Search Results (934)

The spatial layout of farmland involves coordinated planning across diverse functional zones. Irregular land boundaries and functional demands pose challenges to traditional CAD-based workflows and general optimization algorithms. To address these limitations, we propose an interactive farmland layout system based on the Graphic-Guided Evolutionary Layout (GGEL) algorithm. GGEL not only introduces a graph-based spatial pruning and encoding strategy to improve search efficiency, but also performs real-time spatial overlap detection based on functional region boundaries to ensure layout feasibility. Additionally, an interactive module enables real-time user customization to accommodate specific planning needs. Experimental results demonstrate that the system can efficiently generate complete multi-region layouts, significantly enhancing design productivity. A user study with 20 agricultural park experts confirms the system’s usability and effectiveness. This study highlights the potential of integrating evolutionary algorithms with topological graph representations to address the complex spatial planning requirements of digital agricultural parks. Full article

Soil erosion is a widespread problem leading to land degradation in many watersheds, including the Lato Basin, an Apulian permanent river that supplies water used for irrigation in many agricultural territories along the Ionian coast with considerable economic importance for crop production. The loss of fertile soil makes land less productive for agriculture; soil erosion decreases soil fertility, which can negatively affect crop yields. The present research aimed to determine soil loss (t/ha/year) in the Lato watershed in 2024, and then four ecosystem services—loss of carbon, habitat quality, crop productivity and sustainable tourism suitability—directly or indirectly linked to erosion, were defined and evaluated in monetary terms. These ecosystem service evaluations were made for the actual basin land use, and also for two hypothetical scenarios applying different afforestation strategies to the watershed. The first scenario envisages afforestation interventions in the areas with the highest erosion; the second scenario envisages afforestation interventions in the areas with medium erosion, cultivated with cereal crops. Each scenario was also used to evaluate the economic convenience and the effects of sustainable land management practices (e.g., reforestation) to reduce soil erosion and loss of ecosystem services. This study demonstrates that soil erosion is related to land use. It also underlines that reforestation reduces soil erosion and increases the value of ecosystem services. Furthermore, the economic analysis shows that crop productivity is the most incisive ecosystem service, as the lands with high productivity achieve higher economic values, making conversion to wooded areas economically disadvantageous if not supported with economic aid. The results of this study may help development of new management strategies for the Lato Basin, to be implemented through the distribution of community funds for rural development programs that consider the real economic productivity of each area through naturalistic engineering interventions. The reforestation measures need to be implemented over a long time frame to perform their functions; this requires relevant investments from the public sector due to cost management, requesting monetary compensation from EU funds for companies involved in forestation projects on highly productive areas that will bring benefits for the entire community. Full article

The primary objective of this study is to assess the techno-economic feasibility of an innovative solar energy generation system with a rainwater collection feature to generate electrical energy and meet irrigation needs in agriculture. The proposed system is designed for an agricultural area (Gonyeli, North Cyprus) with high solar potential and limited rainfall. In the present study, global rainfall datasets are utilized to assess the potential of rainwater harvesting at the selected site. Due to the lack of the measured rainfall data at the selected site, the accuracy of rainfall of nine global reanalysis and analysis datasets (CHIRPS, CFSR, ERA5-LAND, ERA5, ERA5-AG, MERRA2, NOAA CPC CMORPH, NOAA CPC DAILY GLOBAL, and TerraClimate) are evaluated by using data from ground-based observations collected from the Meteorological Department located in Lefkoşa, Northern Cyprus from 1981 to 2023. The results demonstrate that ERA5 outperformed the other datasets, yielding a high R-squared value along with a low mean absolute error (MAE) and root mean square error (RMSE). Based on the best dataset, the potential of the rainwater harvesting system is estimated by analyzing the monthly and seasonal rainfall patterns utilizing 65 different probability distribution functions for the first time. Three goodness-of-fit tests are utilized to identify the best-fit probability distribution. The results show that the Johnson and Wakeby SB distributions outperform the other models in terms of fitting accuracy. Additionally, the results indicate that the rainwater harvesting system could supply between 31% and 38% of the building’s annual irrigation water demand (204 m³/year) based on average daily rainfall and between 285% and 346% based on maximum daily rainfall. Accordingly, the system might be able to collect a lot more water than is needed for irrigation, possibly producing an excess that could be stored for non-potable uses during periods of heavy rainfall. Furthermore, the techno-economic feasibility of the proposed system is evaluated using RETScreen software (version 9.1, 2023). The results show that household energy needs can be met by the proposed photovoltaic system, and the excess energy is transferred to the grid. Furthermore, the cash flow indicates that the investor can expect a return on investment from the proposed PV system within 2.4 years. Consequently, the findings demonstrate the significance of this system for promoting resource sustainability and climate change adaptation. Besides, the developed system can also help reduce environmental impact and enhance resilience in areas that rely on water and electricity. Full article

Agroforestry involves maintaining trees alongside crops and is widely recognised to provide multiple benefits, including improving food security, production efficiency, and soil quality and mitigating climate change. However, in Sub-Saharan Africa, a predominantly dry landscape, various pressures are leading to the removal of trees from farmlands. Evidence from natural dryland systems shows that trees play a central role in regulating the key ecological processes of nutrient and water redistribution, an aspect also invoked in dryland agroecology. In this paper, we synthesise the ecophysiological functioning of trees, focusing on two key processes: water and nutrient redistribution. Additionally, we synthesise the influence of these functions on soil biotic interactions, detailing their ecological significance. Based on available evidence from both natural and agroecosystems, we review the role of tree ecophysiology in sustainable food production in dryland agroecosystems of Sub-Saharan Africa. We provide caveats related to prevalent interpretations and the current understanding of plant resource use in agroecology. Trees in agroforestry systems of Sub-Saharan Africa play a potentially critical role in the ecological intensification of food production. However, there is a lack of data on the roles of tree functions in enhancing crop yields and conserving resources in this region. Although evidence from natural drylands and indirect evidence from dryland agroforests indicate that tree ecophysiological functions may be crucial for ecological intensification of food production in Sub-Saharan Africa, many claims related to agroecosystems are overstated, underscoring the urgent need for focused research. Importantly, large trees on farms need to be conserved. To effectively exploit ecosystem services provided by trees, a key feature of ecological intensification, research tailored to local farm conditions is needed, with a focus on maintaining soil quality, securing long-term productivity, and conserving resources. Balancing agricultural intensification with ecological sustainability remains a challenge, yet it is vital for addressing food security, land degradation, and climate change. Full article

Monitoring and tracking the long-term dynamics of vineyard coverage and fresh grape production can support sustainable agricultural planning under evolving climate, market, and land-use pressures. This study presents a comprehensive, data-driven analysis of global viticulture trends from 1961 to 2023, integrating the official statistical database of the Food and Agriculture Organization of the United Nations (FAOSTAT) for grape-producing countries. We applied statistical trend analysis (Mann–Kendall test), Random Forest regression modeling, cross-correlation functions, and dissimilarity analysis to examine patterns and drivers of change in vineyard area, production volume, yield efficiency, and land-use intensity. Our results reveal a significant global decoupling of production from vineyard areas, driven by increasing yields and technological intensification, particularly in rapidly expanding table grape markets in Asia. While traditional European wine regions are reducing vineyard coverage, emerging producers such as China and India are achieving high production with improved land efficiency. Production volume emerged as the dominant predictor of vineyard-harvested areas, while climatic factors, urbanization, and socio-economic dynamics also exerted significant influence. Our findings point to growing polarization in production amounts, alongside convergence in yield and management efficiency across countries. These findings contribute to the understanding of global viticulture transformation and provide insights into optimizing land-use strategies for sustainable grape production under climate change and market evolution. Full article

The research on the optimization and transformation of rural “production-living-ecological” functions (PLEFs) is of great significance for rural revitalization and sustainable development. Existing studies predominantly evaluate rural PLEFs at the macro level, with few micro-village case studies, and particularly empirical studies in China’s plain agricultural areas. This study takes Caiwu Village, a rural revitalization demonstration village in Yuanyang County, Henan Province, China, as a typical case. First, we constructed a village PLEF classification system based on micro-scale land use types. Then, methods such as GIS spatial analysis, actor network analysis, and satisfaction fuzzy comprehensive evaluation were comprehensively used to systematically analyze the process, mechanism, and effects of the rural PLEF transformation in Caiwu Village. Our research indicates the following: (1) Caiwu Village has gone through three stages of transformation: traditional agriculture leading, ecological agriculture starting, and agriculture-tourism integration development, indicating a shift from traditional agricultural production functions to modern production-ecological composite functions. (2) The PLEF transformation in Caiwu Village resulted from the synergy of multiple actors, including governments, cooperatives, villagers, and water-soil resources, through administrative recruitment and market recruitment. Finally, (3) there are significant differences in the effects of rural PLEF transformation based on villagers’ perception. Specifically, villagers report the highest satisfaction with ecological function, followed by living function, and the lowest satisfaction with production function. This study provides empirical evidence for understanding the differentiated transformation of PLEFs in villages in plain agricultural areas. The research results can provide decision-making references for optimizing and improving the PLEFs of Caiwu Village and other similar villages. Full article

Saline–alkaline wetlands represent critical ecosystems for maintaining biodiversity, regulating hydrological processes, and supporting regional ecological resilience. However, the extent to which dominant vegetation regulates soil functionality and microbial assemblages in these unique saline systems remains insufficiently understood. In this study, we examined five characteristic vegetation types—Phragmites communis Trin., Typha angustifolia L., Bryophytes, Suaeda salsa (L.) Pall., Echinochloa phyllopogon (Stapf) Koss.—across the saline wetlands of Chagan Lake, northeast China, which are embedded in a heterogeneous matrix of forests, grasslands, and agricultural lands. Comprehensive assessments of soil physicochemical properties, enzyme activities, and bacterial communities were conducted, integrating high-throughput sequencing with multivariate statistical analyses. Our results revealed that vegetation cover markedly influenced soil attributes, particularly total organic carbon (TOC) and alkali-hydrolyzed nitrogen (AN), alongside key enzymatic functions such as urease and alkaline phosphatase activities. Proteobacteria, Actinobacteria, and Acidobacteria emerged as dominant bacterial phyla, with their relative abundances tightly linked to vegetation-induced shifts in soil environments. Notably, soils under E. phyllopogon demonstrated elevated bacterial diversity and enzymatic activities, underscoring the synergistic effects of plant selection on soil biogeochemical health. Structural equation modeling further elucidated complex pathways connecting vegetation, microbial diversity, soil quality, and enzymatic functioning. These findings emphasize the pivotal role of vegetation management in improving soil fertility, shaping microbial communities, and guiding the sustainable restoration of saline–alkaline wetlands under environmental stress. Full article

Smallholder farmers, key actors in agri-food supply chains, still face persistent challenges in applying sustainability strategies due to limited resources, context variability, and weak-performance monitoring systems. Their multidimensional needs, across economic, environmental, and social domains, are frequently inadequately captured by traditional key performance indicators (KPIs). This paper proposes an innovative framework to prioritize KPIs tailored to smallholders by integrating a multi-capital approach with expert-based and contradiction-resolving methods. A five-phase methodology is developed that combines Multi-Expert Fuzzy Quality Function Deployment (FQFD) and the Theory of Inventive Problem Solving (TRIZ). Expert input and field data identified 30 KPIs, narrowed to 19 via a capital-constrained algorithm; TRIZ resolved key contradictions like global warming versus land use efficiency. Expert input and field data are used to identify the sustainability capitals and KPIs, which are then ranked using FQFD and filtered using a capital-constrained algorithm. TRIZ is then used to address contradictions between indicators. Applied to a case study, the framework successfully identified a ranked, coherent set of sustainability KPIs. The sensitivity analysis confirmed the stability of the prioritization. TRIZ offered innovative solutions to trade-offs between key indicators (such as environmental impact versus productivity). This is the first known integration of FQFD and TRIZ in sustainability KPIs for smallholders. This approach is adaptable and replicable within similar agricultural contexts, thereby allowing informed and context-sensitive planning for sustainability. It provides actionable insights to guide smallholder-focused agricultural policies globally. Full article

With the intensification of global climate change, extreme weather events increasingly threaten water resources and agricultural systems. This study focuses on the Naoli River Basin, employing the Standardized Precipitation Actual Evapotranspiration Index (SPAEI), the Standardized Runoff Index (SRI), and the Standardized Surface Moisture Index (SSMI) to assess the spatiotemporal variability of meteorological, hydrological, and agricultural droughts. Drought events are identified based on travel time theory, and joint distributions of drought characteristics are modeled using optimized two- and three-dimensional copula functions. Lagged correlation and Bayesian conditional probability analyses are used to explore drought propagation processes. Key findings include (1) the SWAT model showed strong runoff simulation performance (R² > 0.75, NSE > 0.97), while the PLUS model achieved high land use simulation accuracy (overall accuracy > 0.93, Kappa > 0.85); (2) future projections suggest continued forest expansion and farmland decline, with water areas increasing under SSP245 and urban areas expanding under SSP585; (3) five CMIP6 models with high skill (r = 0.80, RMSE = 26.15) were selected via a Taylor diagram for scenario simulation; (4) copula-based joint drought probabilities vary temporally, with meteorological drought risks increasing under long-term moderate-emission scenarios, while hydrological and agricultural droughts show contrasting trends; (5) and under extreme meteorological drought, the conditional probability of extreme agricultural drought doubles from 0.12 (SSP245) to 0.24 (SSP585), indicating heightened vulnerability under high-emission pathways. These results offer critical insights for regional drought risk assessment and adaptive management under future climate scenarios. Full article

Global population growth and dietary transition have intensified demand for livestock and aquaculture products, thereby escalating demand for high-quality animal feed. Conventional protein sources, including soybean meal and fishmeal, face severe supply constraints driven by intense competition for arable land, worsening water scarcity, overexploitation of fishery resources, and rising production costs. These challenges are especially pronounced within agricultural systems. Evidence demonstrates that converting agriculturally derived organic wastes and agri-industrial by-products into feed protein can simultaneously alleviate these pressures, address agricultural waste disposal challenges, and reduce the carbon footprint associated with agricultural production. This review synthesizes fermentation processes for generating feed protein from agricultural organic wastes by employing functionally adapted microorganisms or microbial consortia. This distinguishes it from prior studies, which focused solely on single waste streams or individual microbial strains. It aims to advance feed protein production through an integrated approach that unites agricultural organic wastes, microorganisms, and fermentation processes, thereby promoting resource-oriented utilization of agricultural organic wastes and providing actionable solutions to alleviate feed protein scarcity. Full article

Fiber Bragg grating (FBG) sensing systems face significant challenges in resolving overlapping spectral signatures when multiple sensors operate within limited wavelength ranges, severely limiting sensor density and network scalability. This study introduces a novel Transformer-based neural network architecture that effectively resolves spectral overlap in both uniform and mixed-linewidth FBG sensor arrays, operating under bidirectional drift. The system uniquely combines dual-linewidth configurations with reflection and transmission mode fusion to enhance demodulation accuracy and sensing capacity. By integrating cloud computing, the model enables scalable deployment and near-real-time inference even in large-scale monitoring environments. The proposed approach supports self-healing functionality through dynamic switching between spectral modes during fiber breaks and enhances resilience against spectral congestion. Comprehensive evaluation across twelve drift scenarios demonstrates exceptional demodulation performance under severe spectral overlap conditions that challenge conventional peak-finding algorithms. This breakthrough establishes a new paradigm for high-density, distributed FBG sensing networks applicable to land monitoring, soil stability assessment, groundwater detection, maritime surveillance, and smart agriculture. Full article

Agricultural transformation is vital to sustainable development, allowing food security to be reconciled with environmental sustainability. However, the complex interplay between agricultural modernization and environmental systems, particularly the role of economic drivers, remains insufficiently understood. This study addresses this gap by analyzing the Fujian Province, a representative hilly region in southern China, during the period 2005–2021. We construct a comprehensive agricultural transformation evaluation index based on the “elements, structure, and function” framework and apply a modified coupling coordination model. Using random-effects and moderation-effect models, we assess the impact of agricultural productive services on this coordination and investigate the moderating role of agricultural industrial agglomeration. Our analysis identifies four distinct types of agricultural transformation in Fujian and shows that the overall coupling coordination degree improved steadily, rising from low to basic coordination over the study period. Agricultural productive services significantly enhance coordination, although their effects vary across transformation types. In addition, agricultural industrial agglomeration amplifies the positive influence of productive services, indicating a synergistic mechanism that supports sustainable agricultural development. These findings provide policy-relevant insights for East Asian economies with similar land endowments as well as for hilly regions worldwide. Full article

To address biodiversity degradation in Nationally Important Agricultural Heritage Systems, this study integrates multi-temporal remote sensing data (2000–2023) with the Biodiversity Maintenance Function (BMF) and InVEST Habitat Quality (HQ) models. We assess ecological changes in the Beijing–Tianjin–Hebei (BTH) region and 14 nationally recognized heritage systems. A dual-factor HQ–BMF coupling matrix was developed to trace ecological trajectories shaped by both natural and anthropogenic influences. Results show that (1) regional BMF followed a non-linear trend of increase, decline, and rebound between 2003 and 2023. The mean value rose from 0.1036 in 2003 to 0.1397 in 2023, despite intermediate fluctuations. In contrast, HQ declined steadily from 0.8734 in 2003 to 0.7729 in 2023, reflecting a continuous loss of high-quality habitats. (2) Nearly all heritage systems experienced phased BMF fluctuations—an initial rise, subsequent decline, and eventual recovery. At the same time, HQ showed a continuous decline in 8 of the 14 systems, indicating that more than half of the systems experienced sustained habitat degradation. (3) The HQ–BMF matrix revealed strong spatial heterogeneity. By 2023, only one site remained in a “dual-high” zone, while another had fallen into a “dual-low” condition, suggesting localized ecological degradation. These findings provide quantitative support for conservation strategies, ecological compensation, and land-use regulation in agricultural heritage systems. Full article

Phosphorus deficiency significantly limits soybean production across 74% of China’s arable land. This study investigated the molecular mechanisms enabling soybean to access insoluble phosphorus through transcriptome sequencing of the Heinong 48 variety across four developmental stages (Trefoil, Flower, Podding, and Post-podding). RNA-Seq analysis identified 2755 differentially expressed genes (DEGs), with 2506 up-regulated and 249 down-regulated genes. Notably, early developmental stages showed the most substantial transcriptional reprogramming, with 3825 DEGs in the Trefoil stage and 10,660 DEGs in the Flower stage, compared to only 523 and 393 DEGs in the Podding and Post-podding stages, respectively. Functional enrichment analysis revealed 44 significantly enriched GO terms in the Trefoil stage and 137 in the Flower stage, with 13 GO terms shared between both stages. KEGG pathway analysis identified 8 significantly enriched pathways in the Trefoil stage and 21 in the Flower stage, including key pathways related to isoflavonoid biosynthesis, alpha-linolenic acid metabolism, and photosynthesis. Among 87 differentially expressed transcription factors from 31 families, bHLH (8.08%), bZIP (7.18%), and WRKY (5.94%) were most prevalent. These findings provide genetic targets for developing soybean varieties with improved phosphorus acquisition capacity, potentially reducing fertilizer requirements and supporting more sustainable agricultural practices. Full article

This paper examines the characteristics of agriculture in High Nature Value farmlands (HNVf) in Poland and assesses their capacity to implement key environmental measures under the Common Agricultural Policy (CAP) 2023–2027. Using spatial and statistical analyses at the municipal level, the study compares agricultural structures, production types, participation in eco-schemes, organic farming and agri-environment-climate measures under the CAP 2023–2027. The delimitation of HNVf areas was based on the EU methodology, focusing on the extent of agricultural production and the environmental value of the surrounding landscape. The results indicate that HNVf areas are predominantly located in regions with challenging natural conditions, a high share of permanent grasslands, and limited capacity to diversify crop structures. Farms in these areas show lower participation in eco-schemes compared to more intensive farming regions, suggesting that current instruments may not fully align with the specific needs of low-intensity systems. In contrast, higher levels of engagement were observed in organic farming and agri-environment-climate measures in HNVf. These findings highlight the need for better-adapted CAP instruments that reflect the environmental and economic realities of HNVf areas. Enhancing support mechanisms for these regions is essential to safeguard biodiversity, promote sustainable land use, and maintain the socio-environmental functions of rural landscapes. Full article