling degree of 0.3 < C ≤ 0.5. The classification of coupling coordination levels changed from four levels of “severe imbalance”, “moderate imbalance”, “mild imbalance”, and “primary coordination” to “moderate imbalance”, “mild imbalance”, “primary coordination”, and “intermediate coordination”. The level of “severe imbalance” disappeared, the level of “intermediate coordination” appeared, and the level of “mild imbalance” became the largest scale level. From the perspective of food security, the proportion of grain production in the categories of “primary coordination” and “intermediate coordination” was less than 10%, and these provinces never achieved self-sufficiency in food production. The proportion of grain production at the “mild imbalance” level reached 62.4%, while the per capita grain production at the “moderate imbalance” level reached 846.7 kg. Provinces with lower levels of coupling coordination have stronger food security capabilities. It can be observed that the weaker the coupling coordination between agricultural eco-efficiency and urbanization, the higher the food self-sufficiency. Based on the research results above, we discussed strategies to enhance agricultural eco-efficiency in majority grain-producing regions by focusing on technological progress and technical efficiency. Additionally, we analyzed approaches to achieve grain self-sufficiency in regions characterized by a high level of coordination between agricultural eco-efficiency and urbanization, considering both production and trade dimensions.

Mechanisms and Impact Effects of Digital Agriculture Development on Agricultural Eco-Efficiency in China

The green development of agriculture is an essential way to achieve high-quality agricultural development, and the development of digitalization has given new momentum to the green development of agriculture. In this study, based on the panel data of 30 provinces in China from 2011 to 2022, we measure the agricultural eco-efficiency and the level of digital agriculture development in China using the Super-SBM model with global reference and the entropy value method, respectively. The impact of the level of digital agriculture development on agricultural eco-efficiency is explored with the help of a regression model, and the mediating role of pesticide and fertilizer inputs in this impact pathway is explored using a mediating effects model. The study found that: (1) the level of digital agriculture development positively and significantly affects agricultural eco-efficiency to a relatively large extent; (2) the effect of digital agriculture development on the improvement of agriculture eco-efficiency is significantly heterogeneous in different regions; (3) pesticide and fertilizer inputs have a mediating role in this impact pathway. Therefore, the application and promotion of digital agriculture technology should be strengthened to build a green agricultural production and management system, so as to promote high-quality and sustainable development of Chinese agriculture.

Impact of rural digital economy development on agricultural eco-efficiency: evidence from mainland China

The integration of the digital economy with rural development is of great significance as it plays a pivotal role in mitigating carbon emissions and environmental pollution in agriculture, thereby contributing to the evolution of agriculture in a green and sustainable manner. This study aims to examine the impact and mechanisms of rural digital economy development (RDED) on agricultural eco-efficiency (AEE). Specifically, based on provincial-level panel data from China spanning from 2011 to 2021, we evaluate China’s AEE by employing the super-efficiency slacks-based measure (Super SBM) model, taking into account the positive externality of agricultural carbon sinks. Then we analyze the impact and mechanisms of RDED on AEE using the two-way fixed effects model. The findings indicate that: (1) RDED significantly promotes AEE, and this conclusion remains robust even after being tested by replacing the explained variable, altering the sample interval, and including more control variables; (2) RDED can significantly drive AEE in the midwestern regions of China, but the promotion effect on the eastern region has not been fully demonstrated. Additionally, the promotion effect in southern China is greater than that in northern China; (3) agricultural science and technology investment partially mediates the impact of RDED on AEE. Moreover, agricultural science and technology innovation has a positive moderating effect on the relationship between RDED and AEE. Lastly, this study provides new evidence and policy recommendations for developing countries, such as China, to proactively facilitate the coordinated development of the rural digital economy and agricultural ecology, and attain green and sustainable ecological agriculture.

Agricultural eco-efficiency and sustainable agricultural development influential factors and heterogeneities: Exclusive evidence from Chinese cities

Agricultural eco-efficiency and sustainable agricultural development influential factors and heterogeneities: Exclusive evidence from Chinese cities

Measurement of Agricultural Eco-Efficiency and Analysis of Its Influencing Factors: Insights from 44 Agricultural Counties in Liaoning Province

Agricultural eco-efficiency (AEE) considers economic and environmental benefits and is a key indicator of green agricultural development. To achieve the multiple goals of improving agricultural production efficiency, reducing agricultural environmental damage, and reducing the input of agricultural resources, this study enriches the case study of agricultural production performance evaluation at the county level by measuring the AEE of 44 agricultural counties in Liaoning Province based on panel data and a super-efficient slacks-based measure model including undesired outputs. A two-way fixed-effects model was used to analyze the impact of agricultural development, macro-environment, and policy support on AEE. We found that the average AEE of the counties in Liaoning Province in 2014, 2016, 2018, and 2020 was 0.716, 0.735, 0.749, and 0.813, respectively, indicating a cumulative improvement rate of 13.55%. The average AEE levels gradually improved during the study period. Notably, the development of AEE among the counties was uneven. AEE was distributed in a “block-like” manner, and its local correlation presents a phenomenon of “small agglomeration and large dispersion”. In addition, the level of the agricultural economy, industrialization, and urbanization significantly promoted the improvement of AEE, and the promoting effects varied between different income levels and regions. Therefore, Liaoning Province needs to improve the AEE of each county according to local conditions and narrow the differences in AEE between counties. To continuously improve the level of rural economic development, lead the development of agricultural modernization with new urbanization, and comprehensively improve the overall AEE of counties. The research results are of guiding significance for deepening the study of AEE and can provide decision-making support for optimizing the mode of agricultural production and promoting the green development of regional agriculture.

Re-measurement and influencing factors of agricultural eco-efficiency under the ‘dual carbon’ target in China

Given that agriculture is both a carbon source and sink, the sustainability goals of carbon peaking and neutrality place high demands on the green and low-carbon agricultural development in China, and the exploration of a realistic path for a sustainable agricultural development is urgently needed. Under the above ‘dual carbon’ target, this study focused on the key issue of how to improve China's agricultural eco-efficiency (AEE) and constructed an innovative AEE indicator system that can reflect carbon constraint and coordinated agricultural economic development, resource use and ecological environment. The super-efficient slack-based measured Data Envelopment Analysis (SBM-DEA) method, which considers undesirable outputs, was applied to re-measure the AEE of 30 provinces and cities in China from 2001 to 2020, and its spatial and temporal evolution was analysed in conjunction with kernel density estimation. The Tobit regression model was used to explore various influencing factors by region. The results show that the AEE re-measurements, which take into account the 'dual carbon' requirement, are significantly better than the traditional AEE. From 2001 to 2020, China had an overall V-shaped fluctuation curve AEE, with a small decline and several inter-annual fluctuations, and exhibited a large potential to rise. China's AEE showed a spatially uneven regional development at different stages of distribution and evident multi-polar differentiation. Inter-provincial differences were observed in China's AEE, and the vicious circle of low-level green and low-carbon agricultural development was difficult to break. Urbanisation had a significant positive effect on national and eastern AEE but a significant negative effect on central AEE. The agricultural carbon offset rate had a significant effect on AEE nationally and in the three regions. Thus, the introduction of ‘dual carbon’ target effectively drove the development of AEE. Agricultural industry structure inhibited the improvement of AEE nationally and in the western region. Agricultural economic development hindered the national AEE improvement but promoted that of the central region, where China showed an environment Kuznets curve. Hopefully, this study can provide data support and theoretical reference for the green and low-carbon agricultural development and help achieve the ‘dual carbon’ target.

Evaluation of County Agricultural Eco-Efficiency in Chongqing and Analysis of Its Spatiotemporal Differentiation under the Dual Carbon Target

Evaluation of County Agricultural Eco-Efficiency in Chongqing and Analysis of Its Spatiotemporal Differentiation under the Dual Carbon Target

Impact and Spatial Effect of Socialized Services on Agricultural Eco-Efficiency in China: Evidence from Jiangxi Province

Agricultural eco-efficiency (AEE) is a crucial indicator of the green development of agriculture. Agricultural socialized services (AS) provide services for the agricultural production process and they promote the effective input of production factors, such as science and technology, talent, information, and capital, into the agricultural production chain, deepening the division of labor and injecting vitality into agricultural development. We measured AEE based on field research data in Jiangxi Province, China. We also constructed an endogenous switching model to explore the impact of AS on AEE. Our results show that, based on the counterfactual assumption, the AEE increased by 13.19% among farmers who adopted the services compared to those who did not. From the perspective of scale and structural differences, the larger the scale of agricultural cultivation, the stronger the impact of AS on AEE. Furthermore, a large share of cash crops was found to inhibit the impact of AS on AEE. We also investigated whether farmers in close proximity to each other affect their neighbors through knowledge dissemination and technology spillover. The extent of the impact of AS on AEE depended on distance thresholds: it was more pronounced when we increased the distance threshold. Our results suggest that the government should improve the AS system, provide more public welfare services, and appropriately subsidize AS organizations. The AS for food crops should be emphasized; however, those for cash crops should not be ignored.

Agricultural eco-efficiency and water footprint- A case study of fifteen crops in the Chupaca province of Peru

The water footprint is an indicator of the impact of water use from its formation to its final destination. Agricultural eco-efficiency measures the efficient use of resources or materials available for crop production. Water's economic productivity analyses a product's efficient value as per its water supply and commercial value. The present research aimed to determine and relate the water footprint, economic productivity of water and agricultural eco-efficiency of 15 crops in the province of Chupaca - Peru. Georeferencing material was used for the delimitation of agricultural species, CROPWAT 8.0, CLIMWAT8.0, ArcGis 10.5 software, mathematical equations for the water footprint, agricultural eco-efficiency (Data Envelopment Analysis (DEA)) and economic productivity of water. The Total water footprint (TWF) of the fifteen crops was 1718237.01 m3/ton, likewise the BlueWF > GreenWF > GreyWF. In their economic outputs, gross value of production (GVP) > agricultural production (Ag-p) > economic rent agricultural (ERA) was verified. In environmental costs, water consumption that meets the needs of crops (Wc-Ag) > consumption of phytosanitary products (C-fly) > fertilizer consumption (C-fe) was determined. The average Agricultural eco-efficiency (Ag-Eec) and Economic water productivity (Ewp) were 89.8% and 0.046 PEN/m3 respectively. Statistical analysis between Ewp and Ag-Eec was rho = 0.18, t-test = 0.66 < 2.16 (α = 0.05; bilateral), and the correlation indicated that both activities are independent. The environmental costs and economic outputs of agricultural eco-efficiency did not influence the economic value of water.

Nonlinear Effect of Farmland Management Scale Expansion on Agricultural Eco-Efficiency: A Moderating Effect of Service Outsourcing

Nonlinear Effect of Farmland Management Scale Expansion on Agricultural Eco-Efficiency: A Moderating Effect of Service Outsourcing

Measurement and temporal and spatial characteristics of agricultural eco-efficiency under climate change: a case study of Anhui, China

IntroductionAgricultural eco-efficiency is an important index to evaluate the agricultural sustainable development and ecological economics, while simultaneously providing a metric for improvements to the rural environment and the stability of agricultural ecosystems.MethodsThis study took Anhui province as a case, and applied unit survey and list analysis methodologies to quantify rural agricultural non-point source pollution (NPS). Input-oriented super-efficient DEA-SBM was used to measure agricultural eco-efficiency in the typical North-South Transition Zone, and evaluated spatial correlations and differences.ResultsThis study showed that NPS was relatively stable, with less than 5% local variation in Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP) pollutants. The environmental pressure caused by livestock breeding and the use of chemical fertilizers was very substantial, and the differences of rural agricultural NPS in Anhui Province had obvious north-south characteristics. The agricultural eco-efficiency exhibited an “inverted N” trend. Affected by the “Spatial proximity effect” and the “Matthew effect”, it presented spatial agglomeration and positive spatial correlation. The regional differences were significant, and the heterogeneity increased in our study areas. The southern region had the greatest variation, followed by the northern region, with the smallest variation in the central region, although inter-regional differences were consistent.DiscussionThough the rational allocation of resources, coordination between agricultural economic and environmental protection would be realized, and better conditions for the sustainable development of agricultural ecology and the long-term stability of agricultural ecosystem would be created.

How do outsourcing services affect agricultural eco-efficiency? Perspectives from farmland scale and technology substitution

In-depth research on whether the development of agricultural outsourcing services (AOS) can improve agricultural eco-efficiency (AEE) and the mechanisms underlying the impact of AOS on AEE is still lacking. This study uses micro survey data from Jiangxi Province in China in 2021 to explore the impact of AOS on AEE in terms of farmland scale management and agricultural technology substitution. The results indicate that AOS in general can effectively improve AEE, but this effect varies across the different stages of production. Plough services, fertilizer application services, and pest control services can significantly improve AEE, but seeding services and harvesting services have no significant effect. Farmland scale management and agricultural technology substitution are two effective channels by which AOS improves AEE. The government should improve policies to support AOS, strengthen the positive effects of AOS on AEE, and implement differentiated support policies for AOS related to different production activities.

Spatiotemporal evolution and convergence of agricultural eco-efficiency in the middle reaches of the Yangtze River

In the context of regional coordinated development, exploring the spatiotemporal evolution characteristics of agricultural eco-efficiency(AEE) in the middle reaches of the Yangtze River(MRYR) can provide decision support for the coordinated development of regional agriculture. This study proposes a theoretical hypothesis of AEE spatial convergence at the input-output level and uses the Super-SBM model, kernel density estimation, spatial autocorrelation and β-convergence model to calculate the spatiotemporal evolution and convergence characteristics of AEE in the MRYR from 2005 to 2020. The results show that (1) from 2005 to 2020, the AEE of the study area increased from 0.665 to 0.864, with the average efficiency of Hubei, Jiangxi, and Hunan reaching 0.794, 0.767, and 0.724, respectively; and (2)the overall spatial convergence rate of AEE is 0.045, and there is a phenomenon of “club convergence” between regions. The spatial convergence rates of Jiangxi, Hubei, and Hunan are 0.053, 0.063, and 0.048, respectively. The convergence rate slows down over time, (3) The farmers' living standards, per capita GDP, and technological level have promoted the improvement of AEE. Multiple planting indices and financial support for agriculture have not had a positive effect on the improvement of AEE. The region should strengthen the exchange and cooperation of agricultural production and pay attention to the pollution discharge problem of agricultural production.

The effect of urbanization on agricultural eco-efficiency and mediation analysis

Improving agricultural eco-efficiency (AEE) is a promising way to achieve the sustainability of agricultural development. Although AEE evaluation and driving forces were widely explored, few studies have systematically examined how urbanization, the core driving force, affected AEE. To supplement the existing literature, the GB-US-SBM model was used to assess AEE in China during 2004–2020. Furtherly, it used the mediation effect model to investigate how urbanization influenced the AEE in different agriculture development regions by reducing agricultural labor and changing rural residents’ income. The results showed that: 1) During 2004–2020, China’s AEE revealed a stable improvement, with the mean score increasing from 0.138 to 0.744. Regarding spatial distribution, AEE exhibited a gradient decrease: optimized development region > moderate development region > protected development region. 2) Urbanization had a significantly positive effect on AEE, with the magnitude of the effect greatest in the protected development region, followed by the moderate development region and the optimized development region. 3) The mediator variables, agricultural labor and rural residents’ income, positively mediated the relationship between urbanization and AEE, and the former had a larger mediating effect. Notably, rural residents’ income did not mediate the effect of urbanization on AEE in the protected development region. According to the findings, to improve sustainable agriculture development and urbanization development in China, some policy suggestions were put forward from the aspects of transforming agricultural development mode, accelerating the urbanization process, enhancing vocational education for the middle-aged and young rural labor force, and expanding channels for increasing rural residents’ income.

Spatial Association Network and Driving Factors of Agricultural Eco-Efficiency in the Hanjiang River Basin, China

Reducing agricultural emissions and promoting carbon sequestration are vital for China to achieve its dual carbon goals. Achieving the green transformation of agricultural watersheds requires a thorough understanding of the internal transmission relationships within the watersheds and the underlying spatial correlation structures. This paper used the SBM-3E model to calculate the agricultural ecological efficiency of 17 prefecture-level cities in the Hanjiang River Basin (HRB) from 2010 to 2020, taking agricultural carbon emissions and a comprehensive non-point source pollution index as the unexpected output. The Gravity model and social network analysis methods were used to analyze the evolution characteristics of the network structure of agricultural ecological efficiency, and the secondary assignment procedure method was used to identify the driving factors from the planting structure, water use structure, and resource endowment. First, from 2010 to 2020, the overall agricultural ecological efficiency in the HRB demonstrates a declining trend, with efficiency values of 12.15, 9.40, and 6.67 in the upper, middle, and lower reaches, respectively. Second, the spatial correlation network density of agricultural ecological efficiency in the HRB is 0.17, with a network efficiency of 0.89. The correlation among units within the basin is relatively low, but stability is high. Moreover, the individual network spillover absorption capacity exhibits heterogeneity, and the status of each subject within the watershed follows a “core-edge” structure. Third, total water consumption and corn cultivation have a positive impact on the agricultural ecological efficiency network in the HRB, whereas agricultural water use and rice cultivation negatively influence the network. We propose policy recommendations to facilitate the advancement of green development in China’s agricultural watersheds and the achievement of the dual carbon goals.