Search Results (126)

The Qinba Mountains in China span six provinces, characterized by a large population, rugged terrain, steep peaks, deep valleys, and scarce flat land, making large-scale agricultural development challenging. Terraced fields serve as the core cropland type in this region, playing a vital role in preventing soil erosion on sloping farmland and expanding agricultural production space. They also function as a crucial medium for sustaining the ecosystem services of mountainous areas. As a transitional zone between China’s northern and southern climates and a vital ecological barrier, the Qinba Mountains’ terraced ecosystems have undergone significant spatial changes over the past two decades due to compound factors including the Grain-for-Green Program, urban expansion, and population outflow. However, current large-scale, long-term, high-resolution monitoring studies of terraced fields in this region still face technical bottlenecks. On one hand, traditional remote sensing interpretation methods rely on manually designed features, making them ill-suited for the complex scenarios of fragmented, multi-scale distribution, and terrain shadow interference in Qinba terraced fields. On the other hand, the lack of high-resolution historical imagery means that low-resolution data suffers from insufficient accuracy and spatial detail for capturing dynamic changes in terraced fields. This study aims to fill the technical gap in detailed dynamic monitoring of terraced fields in the Qinba Mountains. By creating image tiles from Landsat-8 satellite imagery collected between 2017 and 2020, it employs three deep learning semantic segmentation models—DeepLabV3 based on ResNet-34, U-Net, and PSPNet deep learning semantic segmentation models. Through optimization strategies such as data augmentation and transfer learning, the study achieves 15-m-resolution remote sensing interpretation of terraced field information in the Qinba Mountains from 2000 to 2020. Comparative results revealed DeepLabV3 demonstrated significant advantages in identifying terraced field types: Mean Pixel Accuracy (MPA) reached 79.42%, Intersection over Union (IoU) was 77.26%, F1 score attained 80.98, and Kappa coefficient reached 0.7148—all outperforming U-Net and PSPNet models. The model’s accuracy is not uniform but is instead highly contingent on the topographic context. The model excels in environments that are archetypal for mid-altitudes with moderately steep slopes. Based on it we create a set of tiles integrating multi-source data from RBG and DEM. The fusion model, which incorporates DEM-derived topographic data, demonstrates improvement across these aspects. Dynamic monitoring based on the optimal model indicates that terraced fields in the Qinba Mountains expanded between 2000 and 2020: the total area was 57.834 km² in 2000, and by 2020, this had increased to 63,742 km², representing an approximate growth rate of 8.36%. Sichuan, Gansu, and Shaanxi provinces contributed the majority of this expansion, accounting for 71% of the newly added terraced fields. Over the 20-year period, the center of gravity of terraced fields shifted upward. The area of terraced fields above 500 m in elevation increased, while that below 500 m decreased. Terraced fields surrounding urban areas declined, and mountainous slopes at higher elevations became the primary source of newly constructed terraces. This study not only establishes a technical paradigm for the refined monitoring of terraced field resources in mountainous regions but also provides critical data support and theoretical foundations for implementing sustainable land development in the Qinba Mountains. It holds significant practical value for advancing regional sustainable development. Full article

This research explores the digital economy’s impact on high-quality agricultural development, with a particular focus on its effect on Agricultural Green Total Factor Productivity (AGTFP). By integrating Dynamic Qualitative Comparative Analysis (QCA) and Necessary Condition Analysis (NCA) on data spanning from 2011 to 2023 across 31 Chinese provinces, the study produces the following results: (1) No single element of the digital economy alone is indispensable for enhancing AGTFP. Instead, its driving force stems from the synergistic interactions among multiple elements. Configuration analysis identifies four effective pathways to boost AGTFP: the financial–government dual-driver model, the infrastructure–government dual-driver model, the financial–resource dual-driver model and the industry-led driver model. (2) Regional disparities exist in the approaches to achieving high-quality agricultural development. The eastern region prioritizes the integration of finance and policy, while the central and western regions emphasize the synergy between infrastructure and government initiatives. (3) The identified pathways demonstrate temporal stability, with digital finance pathways exhibiting particularly high consistency over the study period, maintaining a temporal stability exceeding 0.85 in most years. This study combines the TOE framework with configuration analysis to enrich the theoretical framework of agricultural digitalization, revealing key pathways through which the digital economy can propel green agriculture development and offers empirical evidence to inform tailored digital agriculture policies. Full article

The accumulation of microplastics in agricultural soils poses a serious threat to both crop production and ecosystem health. To explore potential remediation strategies, we conducted a two-factor pot experiment (PE-MPs × TSB). This study was designed to systematically analyze the interactive effects of polyethylene microplastics (PE-MPs) and tobacco stalk-derived biochar (TSB) on soil properties, physiological characteristics, and growth indicators of wheat. Results indicated that TSB addition significantly increased soil pH, organic matter, and available potassium content, which was associated with a mitigation of the soil acidification and nutrient imbalance observed under PE-MPs. Physiologically, TSB was linked to higher activities of antioxidant enzymes (SOD and POD) and maintained leaf chlorophyll content and photosynthetic function, thereby consistent with a reduction in oxidative stress and better maintenance of growth in the presence of PE-MPs. Furthermore, partial least squares structural equation modeling (PLS-SEM) supported a hypothetical cascading pathway for TSB’s dominant influence: soil improvement → physiological mitigation → growth recovery. The total effect of TSB on biomass (0.71) was substantially greater than that of PE-MPs (0.01). This study proposes a conceptual model and provides correlative evidence that is consistent with multi-level processes through which TSB may alleviate PE-MPs stress, thereby providing theoretical support for the resource utilization of agricultural waste and the green remediation of microplastic-contaminated soil. Full article

In the context of promoting sustainable and low-carbon agricultural development, this study investigates the effects of rural labor migration (RLM) on agricultural ecological efficiency from the perspective of green total factor productivity (GTFP). Using panel data from 30 Chinese provinces (autonomous regions, municipalities) over 2011–2022, agricultural GTFP is calculated via the SBM–Global Malmquist–Luenberger (SBM–GML) index. Baseline regressions and the spatial Durbin model (SDM) are employed to examine the impacts of labor migration. The research results show that: (1) Agricultural ecological efficiency exhibits significant spatial clustering, demonstrating “high–high” and “low–low” aggregation patterns. (2) RLM significantly enhances local agricultural ecological efficiency while also generating a positive spatial spillover effect. (3) The effects are heterogeneous: northern regions and highly urbanized areas experience stronger positive impacts, whereas southern regions and less urbanized areas show weaker effects. The findings highlight the pivotal role of RLM in promoting agricultural modernization and provide insights for enhancing regional coordination and ecological efficiency. Full article

Digital literacy (DL) among farmers serves as a vital link between digital technology and green sustainable development, significantly enhancing agricultural green total factor productivity (AGTFP). This study employs panel data from the China Family Panel Studies (CFPS) covering 2014–2020, applying a two-way fixed effects model and machine learning techniques to examine the influence of farmers’ digital literacy on AGTFP. The results indicate that DL positively contributes to AGTFP. Further heterogeneity analysis shows stronger effects among male farmers, households with low trust, and those within the working-age population. Mechanism analysis indicates that social capital accumulation mediates the relationship, whereas agricultural socialization services strengthen the positive impact of DL on AGTFP. Additional analysis using machine learning models reveals that the impact of farmers’ digital literacy on AGTFP changes over time. Specifically, entertainment and learning-oriented network use enhances AGTFP, whereas work-related, social, and lifestyle-related use suppresses it. This study offers a more nuanced understanding by shifting from traditional macro-level frameworks to a micro-level perspective focused on farmers’ digital literacy. Moreover, the innovative application of explainable machine learning provides empirical evidence for the underlying drivers of AGTFP. Full article

This paper evaluates the eco-efficiency of crop production in the European Union (EU) and the Republic of Serbia for the period 2015–2023, using a stochastic frontier analysis (SFA) model based on panel data. Eco-efficiency was assessed as the ratio of agricultural output to key environmental pressures, with expenditures on fertilizers, plant protection products, and energy serving as proxies for ecological burden. The analysis shows that the average eco-efficiency score (Total EE) across the sample is 59.26%, implying that nearly 41% of inputs could be reduced without decreasing output. Decomposition reveals high residual eco-efficiency (93.62%) and lower persistent eco-efficiency (63.30%), suggesting that systematic inefficiencies dominate and are primarily linked to internal farm-level factors such as management practices, organizational structures, and technology adoption. Serbia’s total eco-efficiency score of 63.0% places it close to the EU average, confirming structural similarities with Southern and Eastern European countries. Eco-efficiency scores exhibit notable cross-country variation, ranging from approximately 35% to 96%. About 59% of countries fall within the 50–75% interval, while roughly 11% exceed 75%, indicating considerable scope for further improvement. Cluster analysis further indicates that while Serbia belongs to the lower-intensity group, it has significant potential to converge toward EU frontrunners through farm-level improvements. The findings highlight the importance of targeting internal determinants of efficiency, while recognizing that policy measures can provide enabling conditions and long-term incentives for the green transition. A coherent policy for the green transition should prioritize farm-level structural upgrades, such as technology adoption, advisory and knowledge transfer, and sustainable nutrient and soil management, supported by enabling CAP instruments (eco-schemes and GAEC) and IPARD measures to accelerate improvements in resource efficiency and environmental performance. Full article

Using a balanced provincial panel of 31 Chinese regions (2014–2022), this study examines how Digital Inclusive Finance (DIF) and Rural E-Commerce (RE) jointly shape the urban–rural income gap. Two-way fixed effects and instrumental-variable estimators mitigate confounding. Both DIF and RE are associated with narrower gaps, and the interaction term is negative and robust across specifications. Mechanism evidence indicates that the coupling operates through higher Agricultural Green Total Factor Productivity, expanded rural credit supply, and stronger entrepreneurship. Effects are larger in Central/Western provinces and are most pronounced when DIF’s usage-depth and digital-support components are salient. For policymakers and managers, the findings support bundled investments in digital rails, platform logistics, and e-commerce–linked credit, with priority to lagging regions and programs that deepen usage. Overall, the results provide a tractable systems approach to aligning finance and markets for inclusive rural transformation. Full article

As a critical ecological barrier and key dryland agricultural zone in China, the Loess Plateau is faced with acute tensions between food security risks arising from cropland abandonment (CA) and the imperatives of ecological conservation. Yet, existing research has failed to adequately capture the long-term, high-spatiotemporal-resolution dynamics of abandonment in this region or to quantitatively couple its driving mechanisms with implications for food security. To address these gaps, this study establishes a high-precision identification system for CA tailored to the Plateau’s complex topographic conditions, distinguishing among interannual abandonment, multiyear abandonment, conversion to forest/grassland, and reclamation. Leveraging long-term data from 2000 to 2023 and integrating the Mann–Kendall test with the random forest algorithm, we examine the spatiotemporal trajectories, driving forces, and food security consequences of CA. Guided by a “type differentiation–grade classification–temporal tracking” framework, the analysis reveals a marked transition in dominant drivers from “socioeconomic factors” to “topographic–climatic factors.” It further identifies an “increasing loss–slowing growth” effect of abandonment on grain production, alongside a “pressure alleviation” trend in per capita carrying capacity. The results showed that: (1) Between 2000 and 2023, the area of CA on the Loess Plateau expanded from 2.72 million ha to 6.96 million ha, with high-grade abandonment (≥8 years) accounting for 58.9% of the total and being spatially concentrated in the hilly–gully regions of northern Shaanxi and eastern Gansu; (2) The Grain for Green Project (GFGP) peaked at approximately 340,000 hectares in 2018, followed by a slight decline, but has generally remained at around 300,000 hectares since then; (3) The reclamation rate of CA remained between 5% and 12% during 2003–2015, with minimal overall fluctuations, but after 2016, it gradually increased and peaked at 23.4% in 2022; (4) In terms of driving forces, population density (14.99%) was the primary determinant in 2005, whereas by 2020, slope (15.43%) and mean annual precipitation (15.63%) emerged as core factors; and (5) Grain yield losses attributable to abandonment increased from less than 100 t to nearly 450 t, though the growth rate slowed after 2016, accompanied by gradual alleviation of pressure on per capita carrying capacity. Overall, the study offers robust empirical evidence to inform cropland protection, food security strategies, and sustainable agricultural development policies on the Loess Plateau. Full article

Sustainable agricultural development requires ensuring food security while preserving essential ecological conditions. This study incorporated ecosystem service value and carbon emissions as the positive and negative ecological outputs of agriculture, respectively, to account for the AGEE of 31 Chinese provinces from 2012 to 2021 and to analyse its spatiotemporal characteristics. The Malmquist Index was employed to calculate the green total factor productivity (GTP) as a quantitative indicator of AGEE dynamics, providing further insights into the sources and equilibrium of AGEE growth, as well as provincial-level improvement paths. Furthermore, the Spatial Durbin Model was applied to systematically analyse the influencing factors and their associated spatial spillover effects. The results show the following: (1) AGEE demonstrated steady improvement, with a mean value of 0.576, and was spatially concentrated along a northeast–southwest axis, exhibiting regional disparities and polarisation. (2) GTP consistently exceeded 1, indicating overall AGEE growth, primarily driven by technological scale expansion. Regional imbalances in AGEE growth had emerged, with heterogeneous causes across economic regions. Three identified AGEE improvement paths—technological catch-up, green innovation, and technological progress—varied by province, with green innovation being the most common priority. (3) AGEE exhibited spatial autocorrelation, with rural income, adequate irrigation, and cropping structure promoting AGEE. Effective irrigation also exhibited a positive spatial spillover effect, whereas industrial structure hindered AGEE. These findings provide valuable insights for advancing green agricultural practices and sustainable regional development. Full article

Today, there is an ongoing discourse on the notion of carbon farming on an international scale. The underlying factors contributing to this phenomenon are numerous. Firstly, the degradation of intensively farmed soils is increasing, and secondly, there is a clear need to restore their biodiversity. A multitude of pollutants stemming from agricultural production have incited the implementation of targeted measures, notably by the European Commission. Consequently, the adoption of the European Green Deal in Poland has prompted the agricultural sector to implement a series of modifications to its practices, with the objective of enhancing soil cultivation and animal husbandry methods. In response to these changes, the introduction of carbon farming practices is being proposed. These practices, which are to be implemented in Polish agriculture with the support of EU subsidies, are intended to mitigate the effects of climate change. This prompts further inquiry into the potential evolution of carbon farming practices and the extent of farmer interest in them. According to the available data, in Poland, 56% of the total agricultural area was covered by payments under the carbon farming eco-scheme. However, support was accessed by barely 31% of farms with an area of more than 1 ha. In turn, from a regional perspective, data analysis reveals significant regional differences in the use of support. Therefore, the purpose of this paper is to explore the structural, environmental, and production reasons behind differences in the use of the “Carbon farming and nutrient management“ eco-scheme across the Polish territory. The headline result is that participation is strongly associated with farm structure, moderately with production performance, and only weakly with environmental status. Full article

Underutilized leafy greens are considered as functional plant species primarily due to their resilience to abiotic stress factors, low nutrient requirements, and high nutritional value. Over the past 30 years, many experiments have been conducted to identify nutrient-efficient species, cultivars, landraces, and ecotypes, but few have successfully entered mainstream agriculture. The integration of these species into advanced horticultural systems, such as hydroponics, has the potential to further strengthen their impact on sustainable agriculture by minimizing use of resources, enabling year-round cultivation, and improving the nutritional profile of the harvested produce. As leafy vegetables, a primary food safety concern is the accumulation of nitrates in the leaves. In hydroponics, this issue is usually addressed by balancing the NH₄-N/total-N ratio (N_r) in the nutrient solution. Provided that the plant responses to high ammonia supply are species-dependent, three wild leafy greens, iceplant, corn salad, and common purslane, were grown in a soilless culture, with perlite as the substrate, under low (0.04) and high (0.12) N_r on a molar basis. Additionally, the potential of protein hydrolysates (PH) and seaweed extracts (SW) to alleviate plant tolerance to excess ammonia supply was also investigated. In terms of yield, high N_r led to significant yield restrictions in iceplant that reached 28%, while on corn salad, it had a positive impact, with yield increasing by 18%. Both biostimulant applications enhanced iceplant productivity only under optimal N_r conditions (0.04). Apart from yield responses, biofertilizers had no substantial impact on the plant nutrient profile. In contrast, high N_r suppressed nitrate accumulation in fresh leaves, while enhancing micronutrient uptake in all three plant species. In conclusion, this study highlights the pivotal role of biostimulants as plant stress protectors and growth regulators and identifies the optimal N_r ratio for maximizing the yield and quality performance of corn salad, iceplant, and common purslane in soilless cultivation systems. Full article

Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO₂e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO₂e/ha) and 2014 (6.52 × 10⁷ t CO₂e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article

Mangoes are an important part of Hainan’s tropical characteristic agriculture. In response to the requirements of building an ecological civilization pilot demonstration zone in Hainan, China, green and sustainable development will be the future development trend of the mango planting system. However, the economic benefits and environmental impact during its planting and management process remain unclear. This paper combines emergy, life cycle assessment (LCA), and economic analysis to compare the system sustainability, environmental impact, and economic benefits of the traditional mango cultivation system (TM) in Dongfang City, Hainan Province, and the early-maturing mango cultivation system (EM) in Sanya City. The emergy evaluation results show that the total emergy input of EM (1.37 × 10¹⁶ sej ha⁻¹) was higher than that of TM (1.32 × 10¹⁶ sej ha⁻¹). From the perspective of the emergy index, compared with TM, EM exerted less pressure on the local environment and has better stability and sustainability. This was due to the higher input of renewable resources in EM. The LCA results showed that based on mass as the functional unit, the potential environmental impact of the EM is relatively high, and its total environmental impact index was 18.67–33.19% higher than that of the TM. Fertilizer input and On-Farm emissions were the main factors causing environmental consequences. Choosing alternative fertilizers that have a smaller impact on the environment may effectively reduce the environmental impact of the system. The economic analysis results showed that due to the higher selling price of early-maturing mango, the total profit and cost–benefit ratio of the EM have increased by 55.84% and 36.87%, respectively, compared with the TM. These results indicated that EM in Sanya City can enhance environmental sustainability and boost producers’ annual income, but attention should be paid to the negative environmental impact of excessive fertilizer input. These findings offer insights into optimizing agricultural inputs for Hainan mango production to mitigate multiple environmental impacts while enhancing economic benefits, aiming to provide theoretical support for promoting the sustainable development of the Hainan mango industry. Full article

Accurate assessment of green productivity is essential for advancing sustainable agriculture in ecologically fragile regions. This study examined the evolution of agricultural green total factor productivity (AGTFP) in Tibet over the period 2002–2021 by applying a super-efficiency SBM-GML model that accounts for undesirable outputs. We decompose AGTFP into technical change and efficiency change, conduct redundancy analysis to identify sources of inefficiency and explore its spatiotemporal dynamics through kernel density estimation and convergence analysis. Results show that (1) AGTFP in Tibet grew at an average annual rate of 0.78%, slower than the national average of 1.6%; (2) labor input, livestock scale, and agricultural carbon emissions are major sources of redundancy, especially in pastoral regions; (3) technological progress is the main driver of AGTFP growth, while efficiency gains have a limited impact, reflecting a technology-led growth pattern; (4) AGTFP follows a “convergence-divergence-reconvergence” trend, with signs of conditional β convergence after controlling for regional heterogeneity. These findings highlight the need for region-specific green agricultural policies. Priority should be given to improving green technology diffusion and input allocation in high-altitude pastoral areas, alongside strengthening ecological compensation and interregional coordination to enhance green efficiency and promote high-quality development across Tibet. Full article

The rice-wheat rotation is the main agricultural cropping system in Jiangsu Province, playing a vital role in ensuring food security and promoting economic development. However, current research on rice-wheat systems mainly focuses on in-situ controlled experiments at the point scale, with limited studies addressing carbon footprint (CF) and energy balance (EB) at the regional scale and long time series. Therefore, we analyzed the evolution patterns of the CF and EB of the rice-wheat system in Jiangsu Province from 1980 to 2022, as well as their influencing factors. The results showed that the sown area and total yield of rice and wheat exhibited an increasing–decreasing–increasing trend during 1980–2022, while the yield per unit area increased continuously. The CF of rice and wheat increased by 4172.27 kg CO₂ eq ha⁻¹ and 2729.18 kg CO₂ eq ha⁻¹, respectively, with the greenhouse gas emissions intensity (GHGI) showing a fluctuating upward trend. Furthermore, CH₄ emission, nitrogen (N) fertilizer, and irrigation were the main factors affecting the CF of rice, with proportions of 36%, 20.26%, and 17.34%, respectively. For wheat, N fertilizer, agricultural diesel, compound fertilizer, and total N₂O emission were the primary contributors, accounting for 42.39%, 22.54%, 13.65%, and 13.14%, respectively. Among energy balances, the net energy (NE) of rice exhibited an increasing and then fluctuating trend, while that of wheat remained relatively stable. The energy utilization efficiency (EUE), energy productivity (EPD), and energy profitability (EPF) of rice showed an increasing and then decreasing trend, while wheat decreased by 46.31%, 46.31%, and 60.62% during 43 years, respectively. Additionally, N fertilizer, agricultural diesel, and compound fertilizer accounted for 43.91–45.37%, 21.63–25.81%, and 12.46–20.37% of energy input for rice and wheat, respectively. Moreover, emission factors and energy coefficients may vary over time, which is an important consideration in the analysis of long-term time series. This study analyzes the ecological and environmental effects of the rice-wheat system in Jiangsu Province, which helps to promote the development of agriculture in a green, low-carbon, and high-efficiency direction. It also offers a theoretical basis for constructing a low-carbon sustainable agricultural production system. Full article