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Eco-efficiency in cultivated land use is crucial for ensuring food security and promoting sustainable agriculture amidst the challenges posed by urbanization and climate change. Distinct from much of the existing literature, this paper adopts a super-efficiency EBM model that integrates both radial and non-radial perspectives to estimate the eco-efficiency of cultivated land use and identify sources of inefficiency under carbon emission constraints, focusing on 180 prefecture-level cities in China's major grain-producing regions. Additionally, spatial kernel density estimation is applied to analyze the spatiotemporal dynamics and long-term trends in eco-efficiency, while the Dagum Gini coefficient is used to examine the causes of spatiotemporal disparities. The key findings include (1) The Songhua River Basin shows significantly higher eco-efficiency (mean: 0.718) than the Yellow River (mean: 0.559) and Yangtze River Basins (mean: 0.587), with distinct evolutionary patterns; (2) Long-term evolution reflects a bipolar pattern with spatial agglomeration disparities; (3) Positive spatial spillover effects are evident in regions with efficiency levels between 0.4 and 0.9, with inter-regional differences and super-variable density as significant spatial variation sources. This study reveals a "long-term increase - short-term decline" trend in ecological efficiency, highlighting carbon emissions as the primary limiting factor, although this constraint is gradually diminishing.
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http://dx.doi.org/10.1038/s41598-025-09413-0 | DOI Listing |
Sci Rep
July 2025
Department of Management Science and Engineering, Business School, Nankai University, Tianjin, 300071, China.
Eco-efficiency in cultivated land use is crucial for ensuring food security and promoting sustainable agriculture amidst the challenges posed by urbanization and climate change. Distinct from much of the existing literature, this paper adopts a super-efficiency EBM model that integrates both radial and non-radial perspectives to estimate the eco-efficiency of cultivated land use and identify sources of inefficiency under carbon emission constraints, focusing on 180 prefecture-level cities in China's major grain-producing regions. Additionally, spatial kernel density estimation is applied to analyze the spatiotemporal dynamics and long-term trends in eco-efficiency, while the Dagum Gini coefficient is used to examine the causes of spatiotemporal disparities.
View Article and Find Full Text PDFEfficient nitrogen (N) management is critical for sustaining high maize yields while minimizing environmental impacts, as conventional practices often lead to N losses, greenhouse gas emissions, and reduced eco-efficiency. To address these challenges, the "Pusa N Doctor" app was developed using dark green colour index (DGCI) for precision N management in maize. The app was further validated in experiment conducted with three N rates- 0 kg/ha (N0PK), 50 kg/ha (N0PK), and 75 kg/ha (N75PK) as basal, along with two splits of N at 35 and 45 DAS as per app (N50PK+App and N75PK+App) and GSTM (N50PK + GSTM and N75PK+GSTM).
View Article and Find Full Text PDFPLoS One
April 2024
Nanning Normal University, Nanning, Guangxi, China.
Based on the integrated model of Super-SBM model, spatial Durbin model (SDM) and Grey neural network model, this paper analyzes the panel data of various provinces in China from multiple angles and dimensions. It was found that there were significant differences in eco-efficiency between organic rice production and conventional rice production. The response of organic rice to climate change, the spatial distribution of ecological and economic benefits and the impact on carbon emission were analyzed.
View Article and Find Full Text PDFSci Total Environ
April 2024
Yellow River Delta Modern Agricultural Engineering Laboratory, Chinese Academy of Sciences, Beijing 100101, China.
Under the twin pressures of global food security and dual‑carbon strategies, improving farm eco-efficiency is critical for achieving China's goal of a 50 Pg increase in grain production, meeting the ambitious climate mitigation targets set by the Paris Agreement, and meeting seven of the seventeen Sustainable Development Goals (SDGs) set by the United Nations. However, there is limited research on eco-efficiency measures supported by localised fine-scale data and coupling mechanisms for the structure, production process, efficiency improvement, and carbon reduction synergies of integrated farming systems in China. This study used the Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methods to assess eco-efficiency at the farm level in northern China, included in the National Coupling Crop and Livestock Production Pilot Programs, to improve the eco-efficiency of farms to achieve increased production and emission reductions.
View Article and Find Full Text PDFSci Total Environ
September 2023
Department of Agronomy, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, UP 221 005, India. Electronic address:
The study aimed to manage industrial wastes and create a module for using compost from waste for crops cultivation to conserve energy, reduce fertilizer use and Greenhouse gas (GHG) emissions, and improve the atmospheric CO capturing in agriculture for a green economy. In the main-plot, the experiment's results using NS3 found 50.1 and 41.
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